activity
20242026
collaborators

5 papers

cs.AI2026

EvoGraph-Mem: Failure-Aware Editable Graph Memory for Long-Term Language Agents

Yuxi Qian, Yuxiang Ren

Long-term memory is essential for language agents operating across extended interactions and evolving tasks. Existing memory-augmented agents mainly focus on storing and retrieving…

cs.CL2026

Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs

Yurun Chen, Xavier Hu, Yuhan Liu +8

As multimodal LLM-driven agents advance in autonomy and generalization, traditional static datasets face inherent scalability limitations and are insufficient for fully assessing t…

cs.CL2026

I-MCTS: Enhancing Agentic AutoML via Introspective Monte Carlo Tree Search

Zujie Liang, Feng Wei, Wujiang Xu +3

Recent advancements in large language models (LLMs) have shown remarkable potential in automating machine learning tasks. However, existing LLM-based agents often struggle with low…

cs.AI2025

Towards Adaptive ML Benchmarks: Web-Agent-Driven Construction, Domain Expansion, and Metric Optimization

Hangyi Jia, Yuxi Qian, Hanwen Tong +3

Recent advances in large language models (LLMs) have enabled the emergence of general-purpose agents for automating end-to-end machine learning (ML) workflows, including data analy…

cs.CL2024

SEGMENT+: Long Text Processing with Short-Context Language Models

Wei Shi, Shuang Li, Kerun Yu +9

There is a growing interest in expanding the input capacity of language models (LMs) across various domains. However, simply increasing the context window does not guarantee robust…