rewirebio.iobenchmarks
Benchmark

Zero-shot RNA language model benchmark (Wang et al. 2026)

Standardised zero-shot evaluation of 21 RNA language models, with DNA language models as reference controls, on attention-based secondary structure prediction, embedding-based RNA classification and likelihood-based mutational fitness prediction.

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36 protocols with results

Overview

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Results on linked records

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Methods and evaluation design

Procedure, tasks and evaluated configurations

Baseline coverage

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Baseline status by linked protocol

Protocol coverage CSV (gzip) · Model evaluation matrix (gzip) · Source table (gzip) · Release and checksums (gzip)

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Run instructions

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Strengths, limitations and unresolved questions

Evidence

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Evidence table

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Sources and history

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Technical metadata and extraction receipts

Stable ID: lit-rna-20261011-rnalm-zeroshot-benchmark-wang2026-zero-shot-rna-lm

areas
rna-transcriptomes
contexts
research
entity level
suite
version
Published 2026
task
Zero-shot RNA secondary structure, RNA classification and ncRNA fitness prediction
scope note
No fine-tuning. Secondary structure on TS (70 PDB structures) and TS-Hard (15) with a head-layer and threshold chosen on VL1 (40); classification of homologous versus non-homologous sequence pairs on RfamSample (561 Rfam families) and ArchiveII-Nr (1273 RNAs) from FFT or CLS embeddings; fitness on 31 RNAGym ncRNA deep mutational scanning assays (wild-type length <= 440 nt) with WT-LLR or PLL-D scores.
source locator
Main text Methods 'RNA secondary structure', 'RNA classification', 'RNA DMS assays'; Supplementary Tables 4-11
limitations
RNA-MSM is from the corresponding authors' group (Zhang et al.); the TS and VL1 sets come from the same group's earlier work (ref. 29).; Models are included per task only where their attention, embeddings or logits were available (Supplementary Table 3).
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