most citedProtein Large Language Models: A Comprehensive Survey

2 citations · 3 across the 9 of their papers we have counts for

collaborators

11 papers

cs.AI2026

LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents

Lei Liu, Yikun Zhang, Jialin Chen +7

Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to explore more novel and in-d…

cs.AI2026

Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation

Lin Shi, Haowei Lin, Zixuan Zhu +123

Evaluating agents on the growing number of agentic benchmarks is challenging because they often require complex environments and agent integrations. We introduce Harbor Adapters, a…

cs.AI2026

Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents

Batu El, Jinhee Paeng, Fatih Dinc +7

AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their interactions can improve co…

cs.AI2026

OpenThoughts-Agent: Data Recipes for Agentic Models

Negin Raoof, Richard Zhuang, Marianna Nezhurina +47

Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents. Existing open efforts…

cs.CL2026

CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning

Dachuan Shi, Hanlin Zhu, Xiangchi Yuan +4

Chain-of-thought (CoT) is a standard approach for eliciting reasoning capabilities from large language models (LLMs). However, the common CoT paradigm treats thinking as a prerequi…

cs.AI2026

ZEBRAARENA: A Diagnostic Simulation Environment for Studying Reasoning-Action Coupling in Tool-Augmented LLMs

Wanjia Zhao, Ludwig Schmidt, Yejin Choi +3

Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound this interplay with complex envir…

cs.LG2025

PRISM-Physics: Causal DAG-Based Process Evaluation for Physics Reasoning

Wanjia Zhao, Qinwei Ma, Jingzhe Shi +7

Benchmarks for competition-style reasoning have advanced evaluation in mathematics and programming, yet physics remains comparatively explored. Most existing physics benchmarks eva…

cs.LG2025

GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters

Wanjia Zhao, Jiaqi Han, Siyi Gu +3

Geometric diffusion models have shown remarkable success in molecular dynamics and structure generation. However, efficiently fine-tuning them for downstream tasks with varying geo…

cs.LG2025★ 1 cited

OpenThoughts: Data Recipes for Reasoning Models

Etash Guha, Ryan Marten, Sedrick Keh +47

Reasoning models have made rapid progress on many benchmarks involving math, code, and science. Yet, there are still many open questions about the best training recipes for reasoni…

q-bio.BM2025★ 2 cited

Protein Large Language Models: A Comprehensive Survey

Yijia Xiao, Wanjia Zhao, Junkai Zhang +12

Protein-specific large language models (Protein LLMs) are revolutionizing protein science by enabling more efficient protein structure prediction, function annotation, and design.…

cs.AI2025

SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning

Wanjia Zhao, Mert Yuksekgonul, Shirley Wu +1

Multi-agent AI systems powered by large language models (LLMs) are increasingly applied to solve complex tasks. However, these systems often rely on fragile, manually designed prom…