6 citations · 21 across the 38 of their papers we have counts for
9 papers · 1 filter
DPIAgent: Divide, Protocol, Isolate for Agentic Reproduction Test Generation
Hao Liu, Steven Liu, Xin Zhang +8
Reproduction test generation, producing a failing-then-passing test that captures a reported bug, is a critical step in automated software engineering. Existing agentic methods tre…
Beyond Fail-to-Pass: Iterative Hardening of Co-Generated Bug Reproduction Tests and Fixes
Yuhao Tan, Zhibang Yang, Fangkai Yang +9
Large language models (LLMs) have made automated program repair (APR) increasingly practical for real-world bugs, but repairing directly from bug reports remains underconstrained.…
ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory
Yue Fang, Zhibang Yang, Fangkai Yang +5
Large language model (LLM) agents increasingly rely on external tools served by shared providers and accessed by heterogeneous downstream agents. Existing approaches improve tool u…
DUET: Joint Exploration of User Item Profiles in Recommendation System
Yue Chen, Yifei Sun, Lu Wang +17
Traditional recommendation systems represent users and items as dense vectors and learn to align them in a shared latent space for relevance estimation. Recent LLM-based recommende…
Beyond State Consistency: Behavior Consistency in Text-Based World Models
Youling Huang, Guanqiao Chen, Junchi Yao +8
World models have been emerging as critical components for assessing the consequences of actions generated by interactive agents in online planning and offline evaluation. In text-…
Computer-Using World Model
Yiming Guan, Rui Yu, John Zhang +15
Agents operating in complex software environments benefit from reasoning about the consequences of their actions, as even a single incorrect user interface (UI) operation can derai…
A Tale of Two Graphs: Separating Knowledge Exploration from Outline Structure for Open-Ended Deep Research
Zhuofan Shi, Ming Ma, Zekun Yao +7
Open-Ended Deep Research (OEDR) pushes LLM agents beyond short-form QA toward long-horizon workflows that iteratively search, connect, and synthesize evidence into structured repor…
DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
Ming Ma, Jue Zhang, Fangkai Yang +4
Large language model (LLM)-based multi-agent systems are challenging to debug because failures often arise from long, branching interaction traces. The prevailing practice is to le…
RepoGenesis: Benchmarking End-to-End Microservice Generation from Readme to Repository
Zhiyuan Peng, Xin Yin, Pu Zhao +7
Large language models and agents have achieved remarkable progress in code generation. However, existing benchmarks focus on isolated function/class-level generation (e.g., ClassEv…