LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet?
Primary source retrieved and hashed for the therapeutic target validation use-case pass.
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
22 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.access_and_reuse CC-BY-4.0 permits redistribution of the article bytes. Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.archive_note Not archived in the batch although the licence permits it: the PDF is 475,883 bytes and the repository keeps releases small. The artifact_sha256 pins the bytes that were read. Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.artifact_sha256 7dda0b590f2736b7d30e48b97167a0868a2b4bde253589d8aff7929d01506ff9 Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.artifact_url https://aclanthology.org/2025.findings-emnlp.838.pdf Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.doi 10.48550/arXiv.2509.21403 Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.extraction_method pdftotext -layout text layer, parsed by extract/extract_target_validation.py Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.licence CC-BY-4.0 Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.media_type application/pdf Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.publication_status peer_reviewed Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.retrieved_at 2026-10-09T20:55:36Z Source metadata | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? No field-specific location recorded Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
Sources and history
Release 2026-10-10-7fcc3e48a123 · Record review: source checked
Technical metadata and extraction receipts
Stable ID: tgtval-20261009-source-gupta2025
- areas
- cells-tissues
- contexts
- research
- url
- https://aclanthology.org/2025.findings-emnlp.838/
- artifact url
- https://aclanthology.org/2025.findings-emnlp.838.pdf
- version
- Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510
- retrieved at
- 2026-10-09T20:55:36Z
- artifact sha256
- 7dda0b590f2736b7d30e48b97167a0868a2b4bde253589d8aff7929d01506ff9
- publication status
- peer_reviewed
- licence
- CC-BY-4.0
- media type
- application/pdf
- doi
- 10.48550/arXiv.2509.21403
- source locator
- Full artifact bytes; per-record locators on each record
- access and reuse
- CC-BY-4.0 permits redistribution of the article bytes.
- archive note
- Not archived in the batch although the licence permits it: the PDF is 475,883 bytes and the repository keeps releases small. The artifact_sha256 pins the bytes that were read.
- extraction method
- pdftotext -layout text layer, parsed by extract/extract_target_validation.py
- version note
- The DOI recorded is the arXiv preprint (arXiv:2509.21403) of the same work; the bytes read are the ACL Anthology version of record.