3 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
HELIX: Model-Harness Co-evolution for Recursive Self-Improvement
Tianyu Fan, Chao Huang
Scaling agent capability has largely focused on improving the model, yet an interactive agent acts through a runtime harness that mediates context, tools, control flow, and stoppin…
Why Your Deep Research Agent Fails? On Hallucination Evaluation in Full Research Trajectory
Yuhao Zhan, Tianyu Fan, Linxuan Huang +2
Diagnosing failure patterns in Deep Research Agents (DRAs) remains a critical challenge. Existing benchmarks predominantly rely on end-to-end evaluation, obscuring intermediate hal…
Needle in the Web: A Benchmark for Retrieving Targeted Web Pages in the Wild
Yumeng Wang, Tianyu Fan, Lingrui Xu +1
Large Language Models (LLMs) have evolved from simple chatbots into sophisticated agents capable of automating complex real-world tasks, where browsing and reasoning over live web…
Understanding DeepResearch via Reports
Tianyu Fan, Xinyao Niu, Yuxiang Zheng +5
DeepResearch agents represent a transformative AI paradigm, conducting expert-level research through sophisticated reasoning and multi-tool integration. However, evaluating these s…
AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents
Jiabin Tang, Tianyu Fan, Chao Huang
Large Language Model (LLM) Agents have demonstrated remarkable capabilities in task automation and intelligent decision-making, driving the widespread adoption of agent development…
MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation
Tianyu Fan, Jingyuan Wang, Xubin Ren +1
The growing demand for efficient and lightweight Retrieval-Augmented Generation (RAG) systems has highlighted significant challenges when deploying Small Language Models (SLMs) in…