From the 1 of 7 linked papers with an AI index.
9 papers
LabEvolver: Training-Free Experience Evolution for Safe and Grounded Wet-Lab Agents
Jingya Wang, Yuyang Gao, Liuzhenghao Lv +2
LabEvolver is a training‑free framework that gives wet‑lab robotic agents episodic memory and safety checks by combining an adaptive inner trial loop with an outer evolution loop t…
BioProAgent: Neuro-Symbolic Grounding for Constrained Scientific Planning
Yuyang Liu, Jingya Wang, Liuzhenghao Lv +1
Large language models (LLMs) have demonstrated significant reasoning capabilities in scientific discovery but struggle to bridge the gap to physical execution in wet-labs. In these…
MoleCode unlocks structural intelligence in large language models
Zhiyuan Yan, Chen Liu, Boxuan Zhao +8
Molecules are graphs, but large language models~(LLMs) are usually asked to reason about them through linear strings. The most popular molecular representation, SMILES, compresses…
BioProBench: A Corpus and Benchmark for Biological Protocol Reasoning in Autonomous Science
Yuyang Liu, Liuzhenghao Lv, Xiancheng Zhang +2
The realization of autonomous scientific experimentation is currently limited by LLMs' struggle to grasp the strict procedural logic and accuracy required by biological protocols.…
ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing
Liuzhenghao Lv, Zongying Lin, Hao Li +5
Recent advances in Protein Language Models (PLMs) have transformed protein engineering, yet unlike their counterparts in Natural Language Processing (NLP), current PLMs exhibit a f…
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension
Hao Li, Liuzhenghao Lv, He Cao +6
Large language models are increasingly used in scientific domains, especially for molecular understanding and analysis. However, existing models are affected by hallucination issue…