Paper Citation Record · LEDGER

PDFBench: A Benchmark for De novo Protein Design from Function

As of 16 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 4 inbound Pith citation observations for arXiv:2505.20346.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.20346 v3

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:26:42.895098Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T20:05:06.168933Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-28T20:12:37.748336Z

Reference resolution

48 of 48 outbound references displayed

verified exact2
verified fuzzy38
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cfab0f4-127c-4291-a2a3-1ac662cc59bc · outbound

This paper cites The coming of age of de novo protein design.

PDFBench: A Benchmark for De novo Protein Design from Function The coming of age of de novo protein design

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:44.015124Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation acdab126-72a5-48c8-babe-02c86708f800 · outbound

This paper cites Computational protein design.

PDFBench: A Benchmark for De novo Protein Design from Function Computational protein design

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.992813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cec036e-9f48-4fc3-b8d3-dcef7a34c228 · outbound

This paper cites Computational design of enzymes for biotechnological applications.

PDFBench: A Benchmark for De novo Protein Design from Function Computational design of enzymes for biotechnological applications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.971519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e6b2f365-bc63-4122-9e57-678975a7dba2 · outbound

This paper cites De novo enzymes by computational design.

PDFBench: A Benchmark for De novo Protein Design from Function De novo enzymes by computational design

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.941368Z

Source-reported events for the cited work

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Observation 1a81f03e-3684-4e77-b749-abd2c5b1a150 · outbound

This paper cites Computational design of enzymes.

PDFBench: A Benchmark for De novo Protein Design from Function Computational design of enzymes

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.921964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 56a3339d-4f4a-4409-8a6d-810038e76936 · outbound

This paper cites Computational approaches for drug discovery.

PDFBench: A Benchmark for De novo Protein Design from Function Computational approaches for drug discovery

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.896102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d6de2378-6881-42db-acc1-c0d82d55c9b5 · outbound

This paper cites Computational approaches in drug designing.

PDFBench: A Benchmark for De novo Protein Design from Function Computational approaches in drug designing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.869399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 32807268-3108-4790-b130-319c36d740be · outbound

This paper cites Protgpt2 is a deep unsupervised language model for protein design.

PDFBench: A Benchmark for De novo Protein Design from Function Protgpt2 is a deep unsupervised language model for protein design

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.841448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e9f73137-8294-49d1-b000-abca37258cff · outbound

This paper cites Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds.

PDFBench: A Benchmark for De novo Protein Design from Function Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds

Reference 9

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Source-reported events for the cited work

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Observation dc59d7e2-10a8-42a2-84b9-0a02a7c762e9 · outbound

This paper cites De novo design of protein structure and function with rfdiffusion.

PDFBench: A Benchmark for De novo Protein Design from Function De novo design of protein structure and function with rfdiffusion

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.705738Z

Source-reported events for the cited work

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Observation 57af2fef-d32d-45f6-8ef7-9b2bfc3823d3 · outbound

This paper cites Large language models generate functional protein sequences across diverse families.

PDFBench: A Benchmark for De novo Protein Design from Function Large language models generate functional protein sequences across diverse families

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.808261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9d6ce6df-16f1-439c-8a29-ca206e76ae9f · outbound

This paper cites Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space.

PDFBench: A Benchmark for De novo Protein Design from Function Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.714328Z

Source-reported events for the cited work

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Observation d95b74a7-dbf0-4c65-9d2c-5aca2d9d4595 · outbound

This paper cites A text-guided protein design framework.

PDFBench: A Benchmark for De novo Protein Design from Function A text-guided protein design framework

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.790550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cb69cf21-525f-4d60-a147-cfeaaa97c216 · outbound

This paper cites Toward de novo protein design from natural language.

PDFBench: A Benchmark for De novo Protein Design from Function Toward de novo protein design from natural language

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.771189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a97d5ccf-db68-49ab-85a2-944ec1cfa4a0 · outbound

This paper cites Annotation-guided Protein Design with Multi-Level Domain Alignment.

PDFBench: A Benchmark for De novo Protein Design from Function Annotation-guided Protein Design with Multi-Level Domain Alignment

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:26:43.049391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 129ab8a0-77b3-4735-af3c-29bbeb3b320b · outbound

This paper cites Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models.

PDFBench: A Benchmark for De novo Protein Design from Function Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.732240Z

Source-reported events for the cited work

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Observation c1bd9f9a-6285-4e9c-a5fd-af0d351bd7f7 · outbound

This paper cites Continuous automated model evaluation (cameo) complementing the critical assessment of structure prediction in casp12.

PDFBench: A Benchmark for De novo Protein Design from Function Continuous automated model evaluation (cameo) complementing the critical assessment of structure prediction in casp12

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.750357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 799663b2-f44b-4d58-abe4-8a83e7378818 · outbound

This paper cites Interpro in 2022.

PDFBench: A Benchmark for De novo Protein Design from Function Interpro in 2022

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.731087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d3e33fa6-9367-45c2-84f6-e3d14e7d3a57 · outbound

This paper cites RITA: a Study on Scaling Up Generative Protein Sequence Models.

PDFBench: A Benchmark for De novo Protein Design from Function RITA: a Study on Scaling Up Generative Protein Sequence Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.746112Z

Source-reported events for the cited work

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Observation 25bea308-2d23-4c12-8494-6b53eee8c33a · outbound

This paper cites Protein generation with evolutionary diffusion: sequence is all you need.

PDFBench: A Benchmark for De novo Protein Design from Function Protein generation with evolutionary diffusion: sequence is all you need

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.711703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 20907fe7-9ff2-4c4c-9251-8660752f3320 · outbound

This paper cites Diffusion language models are versatile protein learners.

PDFBench: A Benchmark for De novo Protein Design from Function Diffusion language models are versatile protein learners

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.689614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 782d9e7d-9c18-4ecf-a552-77c9c0e3bd81 · outbound

This paper cites Deep sharpening of topological features for de novo protein design.

PDFBench: A Benchmark for De novo Protein Design from Function Deep sharpening of topological features for de novo protein design

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.660296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80851375-f277-4d1d-afe5-48fd7347ba56 · outbound

This paper cites Robust deep learning--based protein sequence design using proteinmpnn.

PDFBench: A Benchmark for De novo Protein Design from Function Robust deep learning--based protein sequence design using proteinmpnn

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.636785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af90611a-a32e-498e-bf1e-8a9435be426b · outbound

This paper cites Learning inverse folding from millions of predicted structures.

PDFBench: A Benchmark for De novo Protein Design from Function Learning inverse folding from millions of predicted structures

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.619462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation acc3a306-29a4-427d-a541-b0c275f28218 · outbound

This paper cites PiFold: Toward effective and efficient protein inverse folding.

PDFBench: A Benchmark for De novo Protein Design from Function PiFold: Toward effective and efficient protein inverse folding

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.776042Z

Source-reported events for the cited work

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Observation f679d876-51ab-4e8f-b313-5a16e8078742 · outbound

This paper cites Secondary structure-guided novel protein sequence generation with latent graph diffusion.

PDFBench: A Benchmark for De novo Protein Design from Function Secondary structure-guided novel protein sequence generation with latent graph diffusion

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.602884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c49a2be2-ad66-4975-aa6d-c67b9971032b · outbound

This paper cites Ppi-llama2: De novo generation of binding proteins conditioned on target sequence alone.

PDFBench: A Benchmark for De novo Protein Design from Function Ppi-llama2: De novo generation of binding proteins conditioned on target sequence alone

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.584346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fa946014-7613-4058-98fd-31edee98aae1 · outbound

This paper cites Progen2: exploring the boundaries of protein language models.

PDFBench: A Benchmark for De novo Protein Design from Function Progen2: exploring the boundaries of protein language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.563920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6713411b-e0bd-46f3-9c8d-7eddc808454e · outbound

This paper cites Illuminating protein space with a programmable generative model.

PDFBench: A Benchmark for De novo Protein Design from Function Illuminating protein space with a programmable generative model

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.542735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9789b4d8-fabb-4d86-b9ec-0b24be5d348d · outbound

This paper cites Simulating 500 million years of evolution with a language model.

PDFBench: A Benchmark for De novo Protein Design from Function Simulating 500 million years of evolution with a language model

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.525213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 41264594-1411-4982-8e09-2f91fcb3d5a6 · outbound

This paper cites De novo protein design using geometric vector field networks.

PDFBench: A Benchmark for De novo Protein Design from Function De novo protein design using geometric vector field networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.505973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 621345ae-0319-445e-bd61-16794dd8aece · outbound

This paper cites Proteus: exploring protein structure generation for enhanced designability and efficiency.

PDFBench: A Benchmark for De novo Protein Design from Function Proteus: exploring protein structure generation for enhanced designability and efficiency

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.485067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ccbace6b-cab9-4134-a0bc-a4668d086386 · outbound

This paper cites Carbonnovo: Joint design of protein structure and sequence using a unified energy-based model.

PDFBench: A Benchmark for De novo Protein Design from Function Carbonnovo: Joint design of protein structure and sequence using a unified energy-based model

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.465047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 07983744-5181-4e1e-9fa0-96542f7e54f2 · outbound

This paper cites DPLM-2: A Multimodal Diffusion Protein Language Model.

PDFBench: A Benchmark for De novo Protein Design from Function DPLM-2: A Multimodal Diffusion Protein Language Model

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.827297Z

Source-reported events for the cited work

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Observation aead6542-8275-488e-afed-b47e296b6c84 · outbound

This paper cites Uniprot: the universal protein knowledgebase.

PDFBench: A Benchmark for De novo Protein Design from Function Uniprot: the universal protein knowledgebase

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.446688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 22e59890-f123-469b-89bb-6230e080e653 · outbound

This paper cites Uniprotkb/swiss-prot: the manually annotated section of the uniprot knowledgebase.

PDFBench: A Benchmark for De novo Protein Design from Function Uniprotkb/swiss-prot: the manually annotated section of the uniprot knowledgebase

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.428629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0b66b9aa-493d-4e14-b811-e2503bbe69ee · outbound

This paper cites Neural text generation with unlikelihood training, 2019.

PDFBench: A Benchmark for De novo Protein Design from Function Neural text generation with unlikelihood training, 2019

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:42.840438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a138db99-a5e0-496e-8b1c-867f6d26842d · outbound

This paper cites Weinberger, and Yoav Artzi.

PDFBench: A Benchmark for De novo Protein Design from Function Weinberger, and Yoav Artzi

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.395317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2756d200-ca3b-47cc-9b22-b39fba19ccf1 · outbound

This paper cites Gpu-accelerated homology search with mmseqs2.

PDFBench: A Benchmark for De novo Protein Design from Function Gpu-accelerated homology search with mmseqs2

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.253224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 320e7ab1-19af-43d1-9669-e4c760d088a1 · outbound

This paper cites Language models of protein sequences at the scale of evolution enable accurate structure prediction.

PDFBench: A Benchmark for De novo Protein Design from Function Language models of protein sequences at the scale of evolution enable accurate structure prediction

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.233192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 256efd4d-4feb-4dcb-81df-ca4a32172134 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

PDFBench: A Benchmark for De novo Protein Design from Function Highly accurate protein structure prediction with alphafold

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.213540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6c05ed69-d9bf-4841-9982-a9da7bd15cbd · outbound

This paper cites u rgen J \.

PDFBench: A Benchmark for De novo Protein Design from Function u rgen J \

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.194571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bffd25dd-78a8-451e-acc8-141e41f46c9b · outbound

This paper cites Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

PDFBench: A Benchmark for De novo Protein Design from Function Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.176510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1b41945d-3b76-4d42-9715-e445663f8ccc · outbound

This paper cites Scoring function for automated assessment of protein structure template quality.

PDFBench: A Benchmark for De novo Protein Design from Function Scoring function for automated assessment of protein structure template quality

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.157787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bed67987-9cd5-474c-af97-79b8fa16af41 · outbound

This paper cites Protrek: Navigating the protein universe through tri-modal contrastive learning.

PDFBench: A Benchmark for De novo Protein Design from Function Protrek: Navigating the protein universe through tri-modal contrastive learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.140339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ce63ae21-63d6-4392-b1d3-64ae8601daad · outbound

This paper cites EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations.

PDFBench: A Benchmark for De novo Protein Design from Function EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:26:42.952626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c017a138-37e0-4edd-ba5b-77a23f4eafe8 · outbound

This paper cites Pearson correlation coefficient.

PDFBench: A Benchmark for De novo Protein Design from Function Pearson correlation coefficient

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.122119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 367e1a90-77a2-444a-ba5a-f95a07f5b970 · outbound

This paper cites Domain-specific language model pretraining for biomedical natural language processing.

PDFBench: A Benchmark for De novo Protein Design from Function Domain-specific language model pretraining for biomedical natural language processing

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:43.104017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 2f633100-3ede-47af-9e12-7644b1ad8386 · inbound

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design cites this paper.

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design PDFBench: A Benchmark for De novo Protein Design from Function

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:09.828184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f70c4af4-8f89-42da-837e-74c398546b70 · inbound

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design cites this paper.

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design PDFBench: A Benchmark for De novo Protein Design from Function

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:09.828184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation db546d35-0593-4342-9849-ecf83a1d8467 · inbound

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design cites this paper.

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design PDFBench: A Benchmark for De novo Protein Design from Function

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:09.828184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a2fdd61b-15d2-43fb-9a88-b00bcd557c97 · inbound

AMix-2: Establishing Protein as a Native Modality in Large Language Models cites this paper.

AMix-2: Establishing Protein as a Native Modality in Large Language Models PDFBench: A Benchmark for De novo Protein Design from Function

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:09.828184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.