Paper Citation Record · LEDGER

Computational Protein Science in the Era of Large Language Models (LLMs)

As of 11 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 8 inbound Pith citation observations for arXiv:2501.10282.

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

pith.paper-citation-record.v1
2501.10282 v2

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:19:27.926002Z

measured 108 of 108 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:07:37.376432Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T20:36:12.411481Z

Reference resolution

100 of 300 outbound references displayed

verified exact1
verified fuzzy0
unresolved99
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac3a4fab-c0c6-40e0-88e8-cfd698b5f8f0 · outbound

This paper cites Controllable protein design with language models.

Computational Protein Science in the Era of Large Language Models (LLMs) Controllable protein design with language models

Reference 1

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Observation e66dc523-4688-4dd1-bf62-306fae9e94c6 · outbound

This paper cites Learning the protein language: Evolution, structure, and function.

Computational Protein Science in the Era of Large Language Models (LLMs) Learning the protein language: Evolution, structure, and function

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.511539Z

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Observation 404cd7be-fbd5-4092-b1fd-302c67e976a2 · outbound

This paper cites Principles that govern the folding of protein chains.

Computational Protein Science in the Era of Large Language Models (LLMs) Principles that govern the folding of protein chains

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.515900Z

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Observation 48081467-c854-4346-8d14-bbb12026433e · outbound

This paper cites Exploring the structure and function paradigm.

Computational Protein Science in the Era of Large Language Models (LLMs) Exploring the structure and function paradigm

Reference 4

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Observation 6d5b6bf2-3fcd-47f0-a2f0-d15daf45cba2 · outbound

This paper cites Natural selection and the concept of a protein space.

Computational Protein Science in the Era of Large Language Models (LLMs) Natural selection and the concept of a protein space

Reference 5

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Observation 021b0e63-862f-43d0-9061-a3ac20d9d2d5 · outbound

This paper cites The language of pro- teins: Nlp, machine learning & protein sequences.

Computational Protein Science in the Era of Large Language Models (LLMs) The language of pro- teins: Nlp, machine learning & protein sequences

Reference 6

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Observation e24b25a8-27db-472f-a01d-e8bdd36040a1 · outbound

This paper cites Unified rational protein engineering with sequence-based deep representation learning.

Computational Protein Science in the Era of Large Language Models (LLMs) Unified rational protein engineering with sequence-based deep representation learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.535269Z

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Observation f73befcc-95e7-4703-b86a-0e93d21a8f6f · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

Computational Protein Science in the Era of Large Language Models (LLMs) Highly accurate protein structure prediction with alphafold

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.539690Z

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Observation f97bd55b-32ea-4f4e-bb96-fc2d02d9ed44 · outbound

This paper cites Accurate prediction of protein structures and interactions using a three-track neural network.

Computational Protein Science in the Era of Large Language Models (LLMs) Accurate prediction of protein structures and interactions using a three-track neural network

Reference 9

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Observation d991a72b-761c-48c6-a9d3-954a7e6e98c4 · outbound

This paper cites Deepgoplus: im- proved protein function prediction from sequence.

Computational Protein Science in the Era of Large Language Models (LLMs) Deepgoplus: im- proved protein function prediction from sequence

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.548041Z

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Observation 44611c11-e1d4-4bd2-a59b-4a3a9c524ae0 · outbound

This paper cites Prediction of designer-recombinases for dna editing with generative deep learning.

Computational Protein Science in the Era of Large Language Models (LLMs) Prediction of designer-recombinases for dna editing with generative deep learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.552095Z

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Observation 29db2917-5971-4801-ab7c-94582ade4991 · outbound

This paper cites Ig-vae: Generative modeling of protein structure by direct 3d coordinate generation.

Computational Protein Science in the Era of Large Language Models (LLMs) Ig-vae: Generative modeling of protein structure by direct 3d coordinate generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.555809Z

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Observation 95977e39-de82-41ad-a09c-a8b5782b5a52 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Computational Protein Science in the Era of Large Language Models (LLMs) BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 13

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Observation 4f97078c-05dd-4084-95c7-962b3889c604 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

Computational Protein Science in the Era of Large Language Models (LLMs) Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 14

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Observation 7d2a28cd-5739-40a3-b6d3-f27f8587cec2 · outbound

This paper cites Improving language understanding by generative pre- training.

Computational Protein Science in the Era of Large Language Models (LLMs) Improving language understanding by generative pre- training

Reference 15

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Observation 7953df85-a281-4982-91ee-4346a713d8ad · outbound

This paper cites Language models are unsupervised multitask learners.

Computational Protein Science in the Era of Large Language Models (LLMs) Language models are unsupervised multitask learners

Reference 16

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Observation 792d0258-8b1b-4c29-9f78-e134de215458 · outbound

This paper cites Language models are few-shot learners.

Computational Protein Science in the Era of Large Language Models (LLMs) Language models are few-shot learners

Reference 17

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Observation f9f8740d-ed2c-46d4-a7b0-7af055f65cae · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Computational Protein Science in the Era of Large Language Models (LLMs) LLaMA: Open and Efficient Foundation Language Models

Reference 18

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Observation 7bd037a6-250e-4e1f-9d50-cc3e4ed24e0e · outbound

This paper cites A Survey of Large Language Models.

Computational Protein Science in the Era of Large Language Models (LLMs) A Survey of Large Language Models

Reference 19

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Observation e6c1fe5c-0a77-4743-a8ce-936e5dc4e192 · outbound

This paper cites Recommender systems in the era of large language models (llms).

Computational Protein Science in the Era of Large Language Models (LLMs) Recommender systems in the era of large language models (llms)

Reference 20

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Observation 387bc5f0-2a8e-47cd-ade1-bd89e8f7e912 · outbound

This paper cites TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation.

Computational Protein Science in the Era of Large Language Models (LLMs) TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation

Reference 21

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Observation bc3f9d3d-f64a-4f40-9ceb-097acb5daccc · outbound

This paper cites A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics.

Computational Protein Science in the Era of Large Language Models (LLMs) A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics

Reference 22

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Observation 71785174-2397-48db-ac58-e086fedb5fae · outbound

This paper cites To Transformers and Beyond: Large Language Models for the Genome.

Computational Protein Science in the Era of Large Language Models (LLMs) To Transformers and Beyond: Large Language Models for the Genome

Reference 23

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Observation db2b7d7e-4fb6-4f50-b472-e6fba2c50579 · outbound

This paper cites Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective.

Computational Protein Science in the Era of Large Language Models (LLMs) Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective

Reference 24

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Observation 9d3ba3ed-5cb4-41ad-a4f9-513fcb01746a · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.

Computational Protein Science in the Era of Large Language Models (LLMs) Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 25

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Observation ba488107-6513-40ea-a597-1c709bd3e822 · outbound

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

Computational Protein Science in the Era of Large Language Models (LLMs) Protgpt2 is a deep unsupervised language model for protein design

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.617961Z

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Observation f40ad67f-a29f-4bb4-8a9c-bea4a5c87a3c · outbound

This paper cites xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein.

Computational Protein Science in the Era of Large Language Models (LLMs) xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Reference 27

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Observation 16459848-cd38-48b9-8578-d2394bfbbdc0 · outbound

This paper cites Msa transformer.

Computational Protein Science in the Era of Large Language Models (LLMs) Msa transformer

Reference 28

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Observation 6e234568-072e-47c3-870c-b6c4577dffcd · outbound

This paper cites Saprot: protein language modeling with structure- aware vocabulary.

Computational Protein Science in the Era of Large Language Models (LLMs) Saprot: protein language modeling with structure- aware vocabulary

Reference 29

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Observation 22ab2b80-1f5b-4a3e-a79b-057e72b980a3 · outbound

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

Computational Protein Science in the Era of Large Language Models (LLMs) Simulating 500 million years of evolution with a language model

Reference 30

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Observation 724ca5f2-bb53-426a-9f40-7a9f7f7da6fa · outbound

This paper cites ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing.

Computational Protein Science in the Era of Large Language Models (LLMs) ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing

Reference 31

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This paper cites BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations.

Computational Protein Science in the Era of Large Language Models (LLMs) BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations

Reference 32

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Observation 5e7a31e6-ea1c-4978-bc11-bf67d0e1c4ff · outbound

This paper cites Protein- chat: Towards achieving chatgpt-like functionalities on protein 3d structures.

Computational Protein Science in the Era of Large Language Models (LLMs) Protein- chat: Towards achieving chatgpt-like functionalities on protein 3d structures

Reference 33

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This paper cites Proteinnpt: improving protein property prediction and design with non-parametric transformers.

Computational Protein Science in the Era of Large Language Models (LLMs) Proteinnpt: improving protein property prediction and design with non-parametric transformers

Reference 34

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

Computational Protein Science in the Era of Large Language Models (LLMs) Large language models generate functional protein sequences across diverse families

Reference 35

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This paper cites Scientific Large Language Models: A Survey on Biological & Chemical Domains.

Computational Protein Science in the Era of Large Language Models (LLMs) Scientific Large Language Models: A Survey on Biological & Chemical Domains

Reference 36

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Observation 3c8265dc-a1ad-4bbf-a7e9-f9212dbb9572 · outbound

This paper cites Protein Language Models and Structure Prediction: Connection and Progression.

Computational Protein Science in the Era of Large Language Models (LLMs) Protein Language Models and Structure Prediction: Connection and Progression

Reference 37

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Observation 3024c045-ffdb-448a-bcc9-3ad1387af184 · outbound

This paper cites Learning functional properties of proteins with language models.

Computational Protein Science in the Era of Large Language Models (LLMs) Learning functional properties of proteins with language models

Reference 38

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This paper cites Designing proteins with language models.

Computational Protein Science in the Era of Large Language Models (LLMs) Designing proteins with language models

Reference 39

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This paper cites Mass spectrometry: principles and applications.

Computational Protein Science in the Era of Large Language Models (LLMs) Mass spectrometry: principles and applications

Reference 40

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This paper cites A new generation of crystallographic validation tools for the protein data bank.

Computational Protein Science in the Era of Large Language Models (LLMs) A new generation of crystallographic validation tools for the protein data bank

Reference 41

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Computational Protein Science in the Era of Large Language Models (LLMs) Outcome of the first electron microscopy validation task force meeting

Reference 42

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Computational Protein Science in the Era of Large Language Models (LLMs) Deep mutational scanning: a new style of protein science

Reference 43

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Computational Protein Science in the Era of Large Language Models (LLMs) Uniref clusters: a comprehensive and scalable alternative for improving sequence similarity searches

Reference 44

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This paper cites Nucleic acids research, 47(D1):D520–D528, 2019.

Computational Protein Science in the Era of Large Language Models (LLMs) Nucleic acids research, 47(D1):D520–D528, 2019

Reference 45

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Computational Protein Science in the Era of Large Language Models (LLMs) Gene ontology: tool for the unification of biology

Reference 46

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Computational Protein Science in the Era of Large Language Models (LLMs) Central dogma of molecular biology

Reference 47

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This paper cites Origin and evolution of the genetic code: the universal enigma.

Computational Protein Science in the Era of Large Language Models (LLMs) Origin and evolution of the genetic code: the universal enigma

Reference 48

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This paper cites One thousand families for the molecular biologist.

Computational Protein Science in the Era of Large Language Models (LLMs) One thousand families for the molecular biologist

Reference 49

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Computational Protein Science in the Era of Large Language Models (LLMs) The protein-folding problem, 50 years on

Reference 50

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This paper cites Learning from protein structure with geometric vector perceptrons.

Computational Protein Science in the Era of Large Language Models (LLMs) Learning from protein structure with geometric vector perceptrons

Reference 51

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Computational Protein Science in the Era of Large Language Models (LLMs) PiFold: Toward effective and efficient protein inverse folding

Reference 52

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This paper cites Exploring protein fitness landscapes by directed evolution.

Computational Protein Science in the Era of Large Language Models (LLMs) Exploring protein fitness landscapes by directed evolution

Reference 53

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This paper cites A Survey on Protein Representation Learning: Retrospect and Prospect.

Computational Protein Science in the Era of Large Language Models (LLMs) A Survey on Protein Representation Learning: Retrospect and Prospect

Reference 54

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This paper cites Convolutions are competitive with transformers for protein sequence pretraining.

Computational Protein Science in the Era of Large Language Models (LLMs) Convolutions are competitive with transformers for protein sequence pretraining

Reference 55

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This paper cites Prottrans: Toward understanding the language of life through self-supervised learning.

Computational Protein Science in the Era of Large Language Models (LLMs) Prottrans: Toward understanding the language of life through self-supervised learning

Reference 56

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This paper cites Protein Representation Learning by Geometric Structure Pretraining.

Computational Protein Science in the Era of Large Language Models (LLMs) Protein Representation Learning by Geometric Structure Pretraining

Reference 57

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This paper cites Lm-gvp: an extensible sequence and structure informed deep learning framework for protein property prediction.

Computational Protein Science in the Era of Large Language Models (LLMs) Lm-gvp: an extensible sequence and structure informed deep learning framework for protein property prediction

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-10T19:19:27.738939Z

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Computational Protein Science in the Era of Large Language Models (LLMs) A Systematic Study of Joint Representation Learning on Protein Sequences and Structures

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Computational Protein Science in the Era of Large Language Models (LLMs) Colabfold: making protein folding accessible to all

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Computational Protein Science in the Era of Large Language Models (LLMs) Single-sequence protein structure prediction using supervised transformer protein language models

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Computational Protein Science in the Era of Large Language Models (LLMs) A method for multiple-sequence-alignment-free protein structure prediction using a protein language model

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Computational Protein Science in the Era of Large Language Models (LLMs) Flip: Benchmark tasks in fitness landscape inference for proteins

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Computational Protein Science in the Era of Large Language Models (LLMs) Exploring machine learning algorithms and protein language models strategies to develop enzyme classi- fication systems

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Computational Protein Science in the Era of Large Language Models (LLMs) Protein–dna binding sites prediction based on pre-trained protein language model and contrastive learning

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Computational Protein Science in the Era of Large Language Models (LLMs) Genome-scale annotation of protein binding sites via language model and geometric deep learning

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Computational Protein Science in the Era of Large Language Models (LLMs) Unikp: a unified framework for the prediction of enzyme kinetic parameters

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Computational Protein Science in the Era of Large Language Models (LLMs) ProtChatGPT: Towards Understanding Proteins with Large Language Models

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Computational Protein Science in the Era of Large Language Models (LLMs) Machine learning for functional protein design

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Computational Protein Science in the Era of Large Language Models (LLMs) Language models enable zero-shot prediction of the effects of mutations on protein function

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Computational Protein Science in the Era of Large Language Models (LLMs) De novo protein design—from new structures to programmable functions

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Computational Protein Science in the Era of Large Language Models (LLMs) De novo design of protein structure and function with rfdiffusion

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Computational Protein Science in the Era of Large Language Models (LLMs) Illuminating protein space with a programmable generative model

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Computational Protein Science in the Era of Large Language Models (LLMs) Learning inverse folding from millions of predicted structures

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Computational Protein Science in the Era of Large Language Models (LLMs) Robust deep learning–based protein sequence design using proteinmpnn

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Computational Protein Science in the Era of Large Language Models (LLMs) Protein generation with evolutionary diffusion: sequence is all you need

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Computational Protein Science in the Era of Large Language Models (LLMs) Graph Machine Learning in the Era of Large Language Models (LLMs)

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Computational Protein Science in the Era of Large Language Models (LLMs) MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction

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Computational Protein Science in the Era of Large Language Models (LLMs) Scaling Laws for Neural Language Models

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Computational Protein Science in the Era of Large Language Models (LLMs) LoRA: Low-Rank Adaptation of Large Language Models

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Computational Protein Science in the Era of Large Language Models (LLMs) Chain-of-thought prompting elicits reasoning in large language models

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Computational Protein Science in the Era of Large Language Models (LLMs) PaLM-E: An Embodied Multimodal Language Model

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Computational Protein Science in the Era of Large Language Models (LLMs) Leveraging biomolecule and natural language through multi-modal learning: A survey

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Observation 99ad9e39-0c07-4695-b418-d99c63cde9fc · inbound

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