Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T19:20:34.126087Z
Paper Citation Record · LEDGER
EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery?
As of 16 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2608.06022.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
46 of 46 outbound references displayed
- verified exact2
- verified fuzzy34
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.