1 citations · 2 across the 8 of their papers we have counts for
12 papers
WorkRover: Scaling Long-Horizon Cowork Agent Training Via Recursive Environment Evolution
Hang He, Linting Wang, Guanming Liu +14
Scaling interactive environments is important for training long-horizon agents through reinforcement learning. These environments often require further testing and refinement after…
CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?
Hang He, Li Wang, Hao Chen +9
Static-analysis checker synthesis requires agents to interpret a defect specification, inspect a repository, implement analyzer-specific logic, and refine the checker through repea…
WEFT: Scaling Tool-Use Post-Training for General-Purpose Agents
Bo Mao, Hang He, Linting Wang +17
Recent efforts to scale tool-use post-training have largely centered on the synthesis of executable environments, which constitute only one component of a broader agentic interacti…
VistaHop: Benchmarking Long-Horizon Visual DeepSearch
Hang He, Chuhuai Yue, Chengqi Dong +6
Visual DeepSearch tasks require multimodal large language models (MLLMs) to resolve complex visual queries by repeatedly inspecting image regions, grounding reasoning in visual evi…
Clarity Is Not Assumed: Understanding LLM-Based Code Generation under Ambiguous Requirements
Di Yang, Xinou Xie, Xiuwen Yang +7
Software requirement ambiguity is ubiquitous in real-world development, stemming from the inherent imprecision of natural language and the varying interpretations of stakeholders.…
Improving Random Testing via LLM-powered UI Tarpit Escaping for Mobile Apps
Mengqian Xu, Yiheng Xiong, Le Chang +3
Random GUI testing is a widely-used technique for testing mobile apps. However, its effectiveness is limited by the notorious issue -- UI exploration tarpits, where the exploration…
FLARE: Agentic Coverage-Guided Fuzzing for LLM-Based Multi-Agent Systems
Mingxuan Hui, Xinyue Li, Lu Wang +7
Multi-Agent LLM Systems (MAS) have been adopted to automate complex human workflows by breaking down tasks into subtasks. However, due to the non-deterministic behavior of LLM agen…
LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services
Hang He, Chuhuai Yue, Chengqi Dong +12
Recent advances in large reasoning models LRMs have enabled agentic search systems to perform complex multi-step reasoning across multiple sources. However, most studies focus on g…
Automated detection of atomicity violations in large-scale systems
Hang He, Yixing Luo, Chengcheng Wan +3
Atomicity violations in interrupt-driven programs pose a significant threat to software reliability in safety-critical systems. These violations occur when the execution sequence o…
Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errors
Jiawei Shen, Chengcheng Wan, Ruoyi Qiao +6
Large language models (LLMs) have been adopted for text-to-SQL tasks, utilizing their in-context learning (ICL) capability to translate natural language questions into SQL queries.…
BinPRE: Enhancing Field Inference in Binary Analysis Based Protocol Reverse Engineering
Jiayi Jiang, Xiyuan Zhang, Chengcheng Wan +3
Protocol reverse engineering (PRE) aims to infer the specification of network protocols when the source code is not available. Specifically, field inference is one crucial step in…
Are LLMs Correctly Integrated into Software Systems?
Yuchen Shao, Yuheng Huang, Jiawei Shen +3
Large language models (LLMs) provide effective solutions in various application scenarios, with the support of retrieval-augmented generation (RAG). However, developers face challe…