Contested result

RNA-FM and RNAErnie: Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning reverses the order

Low severity
Not yet reviewed
Ordering reversal
Different tasks across studies

Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning ranks RNA-FM above RNAErnie in 28 of 36 comparisons; other studies rank RNAErnie above RNA-FM in 6 of 6.

An automatic lead, not a finding of error. The results below are shown as published, everywhere on the site, until a reviewer decides otherwise.

Which studies agree

2 papers rank RNAErnie above RNA-FM in all 6 comparisons that are not ties (13 are ties). Zero-shot benchmarking of RNA language… ranks RNA-FM above RNAErnie in 28 of its 36 comparisons and RNAErnie higher in 8.

Rank RNAErnie higher (2): Benchmarking pre-trained genomic…, RNAGym fitness leaderboard
Rank RNA-FM higher (1): Zero-shot benchmarking of RNA language… (disagrees)
Mixed (0): none

Each paper sits where at least two thirds of its comparisons point; Mixed means neither model reaches two thirds. The larger, outlined dot is the paper that disagrees.

RNAErnie higherTieRNA-FM higherNumbers are counts of comparisons; the outlined bar is the paper that disagrees.

Papers compared (3)
Paper	Role	Ranks RNAErnie higher	Ranks RNA-FM higher	Ties
Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning and 1 more record · DOI	Disagrees	8	28	0
Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications and 1 more record · DOI	Agrees	2	0	13
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md · Repository	Agrees	4	0	0

Comparisons in Zero-shot benchmarking of RNA language… (36)

Protocol	Dataset	Metric	RNAErnie	RNA-FM	Higher
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	AUROC (WT-LLR; mean over assays), unitless	0.581	0.609	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	AUROC (WT-LLR; median over assays), unitless	0.568	0.6	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	MCC (WT-LLR; mean over assays), unitless	0.125	0.168	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	MCC (WT-LLR; median over assays), unitless	0.099	0.172	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	Absolute spearman correlation (WT-LLR; mean over assays), unitless	0.162	0.226	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	Absolute spearman correlation (WT-LLR; median over assays), unitless	0.133	0.207	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	AUROC (PLL-D; mean over assays), unitless	0.551	0.569	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	AUROC (PLL-D; median over assays), unitless	0.541	0.55	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	MCC (PLL-D; mean over assays), unitless	0.076	0.095	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	MCC (PLL-D; median over assays), unitless	0.051	0.075	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (mean over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	Absolute spearman correlation (PLL-D; mean over assays), unitless	0.1	0.14	RNA-FM
Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (median over assays)	RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	Absolute spearman correlation (PLL-D; median over assays), unitless	0.081	0.103	RNA-FM
Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (mean over structures)	TS test set (70 PDB structures) (Wang et al. 2026)	F1 (attention; mean over structures), unitless	0.288	0.267	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (median over structures)	TS test set (70 PDB structures) (Wang et al. 2026)	F1 (attention; median over structures), unitless	0.238	0.18	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (mean over structures)	TS test set (70 PDB structures) (Wang et al. 2026)	MCC (attention; mean over structures), unitless	0.29	0.273	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (median over structures)	TS test set (70 PDB structures) (Wang et al. 2026)	MCC (attention; median over structures), unitless	0.236	0.186	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (mean over structures)	TS-Hard test set (15 PDB structures) (Wang et al. 2026)	F1 (attention; mean over structures), unitless	0.24	0.224	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (median over structures)	TS-Hard test set (15 PDB structures) (Wang et al. 2026)	F1 (attention; median over structures), unitless	0.231	0.148	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (mean over structures)	TS-Hard test set (15 PDB structures) (Wang et al. 2026)	MCC (attention; mean over structures), unitless	0.243	0.231	RNAErnie
Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (median over structures)	TS-Hard test set (15 PDB structures) (Wang et al. 2026)	MCC (attention; median over structures), unitless	0.237	0.164	RNAErnie
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs), unitless	0.709	0.878	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	AUROC (FFT embedding; mean over random samplings of sequence pairs), unitless	0.854	0.953	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	F1 (FFT embedding; mean over random samplings of sequence pairs), unitless	0.775	0.889	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	MCC (FFT embedding; mean over random samplings of sequence pairs), unitless	0.532	0.771	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs), unitless	0.572	0.75	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	AUROC (FFT embedding; mean over random samplings of sequence pairs), unitless	0.765	0.872	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	F1 (FFT embedding; mean over random samplings of sequence pairs), unitless	0.713	0.789	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	MCC (FFT embedding; mean over random samplings of sequence pairs), unitless	0.367	0.568	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs), unitless	0.751	0.891	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	AUROC (CLS embedding; mean over random samplings of sequence pairs), unitless	0.88	0.93	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	F1 (CLS embedding; mean over random samplings of sequence pairs), unitless	0.801	0.898	RNA-FM
Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	RfamSample (561 Rfam families) (Wang et al. 2026)	MCC (CLS embedding; mean over random samplings of sequence pairs), unitless	0.594	0.803	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs), unitless	0.612	0.771	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	AUROC (CLS embedding; mean over random samplings of sequence pairs), unitless	0.784	0.861	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	F1 (CLS embedding; mean over random samplings of sequence pairs), unitless	0.728	0.803	RNA-FM
Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	ArchiveII-Nr (1273 RNAs) (Wang et al. 2026)	MCC (CLS embedding; mean over random samplings of sequence pairs), unitless	0.404	0.635	RNA-FM

Comparisons in Benchmarking pre-trained genomic… (15)

Protocol	Dataset	Metric	RNAErnie	RNA-FM	Higher
GTEx tissue-specific splicing prediction, Splice acceptors and donors (You et al. 2026 Supplementary Table 5)	GTEx-derived tissue-specific splice site usage dataset (You et al. 2026)	AUPRC (GTEx splicing task, Splice acceptors and donors, averaged over categories), fraction	0.806	0.796	RNAErnie
GTEx tissue-specific splicing prediction, Splice-15class (You et al. 2026 Supplementary Table 5)	GTEx-derived tissue-specific splice site usage dataset (You et al. 2026)	AUPRC (GTEx splicing task, Splice-15class, averaged over categories), fraction	0.687	0.677	RNAErnie
GTEx tissue-specific splicing prediction, Splice-53class (You et al. 2026 Supplementary Table 5)	GTEx-derived tissue-specific splice site usage dataset (You et al. 2026)	AUPRC (GTEx splicing task, Splice-53class, averaged over categories), fraction	0.685	0.684	Tie
NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, acceptors	Accuracy (NT-splice-sites-acceptors, fine-tuned), fraction	0.979	0.98	Tie
NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, acceptors	F1 (NT-splice-sites-acceptors, fine-tuned), fraction	0.979	0.98	Tie
NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, acceptors	Precision (NT-splice-sites-acceptors, fine-tuned), fraction	0.979	0.98	Tie
NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, acceptors	Recall (NT-splice-sites-acceptors, fine-tuned), fraction	0.979	0.98	Tie
NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, all sites	Accuracy (NT-splice-sites-all, fine-tuned), fraction	0.981	0.981	Tie
NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, all sites	F1 (NT-splice-sites-all, fine-tuned), fraction	0.981	0.981	Tie
NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, all sites	Precision (NT-splice-sites-all, fine-tuned), fraction	0.981	0.981	Tie
NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, all sites	Recall (NT-splice-sites-all, fine-tuned), fraction	0.981	0.981	Tie
NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, donors	Accuracy (NT-splice-sites-donors, fine-tuned), fraction	0.983	0.984	Tie
NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, donors	F1 (NT-splice-sites-donors, fine-tuned), fraction	0.983	0.984	Tie
NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, donors	Precision (NT-splice-sites-donors, fine-tuned), fraction	0.983	0.984	Tie
NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4)	Nucleotide Transformer benchmark splice-site dataset, donors	Recall (NT-splice-sites-donors, fine-tuned), fraction	0.983	0.984	Tie

Comparisons in RNAGym fitness leaderboard (4)

Protocol	Dataset	Metric	RNAErnie	RNA-FM	Higher
RNAGym v0.1.1 fitness, signed Spearman, Aptamer	RNAGym Aptamer DMS assays (2)	Spearman (mean signed Spearman over the 2 Aptamer assays), unitless	0.0306	0.0004	RNAErnie
RNAGym v0.1.1 fitness, signed Spearman, macro over 3 ncRNA categories	RNAGym ncRNA DMS assays (31)	Spearman (macro-mean over 3 ncRNA categories (equal category weights)), unitless	0.194	0.101	RNAErnie
RNAGym v0.1.1 fitness, signed Spearman, Ribozyme	RNAGym Ribozyme DMS assays (26)	Spearman (mean signed Spearman over the 26 Ribozyme assays), unitless	0.134	-0.0303	RNAErnie
RNAGym v0.1.1 fitness, signed Spearman, tRNA	RNAGym tRNA DMS assays (3)	Spearman (mean signed Spearman over the 3 tRNA assays), unitless	0.416	0.334	RNAErnie

What disagrees

Other studies: rank RNAErnie above RNA-FM in 6 of 6 comparisons
This study: ranks RNA-FM above RNAErnie in 28 of 36 comparisons

Compared: RNA-FM, RNAErnie
Study that disagrees: Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning, Zero-shot benchmarking of RNA language models: Supplementary Information
Other studies: Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications, You et al. 2026, Supplementary Information, RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md
Rule: Ordering reversal; different tasks across studies
Model identity: Matched across studies partly through links not yet reviewed

The compared numbers

Each value links to its result record and source. Compare values within one protocol; the rule compares rankings, not raw values across protocols.

In the study that disagrees (72)
Study	Tool	Protocol or benchmark	Metric	Value
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (mean over assays)	AUROC (WT-LLR; mean over assays)	0.609±0.081
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (median over assays)	AUROC (WT-LLR; median over assays)	0.6
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (mean over assays)	MCC (WT-LLR; mean over assays)	0.168±0.125
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays)	MCC (WT-LLR; median over assays)	0.172
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (mean over assays)	Absolute spearman correlation (WT-LLR; mean over assays)	0.226±0.170
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (median over assays)	Absolute spearman correlation (WT-LLR; median over assays)	0.207
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (mean over assays)	AUROC (PLL-D; mean over assays)	0.569±0.057
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (median over assays)	AUROC (PLL-D; median over assays)	0.55
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (mean over assays)	MCC (PLL-D; mean over assays)	0.095±0.085
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (median over assays)	MCC (PLL-D; median over assays)	0.075
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (mean over assays)	Absolute spearman correlation (PLL-D; mean over assays)	0.140±0.116
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (median over assays)	Absolute spearman correlation (PLL-D; median over assays)	0.103
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (mean over structures)	F1 (attention; mean over structures)	0.267±0.239
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (median over structures)	F1 (attention; median over structures)	0.18
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (mean over structures)	MCC (attention; mean over structures)	0.273±0.239
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (median over structures)	MCC (attention; median over structures)	0.186
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (mean over structures)	F1 (attention; mean over structures)	0.224±0.228
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (median over structures)	F1 (attention; median over structures)	0.148
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (mean over structures)	MCC (attention; mean over structures)	0.231±0.228
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (median over structures)	MCC (attention; median over structures)	0.164
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs)	0.878±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (FFT embedding; mean over random samplings of sequence pairs)	0.953±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (FFT embedding; mean over random samplings of sequence pairs)	0.889±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (FFT embedding; mean over random samplings of sequence pairs)	0.771±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs)	0.750±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (FFT embedding; mean over random samplings of sequence pairs)	0.872±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (FFT embedding; mean over random samplings of sequence pairs)	0.789±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (FFT embedding; mean over random samplings of sequence pairs)	0.568±0.002
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs)	0.891±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (CLS embedding; mean over random samplings of sequence pairs)	0.930±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (CLS embedding; mean over random samplings of sequence pairs)	0.898±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (CLS embedding; mean over random samplings of sequence pairs)	0.803±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs)	0.771±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (CLS embedding; mean over random samplings of sequence pairs)	0.861±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (CLS embedding; mean over random samplings of sequence pairs)	0.803±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNA-FM (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (CLS embedding; mean over random samplings of sequence pairs)	0.635±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (mean over assays)	AUROC (WT-LLR; mean over assays)	0.581±0.071
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, AUC (median over assays)	AUROC (WT-LLR; median over assays)	0.568
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (mean over assays)	MCC (WT-LLR; mean over assays)	0.125±0.105
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays)	MCC (WT-LLR; median over assays)	0.099
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (mean over assays)	Absolute spearman correlation (WT-LLR; mean over assays)	0.162±0.148
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, SR (median over assays)	Absolute spearman correlation (WT-LLR; median over assays)	0.133
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (mean over assays)	AUROC (PLL-D; mean over assays)	0.551±0.045
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, AUC (median over assays)	AUROC (PLL-D; median over assays)	0.541
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (mean over assays)	MCC (PLL-D; mean over assays)	0.076±0.069
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, MCC (median over assays)	MCC (PLL-D; median over assays)	0.051
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (mean over assays)	Absolute spearman correlation (PLL-D; mean over assays)	0.100±0.092
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), PLL-D, SR (median over assays)	Absolute spearman correlation (PLL-D; median over assays)	0.081
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (mean over structures)	F1 (attention; mean over structures)	0.288±0.223
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, F1 score (median over structures)	F1 (attention; median over structures)	0.238
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (mean over structures)	MCC (attention; mean over structures)	0.290±0.221
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS test set (70 PDB structures), attention, MCC (median over structures)	MCC (attention; median over structures)	0.236
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (mean over structures)	F1 (attention; mean over structures)	0.240±0.152
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, F1 score (median over structures)	F1 (attention; median over structures)	0.231
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (mean over structures)	MCC (attention; mean over structures)	0.243±0.152
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot secondary structure, TS-Hard test set (15 PDB structures), attention, MCC (median over structures)	MCC (attention; median over structures)	0.237
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs)	0.709±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (FFT embedding; mean over random samplings of sequence pairs)	0.854±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (FFT embedding; mean over random samplings of sequence pairs)	0.775±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (FFT embedding; mean over random samplings of sequence pairs)	0.532±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (FFT embedding; mean over random samplings of sequence pairs)	0.572±0.002
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (FFT embedding; mean over random samplings of sequence pairs)	0.765±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (FFT embedding; mean over random samplings of sequence pairs)	0.713±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), FFT embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (FFT embedding; mean over random samplings of sequence pairs)	0.367±0.011
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs)	0.751±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (CLS embedding; mean over random samplings of sequence pairs)	0.880±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (CLS embedding; mean over random samplings of sequence pairs)	0.801±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot family classification, RfamSample (561 Rfam families), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (CLS embedding; mean over random samplings of sequence pairs)	0.594±0.002
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, 1 − OR (mean over repeated random samplings of sequence pairs)	One minus overlap ratio (CLS embedding; mean over random samplings of sequence pairs)	0.612±0.000
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, AUC (mean over repeated random samplings of sequence pairs)	AUROC (CLS embedding; mean over random samplings of sequence pairs)	0.784±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, F1 (mean over repeated random samplings of sequence pairs)	F1 (CLS embedding; mean over random samplings of sequence pairs)	0.728±0.001
Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning	RNAErnie (zero-shot, Wang et al. 2026)	Wang et al. 2026 zero-shot RNA type classification, ArchiveII-Nr (1273 RNAs), CLS embedding, MCC (mean over repeated random samplings of sequence pairs)	MCC (CLS embedding; mean over random samplings of sequence pairs)	0.404±0.002

In the other studies (12)
Study	Tool	Protocol or benchmark	Metric	Value
Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information	RNAErnie fine-tuned with an appended convolutional layer (You et al. 2026)	GTEx tissue-specific splicing prediction, Splice acceptors and donors (You et al. 2026 Supplementary Table 5)	AUPRC (GTEx splicing task, Splice acceptors and donors, averaged over categories)	0.8063(0.0015)
Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information	RNAFM fine-tuned with an appended convolutional layer (You et al. 2026)	GTEx tissue-specific splicing prediction, Splice acceptors and donors (You et al. 2026 Supplementary Table 5)	AUPRC (GTEx splicing task, Splice acceptors and donors, averaged over categories)	0.7959(0.0011)
Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information	RNAErnie fine-tuned with an appended convolutional layer (You et al. 2026)	GTEx tissue-specific splicing prediction, Splice-15class (You et al. 2026 Supplementary Table 5)	AUPRC (GTEx splicing task, Splice-15class, averaged over categories)	0.6868(0.0055)
Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information	RNAFM fine-tuned with an appended convolutional layer (You et al. 2026)	GTEx tissue-specific splicing prediction, Splice-15class (You et al. 2026 Supplementary Table 5)	AUPRC (GTEx splicing task, Splice-15class, averaged over categories)	0.6770(0.0033)
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-ERNIE (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, Aptamer	Spearman (mean signed Spearman over the 2 Aptamer assays)	0.0306
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-ERNIE (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, macro over 3 ncRNA categories	Spearman (macro-mean over 3 ncRNA categories (equal category weights))	0.194
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-ERNIE (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, Ribozyme	Spearman (mean signed Spearman over the 26 Ribozyme assays)	0.134
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-ERNIE (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, tRNA	Spearman (mean signed Spearman over the 3 tRNA assays)	0.416
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-FM (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, Aptamer	Spearman (mean signed Spearman over the 2 Aptamer assays)	0.0004
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-FM (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, macro over 3 ncRNA categories	Spearman (macro-mean over 3 ncRNA categories (equal category weights))	0.101
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-FM (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, Ribozyme	Spearman (mean signed Spearman over the 26 Ribozyme assays)	-0.0303
RNAGym fitness leaderboard (v0.1.1), leaderboard/fitness/README.md	RNA-FM (RNAGym fitness leaderboard v0.1.1)	RNAGym v0.1.1 fitness, signed Spearman, tRNA	Spearman (mean signed Spearman over the 3 tRNA assays)	0.334

Follow-up

Current state: Not yet reviewed.

No one has reviewed this finding yet.

How to help resolve this

If you know why these studies disagree, for example a different population, metric or preprocessing step, or you have a corrected value, tell us through the contribution form. A reviewer checks every submission against its source before anything changes, and the step is added to the follow-up above.

Finding discrepancy-13c99a7d8e71874b · All contested results · How findings are made and followed up