5 papers
From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization
Ying Chang, Jiahang Xu, Xuan Feng +3
The optimization of long-horizon agents increasingly relies on reflection-based mechanisms, where a large language model (LLM) acts as an optimizer to diagnose agent failures and i…
Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity
Geoffrey Martin, Xuan Zhong Feng, Yifan Peng
Suicide is a leading cause of death in the United States, and understanding the circumstances that precede it requires extracting structured information from death investigation na…
Beyond Prompt Content: Enhancing LLM Performance via Content-Format Integrated Prompt Optimization
Yuanye Liu, Jiahang Xu, Li Lyna Zhang +6
Large Language Models (LLMs) have shown significant capability across various tasks, with their real-world effectiveness often driven by prompt design. While recent research has fo…
Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models
Zhenghao Lin, Zihao Tang, Xiao Liu +31
We introduce Sigma, an efficient large language model specialized for the system domain, empowered by a novel architecture including DiffQKV attention, and pre-trained on our metic…
ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain
Haochen Zhao, Xiangru Tang, Ziran Yang +8
The advancement and extensive application of large language models (LLMs) have been remarkable, including their use in scientific research assistance. However, these models often g…