activity
20242026
most citedFrom AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery

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

collaborators

7 papers

cs.AI2026

MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs

Kevin Wang, Anna Thöni, Benjamin Kempinski +50

Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…

cs.LG2026

Proteo-R1: Reasoning Foundation Models for De Novo Protein Design

Fang Wu, Weihao Xuan, Heli Qi +26

Deep learning in de novo protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synthesize molecular geometries…

cs.AI2025

HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?

Fangchen Yu, Haiyuan Wan, Qianjia Cheng +14

Recently, the physical capabilities of (M)LLMs have garnered increasing attention. However, existing benchmarks for physics suffer from two major gaps: they neither provide systema…

cs.LG2025★ 5 cited

From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery

Jiaqi Wei, Yuejin Yang, Xiang Zhang +24

Artificial intelligence (AI) is reshaping scientific discovery, evolving from specialized computational tools into autonomous research partners. We position Agentic Science as a pi…

cs.CL2025

Scaling Physical Reasoning with the PHYSICS Dataset

Shenghe Zheng, Qianjia Cheng, Junchi Yao +9

Large Language Models (LLMs) have achieved remarkable progress on advanced reasoning tasks such as mathematics and coding competitions. Meanwhile, physics, despite being both reaso…

cs.CL2025

UltraIF: Advancing Instruction Following from the Wild

Kaikai An, Li Sheng, Ganqu Cui +4

Instruction-following made modern large language models (LLMs) helpful assistants. However, the key to taming LLMs on complex instructions remains mysterious, for that there are hu…

cs.CL2024★ 1 cited

Sharing Parameter by Conjugation for Knowledge Graph Embeddings in Complex Space

Xincan Feng, Zhi Qu, Yuchang Cheng +2

A Knowledge Graph (KG) is the directed graphical representation of entities and relations in the real world. KG can be applied in diverse Natural Language Processing (NLP) tasks wh…