3 citations · 9 across the 16 of their papers we have counts for
5 papers · 1 filter
TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use
Pengfei He, Zhenwei Dai, Bing He +10
Large language model (LLM)-based agents increasingly rely on tool use to complete real-world tasks. While existing works evaluate the LLMs' tool use capability, they largely focus…
Adaptive Test-Time Reasoning via Reward-Guided Dual-Phase Search
Yingqian Cui, Zhenwei Dai, Pengfei He +8
Large Language Models (LLMs) have achieved significant advances in reasoning tasks. A key approach is tree-based search with verifiers, which expand candidate reasoning paths and u…
How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior
Zidi Xiong, Yuping Lin, Wenya Xie +5
Memory is a critical component in large language model (LLM)-based agents, enabling them to store and retrieve past executions to improve task performance over time. In this paper,…
Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data
Juanhui Li, Sreyashi Nag, Hui Liu +7
In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computatio…
A LLM-Powered Automatic Grading Framework with Human-Level Guidelines Optimization
Yucheng Chu, Hang Li, Kaiqi Yang +4
Open-ended short-answer questions (SAGs) have been widely recognized as a powerful tool for providing deeper insights into learners' responses in the context of learning analytics…