7 papers
Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence
Mengru Wang, Junfeng Fang, Shuofei Qiao +16
AI models have achieved remarkable success across diverse domains, yet the mechanisms underlying their capabilities and the risks they may pose remain poorly understood. As AI deve…
Interactive Learning for LLM Reasoning
Hehai Lin, Shilei Cao, Sudong Wang +5
Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby c…
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
Zi-Han Wang, Lam Nguyen, Zhengyang Zhao +4
The saturation of high-quality pre-training data has shifted research focus toward evolutionary systems capable of continuously generating novel artifacts, leading to the success o…
Notes2Skills: From Lab Notebooks to Certainty-Aware Scientific Agent Skills
Shi Liu, Jiayao Chen, Chengwei Qin +3
Scientific discovery workflows usually contain and rely heavily on lab notes, where researchers record observations, interpret uncertain results, and plan follow-up experiments. Su…
StatefulDiscovery: Evidence-Calibrated Claim Formation in Open-Ended Scientific Discovery
Jiayao Chen, Shi Liu, Linyi Yang
Open-ended scientific discovery asks agents to move beyond executing analyses for predefined questions. Across multiple rounds of exploration, a discovery agent must decide which p…
ReviewGuard: Aligning LLM-Assisted Peer Review with Long-Term Scientific Impact
Abdur Rasool, Xiaohui Huang, Yanqing Hu +1
Peer review is central to scientific quality control, yet it can undervalue papers that later achieve substantial citation impact. While frontier large language models have shown p…