8 papers
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.…
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…
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…
Assessing the Impact of Requirement Ambiguity on LLM-based Function-Level Code Generation
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…