S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning | Paper Citation Record

Observation c5b6073e-03af-4795-a597-fc0d3d46b7d4 · outbound

This paper cites Neutralizing monoclonal antibodies for treatment of COVID-19.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Neutralizing monoclonal antibodies for treatment of COVID-19

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.524887Z

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Observation 58a09d14-abbb-4965-8d06-f4f09ee9c70d · outbound

This paper cites SARS-CoV-2 RBD and Its Variants Can Induce Platelet Activa- tion and Clearance: Implications for Antibody Therapy and Vaccinations against COVID-19.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning SARS-CoV-2 RBD and Its Variants Can Induce Platelet Activa- tion and Clearance: Implications for Antibody Therapy and Vaccinations against COVID-19

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.512192Z

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Observation d8e0a5a5-a300-427d-916d-4af79083b484 · outbound

This paper cites Anti-TNFR2 Antibody-Conjugated PLGA Nanoparticles for Targeted Delivery of Adriamycin in Mouse Colon Cancer.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Anti-TNFR2 Antibody-Conjugated PLGA Nanoparticles for Targeted Delivery of Adriamycin in Mouse Colon Cancer

Reference 3

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Observation 9dc7a23a-dfb6-4d9c-a885-a60be23b12c0 · outbound

This paper cites FDA approves 100th monoclonal antibody product.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning FDA approves 100th monoclonal antibody product

Reference 4

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Observation 34daf721-db78-44d6-b362-67b87dcd613d · outbound

This paper cites Generative language modeling for antibody design.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Generative language modeling for antibody design

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.473246Z

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Observation 9bebb36b-60af-4264-ad4c-aea89d9423e6 · outbound

This paper cites De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.460328Z

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Observation cf87ee0a-f733-4c77-8b7c-25aa59582c7d · outbound

This paper cites Toward Unified AI Drug Discovery with Multimodal Knowledge.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Toward Unified AI Drug Discovery with Multimodal Knowledge

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.447386Z

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Observation 28efa657-4e3a-4b6e-a7db-d38d9565d508 · outbound

This paper cites Accurate prediction of antibody function and structure using bio-inspired antibody language model.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Accurate prediction of antibody function and structure using bio-inspired antibody language model

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.434195Z

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Observation 0a14a786-899d-4ba3-83f9-c510e452a1ed · outbound

This paper cites Sequence modeling and design from molecular to genome scale with Evo.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Sequence modeling and design from molecular to genome scale with Evo

Reference 9

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Observation af586c19-f0d7-4d06-a3f7-430ef7b0a071 · outbound

This paper cites A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.407750Z

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Observation 8fc4ffc2-aead-4bde-95aa-78ae04112c27 · outbound

This paper cites DeepSecE: A Deep-Learning-Based Framework for Multiclass Prediction of Secreted Proteins in Gram-Negative Bacteria.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning DeepSecE: A Deep-Learning-Based Framework for Multiclass Prediction of Secreted Proteins in Gram-Negative Bacteria

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.394235Z

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Observation 85fdf4b2-fd3e-4dd4-868f-c33eb67c23db · outbound

This paper cites Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.381150Z

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Observation 2c73a124-f92b-439e-97b3-ec94c5d8e60e · outbound

This paper cites Deciphering the language of antibodies using self-supervised learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Deciphering the language of antibodies using self-supervised learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.368128Z

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Observation 327c136c-f6c4-4510-8149-0ae4c571db79 · outbound

This paper cites Deciphering antibody affinity maturation with language models and weakly supervised learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Deciphering antibody affinity maturation with language models and weakly supervised learning

Reference 14

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Observation de9183f7-cbd1-4483-a825-21da88cd0843 · outbound

This paper cites AbLang: an antibody language model for completing antibody sequences.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning AbLang: an antibody language model for completing antibody sequences

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.354080Z

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Observation 3b5c513c-d303-45b7-9a51-c20c0e8246bb · outbound

This paper cites On Pre-trained Language Models for Antibody.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning On Pre-trained Language Models for Antibody

Reference 16

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Observation 158ce55a-837a-41b0-9f73-dea28a775e72 · outbound

This paper cites UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.328288Z

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Observation 3cdee592-4258-4b07-9569-2c1e9f87f6e5 · outbound

This paper cites The protein data bank.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning The protein data bank

Reference 18

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Observation c4945a64-4250-4e35-ae56-a4048cdb596d · outbound

This paper cites AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.301694Z

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Observation 44041683-0ec1-4868-8ce0-a097b19b2fad · outbound

This paper cites ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.288519Z

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Observation 12374e61-6ae2-4bf9-a87a-921779f90800 · outbound

This paper cites Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.275214Z

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Observation df0e4064-3735-493a-bdb6-95fa1f67aeab · outbound

This paper cites Fast and accurate protein structure search with Foldseek.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Fast and accurate protein structure search with Foldseek

Reference 22

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Observation 7062c010-43fa-42b9-83e1-ead71df9d6c9 · outbound

This paper cites Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.250159Z

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Observation 895493c6-6af9-4f6f-8d19-1816ea436a11 · outbound

This paper cites Clustering huge protein sequence sets in linear time.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Clustering huge protein sequence sets in linear time

Reference 24

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Observation a9f69864-83bf-4af1-95fb-468e7dfcf41e · outbound

This paper cites SAbDab: the structural antibody database.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning SAbDab: the structural antibody database

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.224375Z

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Observation b5a0e3f5-68e9-4e22-9540-8ab2ac862bb8 · outbound

This paper cites Neural discrete representation learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Neural discrete representation learning

Reference 26

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Observation 66cbf23a-c8fc-4fc0-8f13-8a891870213b · outbound

This paper cites SaProt: Protein Language Modeling with Structure-aware Vocabulary.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning SaProt: Protein Language Modeling with Structure-aware Vocabulary

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.199115Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ced21a7a-cd19-4511-82c4-8b9aca2fc536 · outbound

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

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 28

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Observation 8471399e-e1c9-49bf-a237-538c304a37e4 · outbound

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

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.185983Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea2f3b70-66b1-4dea-a422-48249dd84428 · outbound

This paper cites Visualizing data using t-SNE.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Visualizing data using t-SNE

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.172849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0b95a05c-ebdb-43ac-97bd-0e499177920b · outbound

This paper cites Reprogramming pretrained language models for antibody sequence infilling.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Reprogramming pretrained language models for antibody sequence infilling

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.159800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e5806f77-cc87-4d32-bad7-27e6fd06e360 · outbound

This paper cites In situ class switching and differentiation to IgA-producing cells in the gut lamina propria.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning In situ class switching and differentiation to IgA-producing cells in the gut lamina propria

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.146879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 26b4b441-e8b2-40a3-a566-365b2d88cae1 · outbound

This paper cites Optimization of therapeutic antibodies by pre- dicting antigen specificity from antibody sequence via deep learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Optimization of therapeutic antibodies by pre- dicting antigen specificity from antibody sequence via deep learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.132711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b69796b5-8349-4d12-b906-9a2e19a8ac9d · outbound

This paper cites Biological structure and function emerge from scaling unsu- pervised learning to 250 million protein sequences.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Biological structure and function emerge from scaling unsu- pervised learning to 250 million protein sequences

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.118822Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2163cc79-5f9b-43c3-acb8-124e35df2727 · outbound

This paper cites MSA Transformer.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning MSA Transformer

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c8d8e478-94dd-46ce-8870-9f7adc1340f4 · outbound

This paper cites Different B cell subpopulations show distinct patterns in their IgH repertoire metrics.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Different B cell subpopulations show distinct patterns in their IgH repertoire metrics

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.092922Z

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Observation c01a791a-7edd-44f7-8d40-644d3e6ee392 · outbound

This paper cites Antibody regulation of B cell development.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Antibody regulation of B cell development

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.079907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1eeb4c96-f4a8-4f04-acc9-43a7afa2e69e · outbound

This paper cites Differences in the composition of the human antibody repertoire by b cell subsets in the blood.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Differences in the composition of the human antibody repertoire by b cell subsets in the blood

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.066810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 55307e67-cb71-4787-b432-57463edcedd6 · outbound

This paper cites Analysis of the B cell receptor repertoire in six immune-mediated diseases.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Analysis of the B cell receptor repertoire in six immune-mediated diseases

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.053391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8ade0c41-ed49-4d03-adee-ade3349762c0 · outbound

This paper cites Paratome: an online tool for systematic identification of antigen-binding regions in antibodies based on sequence or structure.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Paratome: an online tool for systematic identification of antigen-binding regions in antibodies based on sequence or structure

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.039814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2023a3fc-06bf-424e-a856-16762702921c · outbound

This paper cites BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.026493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bc58d096-ed2e-46e3-aadd-b931db1ac239 · outbound

This paper cites ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.013356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 988253ca-1209-4fcd-a8fc-bffc4ee0c578 · outbound

This paper cites Antibody complementarity determining region design using high-capacity machine learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Antibody complementarity determining region design using high-capacity machine learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:18.000205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5a6cef48-17ff-4ef7-8c2c-81168e95e39d · outbound

This paper cites Learning the language of antibody hypervariability.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Learning the language of antibody hypervariability

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.987049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 029d06f1-1de7-4568-9cab-5cfcfd4d7d7f · outbound

This paper cites Enhancing antibody language models with structural infor- mation.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Enhancing antibody language models with structural infor- mation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.973264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a83b8d0d-1e52-4316-b529-3bb5e710b080 · outbound

This paper cites Antibody Representation Learning for Drug Discovery.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Antibody Representation Learning for Drug Discovery

Reference 46

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Observation 5975d027-2fb4-432d-8a5a-e54398e72952 · outbound

This paper cites Large scale paired antibody language models.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Large scale paired antibody language models

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-12T16:37:17.666544Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation de6f49b5-e870-421d-a145-fa5e4cb50544 · outbound

This paper cites A dataset comprised of binding interactions for 104,972 antibodies against a SARS-CoV-2 peptide.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning A dataset comprised of binding interactions for 104,972 antibodies against a SARS-CoV-2 peptide

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.959671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a3a1f6d6-f6f1-45bc-aa10-bdc9db50a7c4 · outbound

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

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.946316Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 27af5fa8-d3e3-4d8e-9dd6-a7f840e175f2 · outbound

This paper cites Iterative Refinement Graph Neural Net- work for Antibody Sequence-Structure Co-design.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Iterative Refinement Graph Neural Net- work for Antibody Sequence-Structure Co-design

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.933214Z

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Observation 4f1581ff-9f99-4f0e-b949-73729425e386 · outbound

This paper cites CoV-AbDab: the Coronavirus Antibody Database.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning CoV-AbDab: the Coronavirus Antibody Database

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.920175Z

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Observation 59b5c9ed-0106-423f-8599-f707883e6e53 · outbound

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

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Large language models generate functional protein sequences across diverse families

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.907301Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 78da0cde-4b6d-4ef8-9a8e-39e5b1e66843 · outbound

This paper cites RosettaAntibodyDesign (RAbD): A general framework for computational antibody design.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.894251Z

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Observation cfd5384d-ed4a-4895-b596-c2b11deb1c00 · outbound

This paper cites ProGen2: Exploring the bound- aries of protein language models.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning ProGen2: Exploring the bound- aries of protein language models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.881161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e1a87ea0-0779-4a0d-b865-4403b79bf95d · outbound

This paper cites Accurate structure prediction of biomolecular interactions with AlphaFold 3.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Accurate structure prediction of biomolecular interactions with AlphaFold 3

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.868161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a2ed0c09-f546-4858-b0f1-3c41db4bd27d · outbound

This paper cites Multi-Modal CLIP-Informed Protein Editing.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Multi-Modal CLIP-Informed Protein Editing

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T16:37:17.536543Z

Source-reported events for the cited work

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Observation be0746b5-775d-4184-b846-60e5d4cf500c · outbound

This paper cites Bridge-IF: Learning Inverse Protein Folding with Markov Bridges.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Bridge-IF: Learning Inverse Protein Folding with Markov Bridges

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T16:37:17.541482Z

Source-reported events for the cited work

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Observation 80057388-2857-4d3c-aa0c-b66ad6a7823b · outbound

This paper cites Enzyme Commission Number Prediction and Benchmarking with Hierarchical Dual-core Multitask Learning Framework.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Enzyme Commission Number Prediction and Benchmarking with Hierarchical Dual-core Multitask Learning Framework

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.855060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ac78044e-dab3-4b71-8400-051937b85328 · outbound

This paper cites GPT-4 Technical Report.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning GPT-4 Technical Report

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T16:37:17.548995Z

Source-reported events for the cited work

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Observation 3a5d51cf-581c-460c-be0e-7fe7e386ae6e · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Learning transferable visual models from natural lan- guage supervision

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.841645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3aac7676-a16c-4342-96c0-98aeec9928b8 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.828570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7f3acc68-cb0b-47e9-a95c-f9c249b48f9a · outbound

This paper cites ZeRO: Memory optimizations toward training trillion parameter models.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning ZeRO: Memory optimizations toward training trillion parameter models

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.815205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e38b0444-5016-4c06-b589-ce62336d9e34 · outbound

This paper cites Multi-level protein structure pre-training with prompt learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Multi-level protein structure pre-training with prompt learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.801395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2295553a-98ae-41cd-933a-bb054c66384a · outbound

This paper cites Structure-aware protein self-supervised learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Structure-aware protein self-supervised learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.786445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4273a85d-7b41-41c8-ae64-05c1a467f17a · outbound

This paper cites Enhancing protein lan- guage model with structure-based encoder and pre-training.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Enhancing protein lan- guage model with structure-based encoder and pre-training

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.771751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 63c0809d-c549-49dc-9065-2afe24fccf40 · outbound

This paper cites Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.758250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 29adb416-8607-46bf-a535-c04994b6a7f9 · outbound

This paper cites ProstT5: Bilingual Language Model for Protein Sequence and Structure.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning ProstT5: Bilingual Language Model for Protein Sequence and Structure

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.744177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cbb43b8a-dff8-4d23-95ca-a1c12475fe2c · outbound

This paper cites Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design.

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:37:17.730381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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