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