most citedInstructPro: Natural Language Guided Ligand-Binding Protein Design

1 citations · 1 across the 6 of their papers we have counts for

collaborators

9 papers

cs.LG2026

InstructPro2: Natural Language and Biological Grounding Guided De Novo Protein Design

Charles Novak, Zhenqiao Song, Chuan Li +2

The ability to generate proteins with desired functions is a central goal of computational biology. Although natural language can express diverse design objectives, existing protei…

cs.AI2026

Joint Discrete and SE(3) Diffusion for Protein Interface Design

Zhenqiao Song, Jianwen Xie, Lei Li

The design of high-affinity, target-specific protein binders is central to the development of modern therapeutics. However, existing protein-generation methods remain limited in th…

cs.LG2026

TurboPairFormer: Fast and Stable Protein Folding Model Training with an Optimized Triangle Attention Kernel

Yide Ran, Chelsea Lowman, Jan Domański +6

Triangular attention is a core computation in AlphaFold3-style biomolecular models, with cubic cost in token count. Its shared pair bias adds a gradient reduction across attention…

cs.LG2026

Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning

Ziwen Liu, Huawei Lin, Yide Ran +5

Large language models (LLMs) sometimes memorize undesirable knowledge, which must be removed after deployment. Prior work on machine unlearning has focused largely on optimization…

cs.CL2026

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

Zhuofeng Li, Yi Lu, Dongfu Jiang +7

The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-based reviewers often generate s…

cs.LG2026

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation

Yide Ran, Jianwen Xie, Minghui Wang +4

Data attribution and valuation are critical for understanding data-model synergy for Large Language Models (LLMs), yet existing gradient-based methods suffer from scalability chall…

cs.CV2026

PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction

Xiang Zhang, Sohyun Yoo, Hongrui Wu +3

We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed…

cs.LG2025

To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration

Zeyu Yang, Tianyi Zhang, Jianwen Xie +3

The scaling of Generative AI (GenAI) models into the hundreds of billions of parameters makes low-precision computation indispensable for efficient deployment. We argue that the fu…

cs.LG2025★ 1 cited

InstructPro: Natural Language Guided Ligand-Binding Protein Design

Zhenqiao Song, Ramith Hettiarachchi, Chuan Li +2

The de novo design of ligand-binding proteins with tailored functions is essential for advancing biotechnology and molecular medicine, yet existing AI approaches are limited by sca…