3 citations · 6 across the 24 of their papers we have counts for
9 papers · 1 filter
Owl-AuraID 1.0: An Intelligent System for Autonomous Scientific Instrumentation and Scientific Data Analysis
Han Deng, Anqi Zou, Hanling Zhang +14
Scientific discovery increasingly depends on high-throughput characterization, yet automation is hindered by proprietary GUIs and the limited generalizability of existing API-based…
ARCHE: A Novel Task to Evaluate LLMs on Latent Reasoning Chain Extraction
Pengze Li, Jiaqi Liu, Junchi Yu +5
Large language models (LLMs) are increasingly used in scientific domains. While they can produce reasoning-like content via methods such as chain-of-thought prompting, these output…
MicroRCA-Agent: Microservice Root Cause Analysis Method Based on Large Language Model Agents
Pan Tang, Shixiang Tang, Huanqi Pu +2
This paper presents MicroRCA-Agent, an innovative solution for microservice root cause analysis based on large language model agents, which constructs an intelligent fault root cau…
Mimicking the Physicist's Eye:A VLM-centric Approach for Physics Formula Discovery
Jiaqi Liu, Songning Lai, Pengze Li +12
Automated discovery of physical laws from observational data in the real world is a grand challenge in AI. Current methods, relying on symbolic regression or LLMs, are limited to u…
Dynamic Knowledge Exchange and Dual-diversity Review: Concisely Unleashing the Potential of a Multi-Agent Research Team
Weilun Yu, Shixiang Tang, Yonggui Huang +7
Scientific progress increasingly relies on effective collaboration among researchers, a dynamic that large language models (LLMs) have only begun to emulate. While recent LLM-based…
Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI
Sha Zhang, Suorong Yang, Tong Xie +18
Scientific discovery has long been constrained by human limitations in expertise, physical capability, and sleep cycles. The recent rise of AI scientists and automated laboratories…