EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? | Paper Citation Record

Observation c37ce88c-11db-49f8-8a0b-f57db0bcc2db · outbound

This paper cites CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:20:34.206439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7b444f48-4370-417f-b0d8-26f9ac90c3bc · outbound

This paper cites Identification of conformational b-cell epitopes in an antigen from its primary sequence.Immunome research, 6(1):6, 2010.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Identification of conformational b-cell epitopes in an antigen from its primary sequence.Immunome research, 6(1):6, 2010

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.734441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d0dadff-bcad-4306-bc8d-c8e6ca5bf756 · outbound

This paper cites an unresolved cited work.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:20:34.721672Z

Source-reported events for the cited work

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Observation 104a92e1-c22e-40fb-b77b-0ad5251cf34a · outbound

This paper cites Proteinglue multi-task benchmark suite for self-supervised protein modeling.Scientific Reports, 12(1):16047, 2022.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Proteinglue multi-task benchmark suite for self-supervised protein modeling.Scientific Reports, 12(1):16047, 2022

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.708798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f9a5c45c-d930-4cb4-b5c0-ad4253fff238 · outbound

This paper cites Flab: Benchmarking deep learning methods for antibody fitness prediction.BioRxiv, pp.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Flab: Benchmarking deep learning methods for antibody fitness prediction.BioRxiv, pp

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.695371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a19ba13c-608a-402a-8925-0698ac05fb50 · outbound

This paper cites Bepipred-3.0: Improved b-cell epitope prediction using protein language models.Protein Science, 31(12):e4497, 2022.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Bepipred-3.0: Improved b-cell epitope prediction using protein language models.Protein Science, 31(12):e4497, 2022

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.681338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9dcb1c08-0d88-4666-82ad-ed953dc3cb83 · outbound

This paper cites Flip: Benchmark tasks in fitness landscape inference for proteins.bioRxiv, pp.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Flip: Benchmark tasks in fitness landscape inference for proteins.bioRxiv, pp

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.668314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dee25990-05e8-4e1a-8caf-f033710bc184 · outbound

This paper cites Flip2: Expanding protein fitness landscape benchmarks for real-world machine learning applications.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Flip2: Expanding protein fitness landscape benchmarks for real-world machine learning applications

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.655077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a5affd50-62bc-4cd4-b768-925c00caf496 · outbound

This paper cites Sabdab: the structural antibody database.Nucleic acids research, 42(D1):D1140–D1146, 2014.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Sabdab: the structural antibody database.Nucleic acids research, 42(D1):D1140–D1146, 2014

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.641932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f53871a-4904-4fd2-bce3-934c37e4013b · outbound

This paper cites Predicting linear b-cell epitopes using string kernels.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Predicting linear b-cell epitopes using string kernels

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.629009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e6ab6aa9-07f2-4f62-a996-ef58a4479a45 · outbound

This paper cites others prottrans: Toward understanding the language of life through self-supervised learning.IEEE transactions on pattern analysis and machine intelligence, 44(10): 7112–7127, 2021.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? others prottrans: Toward understanding the language of life through self-supervised learning.IEEE transactions on pattern analysis and machine intelligence, 44(10): 7112–7127, 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.615566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3db1cab6-d1da-4bff-89d1-44bcb7d3424b · outbound

This paper cites Induction of hepatitis a virus-neutralizing antibody by a virus-specific synthetic peptide.Journal of virology, 55(3):836–839, 1985.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Induction of hepatitis a virus-neutralizing antibody by a virus-specific synthetic peptide.Journal of virology, 55(3):836–839, 1985

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.602700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 180e7760-2cde-4e04-b0b9-4b480a9f256f · outbound

This paper cites Mol-instructions: A large-scale biomolecular instruction dataset for large language models.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Mol-instructions: A large-scale biomolecular instruction dataset for large language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.589094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ca4c9c38-6d54-44af-aac4-68f56de0b452 · outbound

This paper cites Enhancing protein mutation effect prediction through a retrieval-augmented framework.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Enhancing protein mutation effect prediction through a retrieval-augmented framework

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.575729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fc4af6f0-88e8-435f-9ee6-4ba173e06064 · outbound

This paper cites Prediction of residues in discontinuous b-cell epitopes using protein 3d structures.Protein Science, 15(11):2558–2567, 2006.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Prediction of residues in discontinuous b-cell epitopes using protein 3d structures.Protein Science, 15(11):2558–2567, 2006

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.562930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9cbb9364-5ef5-465c-b262-852acd5afc99 · outbound

This paper cites Artificial intelligence foundation for therapeutic science.Nature chemical biology, 18(10):1033–1036, 2022.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Artificial intelligence foundation for therapeutic science.Nature chemical biology, 18(10):1033–1036, 2022

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.550150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ba66032c-8836-43ec-907f-02cff6e349d3 · outbound

This paper cites A semi-empirical method for prediction of antigenic determinants on protein antigens.FEBS letters, 276(1-2):172–174, 1990.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? A semi-empirical method for prediction of antigenic determinants on protein antigens.FEBS letters, 276(1-2):172–174, 1990

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.536776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f3ed8f5b-9553-4c97-bdbe-c517806595a2 · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.026437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53da5aa1-3f30-4c19-b344-8c71a310f0be · outbound

This paper cites Improved method for predicting linear b-cell epitopes.Immunome research, 2(1):2, 2006.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Improved method for predicting linear b-cell epitopes.Immunome research, 2(1):2, 2006

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.523237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 80f9d7ce-1ed0-49b4-82b7-d931c7415d6e · outbound

This paper cites Hotspot-driven peptide design via multi-fragment autoregressive extension.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Hotspot-driven peptide design via multi-fragment autoregressive extension

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.509949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4d3c2c7d-914b-4406-bc6a-c1511b4a2b16 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.497202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 75dcdb48-3417-4bcc-93d5-9dad7556a9ce · outbound

This paper cites Asep: Benchmarking deep learning methods for antibody-specific epitope prediction.Advances in Neural Information Processing Systems, 37:11700–11734, 2024.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Asep: Benchmarking deep learning methods for antibody-specific epitope prediction.Advances in Neural Information Processing Systems, 37:11700–11734, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.483931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 69b55ef7-5305-43f6-8b32-d4310ee9ffa0 · outbound

This paper cites What makes chain-of-thought prompting effective? a counterfactual study.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? What makes chain-of-thought prompting effective? a counterfactual study

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.469895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dc19871a-4321-4c21-8454-d88856518896 · outbound

This paper cites Large language models generate functional protein sequences across diverse families.Nature biotechnology, 41(8):1099–1106, 2023.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Large language models generate functional protein sequences across diverse families.Nature biotechnology, 41(8):1099–1106, 2023

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.047421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69bdc0a1-69ea-4656-8133-37108f56c17e · outbound

This paper cites Exploring Large Protein Language Models in Constrained Evaluation Scenarios within the FLIP Benchmark.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Exploring Large Protein Language Models in Constrained Evaluation Scenarios within the FLIP Benchmark

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:20:34.176460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bbfc16f4-d6c1-45d9-a877-5e18a8a7258f · outbound

This paper cites Progen2: exploring the boundaries of protein language models.Cell systems, 14(11):968–978, 2023.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Progen2: exploring the boundaries of protein language models.Cell systems, 14(11):968–978, 2023

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.054009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3b03958-0c06-4edb-9aab-09889b0a3333 · outbound

This paper cites Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.441677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 747f718a-c08f-4809-a705-976c99ed956f · outbound

This paper cites Proteingym: Large-scale benchmarks for protein fitness prediction and design.Advances in neural information processing systems, 36:64331–64379, 2023.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Proteingym: Large-scale benchmarks for protein fitness prediction and design.Advances in neural information processing systems, 36:64331–64379, 2023

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.427989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ed815e13-e470-4e9e-ac5f-51df8ee9d51f · outbound

This paper cites Ellipro: a new structure-based tool for the prediction of antibody epitopes.BMC bioinformatics, 9(1):514, 2008.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Ellipro: a new structure-based tool for the prediction of antibody epitopes.BMC bioinformatics, 9(1):514, 2008

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.413957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2f8b9ca7-99da-4894-995c-3c5741e1d6dd · outbound

This paper cites Evaluating protein transfer learning with tape.Biorxiv, pp.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Evaluating protein transfer learning with tape.Biorxiv, pp

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.401363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9359ffd5-c306-4e52-8737-206fb0bd3cef · outbound

This paper cites an unresolved cited work.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.070000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73f18c7c-7eb9-4c8b-9c51-01fb1806faed · outbound

This paper cites Prediction of continuous b-cell epitopes in an antigen using recurrent neural network.Proteins: Structure, Function, and Bioinformatics, 65(1):40–48, 2006.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Prediction of continuous b-cell epitopes in an antigen using recurrent neural network.Proteins: Structure, Function, and Bioinformatics, 65(1):40–48, 2006

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.381146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation feb0ffef-cad5-4009-a647-fe3aa2401227 · outbound

This paper cites Large Language Models Encode Clinical Knowledge.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Large Language Models Encode Clinical Knowledge

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.076124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5894ab2-5922-4835-bfc2-70575bb295f6 · outbound

This paper cites Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature biotechnology, 35(11):1026–1028, 2017.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature biotechnology, 35(11):1026–1028, 2017

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.080447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2702854-2ccb-4f6d-84b7-1900533e4f39 · outbound

This paper cites Seppa: a computational server for spatial epitope prediction of protein antigens.Nucleic acids research, 37(suppl_2): W612–W616, 2009.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Seppa: a computational server for spatial epitope prediction of protein antigens.Nucleic acids research, 37(suppl_2): W612–W616, 2009

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.361438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 270e307a-b47a-42f9-a794-8c01e3801781 · outbound

This paper cites Peta: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications.Journal of Cheminformatics, 16(1):92, 2024.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Peta: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications.Journal of Cheminformatics, 16(1):92, 2024

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.089898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d1990db-06cf-4f38-9082-1963f78b24d0 · outbound

This paper cites Atom3d: Tasks on molecules in three dimensions.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Atom3d: Tasks on molecules in three dimensions

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.340657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a2e8b049-3726-46a1-a302-2c3e0ae3e22f · outbound

This paper cites 2025 ginkgo datapoints antibody developability competition outcomes: limited model performance and a call for data standardization.MAbs, 18(1):2634216, 2026.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? 2025 ginkgo datapoints antibody developability competition outcomes: limited model performance and a call for data standardization.MAbs, 18(1):2634216, 2026

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.326509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b2978cc8-0c85-4a83-8dd3-59eb45537f73 · outbound

This paper cites The immune epitope database (iedb): 2024 update.Nucleic Acids Research, 53(D1):D436–D443, 2025.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? The immune epitope database (iedb): 2024 update.Nucleic Acids Research, 53(D1):D436–D443, 2025

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.312790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 090ab0bd-e97f-4aa4-8ea7-dd1ef37dcd26 · outbound

This paper cites Uni-rna: universal pre-trained models revolutionize rna research.bioRxiv, pp.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Uni-rna: universal pre-trained models revolutionize rna research.bioRxiv, pp

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.299356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 79e63694-5679-4e98-8002-a999169f719d · outbound

This paper cites Comparison of sequence-and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS Computational Biology, 21(5):e1013057, 2025.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Comparison of sequence-and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS Computational Biology, 21(5):e1013057, 2025

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.285917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c82c7516-c3f4-4c3e-991c-93b3ae5e4c8b · outbound

This paper cites Fafe: Immune complex modeling with geodesic distance loss on noisy group frames.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Fafe: Immune complex modeling with geodesic distance loss on noisy group frames

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.271248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1ec9ea33-25eb-4aca-900a-ecfc09f77659 · outbound

This paper cites Peer: a comprehensive and multi-task benchmark for protein sequence understanding.Advances in Neural Information Processing Systems, 35:35156–35173, 2022.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Peer: a comprehensive and multi-task benchmark for protein sequence understanding.Advances in Neural Information Processing Systems, 35:35156–35173, 2022

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T19:20:34.115163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14309334-23db-46af-9d33-5b21563ddb46 · outbound

This paper cites an unresolved cited work.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:20:34.248335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f62e36b5-9852-4d57-a6f8-4686c691b47a · outbound

This paper cites Benchmark for antibody binding affinity maturation and design.arXiv e-prints, pp.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Benchmark for antibody binding affinity maturation and design.arXiv e-prints, pp

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.234693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9ec14f46-fa30-4edb-adbf-9801a15bee8f · outbound

This paper cites Respond with ONLY a JSON object and no other text.

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery? Respond with ONLY a JSON object and no other text

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:20:34.220395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

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