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Paper Citation Record · LEDGER

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery?

As of 9 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.

pith.paper-citation-record.v1
2608.06022 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:20:34.126087Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.959565Z digest=sha256:792927f82f4927fbe7d725f521a9814d7324a6e679ae624ac21c35220a4295b7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.963803Z digest=sha256:e0cd07304d131b99567d56780d23d4c4424fa4084f78992b439c0931d36d46c4

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.967569Z digest=sha256:ed5366662a51a1d499c772401dc8837a0e187b16fabe4534047acaf34f733faa

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.971070Z digest=sha256:32189326b9a8f42849ffb28d3c3a3ce9f7548bbbe20eba564723a2e33d2f97fa

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.974739Z digest=sha256:90f256646801c0f59353fcbdb20d2d6a95b428b4eaadcbb4b9afad94dab39935

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.978401Z digest=sha256:4884e327c48075a3087189e097b0cefed85710bbe35ab1aeb8d3fc5f2b53d449

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.982646Z digest=sha256:435ae71a4f1ed0175ee4298a151cd0fd0bb7e4d20b75fa81f1d872711d82ba1f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.986447Z digest=sha256:423e1f8d0c15e6998e62c7e238b65167dda11012b730dbc9b27bb7cd4e4cf924

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.991115Z digest=sha256:7f50865f772fb722bc6bce05a1ea4b84b425ff0d6906201628481c24abd4dc86

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.995255Z digest=sha256:def39fc13597e9b7b661a7b859234bbf63dc3a44514c5322c4dfe45bddb957cf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:33.999224Z digest=sha256:3b2faf5fc3b240295e931615b27172d1863e91273761cb96a1bd980781e94669

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.003470Z digest=sha256:371eb9ecf267f1dad84f7977d7402a9e6a6e89818ccb3fe61848ea6c79904d94

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.007132Z digest=sha256:d338a86b052519b5c7f0df90e35341f5928de70bc080c4dcd35259690a3f56a7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.011142Z digest=sha256:8e28e85a47182cfa1aff95310bdd5951aef5fc92d4bc85f8d6371b8ddd78fa8f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.014924Z digest=sha256:5d2ba44f18c86e4a1b82345615c99942c27ba25b5778e0f2dd867f7f97fe7f38

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
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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.018859Z digest=sha256:508f7e2a9d7b1172f54147dcef1272b5405f8c9c7e6340281ca4927ece71fad9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.022651Z digest=sha256:93e6da06e09f73be600d4dc59e52dfbd0bea247919a55d92771aa03767fb5842

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.

source=pdf_text observed=2026-08-07T19:20:34.026437Z digest=sha256:7689fa103673af97648ade93838164f133cca8f753128b30e67a49cb865a3b29

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.030695Z digest=sha256:3471c16522fe803a100e8e7b625804d6b7ab7ef78390221d1b36656b52f94958

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.034111Z digest=sha256:23f8b61c9135154cab220062153684758b3cfaccd67ac32df76feed2b807418f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.037655Z digest=sha256:63a884933f08eb40897015060fc9668e57a7ff10e46ed114c196c228336f81c9

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.040997Z digest=sha256:342cd5d641799c4dedc9519b2d83a844f0cde1ddcf8eba24ec6ce32391eea96f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.044131Z digest=sha256:0b93dfac2afd452c0b270c3a17a69addfccb98268d509d6e91ca41737dd7bf2d

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:20:34.047421Z digest=sha256:6f4e1ec9aa88e6562e420f5475ba4991638486cb9a31ad528f7cf9d615bd1f9c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.050643Z digest=sha256:c49c4750ca66cc5aa1620cb39f0e5ea732f85e529ed0871f134c950daa047239

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.

source=pdf_text observed=2026-08-07T19:20:34.054009Z digest=sha256:49a1975e218074733ccb146c60536a6eeac9a029d72c2fec93bb3ed60236ee03

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.057235Z digest=sha256:e966fe8b871de199b07b53e2e8164f6c701ef9445050dadf21c31bf8303648f7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.060755Z digest=sha256:40e48cb96f1a6e202eb161e57ae49cdd3ef2fddcdadc1e23e660f63299d0e938

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.063829Z digest=sha256:5f4bd4a80accb286c13e414a715c9a0ee6a650376b91f0a1d907b61a9073db03

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
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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.066873Z digest=sha256:469896ceb9abf5c837c8571f7bec623db7bc48b88203647e6db916604abdba27

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:20:34.070000Z digest=sha256:40b187be6df0f1a2061e33c7a26dacbec5c7c63029b254a633ebd14b1d8306af

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.073118Z digest=sha256:15b11890062ecc9bb4b5c73c5e2cb0889fa4e82f3e503858e3cc46b7bd45e543

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.

source=pdf_text observed=2026-08-07T19:20:34.076124Z digest=sha256:990a70a424cdc4699c8397e8168dbc91bf627df2dca445156410b30e38ab8a4f

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.

source=pdf_text observed=2026-08-07T19:20:34.080447Z digest=sha256:99144a74d9571b3760767382471e8ec77c9a90b11902ee71a42ff49ea4c5f7b0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.085096Z digest=sha256:96940860ee7f1d285983803d1a2949c5971b37af4c08ac49e6580616412691fd

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.

source=pdf_text observed=2026-08-07T19:20:34.089898Z digest=sha256:6fadb2ed1343cf66eca394c9b22944d32c427065603bfbc91d900acd4f64901c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.093678Z digest=sha256:6c66da3c59339e244469618f590a2d5bd7551b50deaf98f1b44650a18e22ea94

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.097361Z digest=sha256:a83cfef18205ddaa3ee605317cb11caaa590fb3b05b0dbc80603bf56ee4b98e5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.101070Z digest=sha256:5a4066a11418502a3d6c24d12717a4f624ec7552d6dd0ae277d570a77d25c60d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.104544Z digest=sha256:f95735939af871da3a3d49c5799944c8c3a71b9eb57ecebcd292500cae87efae

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.108028Z digest=sha256:7e92c7b51e4e5345ae31349636aeeee578a114d5ff55e957af93de4806671a43

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.111671Z digest=sha256:a7f783e4452891e4641f6751521c6b075931f7759ac339200997264c0284195c

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.

source=pdf_text observed=2026-08-07T19:20:34.115163Z digest=sha256:98bf4a75ac57859b1b55219caf71bfd8889589f2670177c79c23aaf833268fec

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.119046Z digest=sha256:70caf71ed2e9d9227b73e22fa7da5969006c814bf59d8b70b313fdc573dc5593

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.122433Z digest=sha256:e3f63bbcc7de7c945564830913243421586a1324873c6cb3d01a0754b60ecbc1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T19:20:34.126087Z digest=sha256:7a391de8a9c2aef7b0b4006079cd725ab4bca909edd19c2527b38f47039a279e

Pith citing papers

No inbound Pith citation observations are available.