Hugging Face Trending Papers July 7, 2026

AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking

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Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery. However, existing methods treat affinity comparisons independently and ignore the contextual information encoded in other labeled comparisons, limiting their ability to capture antigen-specific binding landscapes.

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arXiv AI

Jul 8

AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking

arXiv:2607. 05846v1 Announce Type: cross Abstract: Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery.

By Zhiyuan Chen, Jing Hu, Junzhe Wang, Yueyang Huang, Xinyi Yang, Zhaoyang Wang, Feng Zhu

llms benchmarks

arXiv Machine Learning

Jul 21

Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision

arXiv:2607. 16263v1 Announce Type: new Abstract: Antibody expression ranking is a critical task in antibody design, yet its modelling is severely hindered by the scarcity of labeled experimental data.

By Josh Qixuan Sun, Morteza Babaie, Wenyang Hou, Mark Crowley, David Young

llms reinforcement-learning safety

arXiv Machine Learning

Sep 2

Learning Task-Specific Antibody Representations via Function-Aware Masking

arXiv:2609.00518v1 Announce Type: new Abstract: Antibody-specific language models pretrained via masked language modeling (MLM) learn representations that are critical for downstream sequence design...

By Ayan Goel, Thomas A. Walton, Amirali Aghazadeh

llms safety

arXiv Machine Learning

Jun 4

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

arXiv:2606. 04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes.

By Mansoor Ahmed, Huirong Chai, Haoxin Wang, Hemanth Venkateswara, Murray Patterson

efficiency benchmarks

Hugging Face Trending Papers

Jul 22

Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design

Antibodies are essential proteins that play a central role in immune recognition by binding specific antigen molecules. Although recent protein language models have enabled progress in single-chain protein modeling and generation, they often fall short in antigen-specific antibody design, where effective modeling requires explicit pairing between antibody and antigen, particularly at the epitope level.

llms diffusion reinforcement-learning fine-tuning multimodal benchmarks

arXiv Machine Learning

Jul 23

Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design

arXiv:2607. 20057v1 Announce Type: cross Abstract: Antibodies are essential proteins that play a central role in immune recognition by binding specific antigen molecules.

By Xiaoliang Shi, Zichen Wang, Runze Ma, Zhongyue Zhang, Shuangjia Zheng

llms diffusion reinforcement-learning fine-tuning multimodal benchmarks

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AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking

Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision

Learning Task-Specific Antibody Representations via Function-Aware Masking

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design

Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design