collaborators

5 papers

cs.AI2026

GUITester: Enabling GUI Agents for Exploratory Defect Discovery

Yifei Gao, Jiang Wu, Xiaoyi Chen +5

Exploratory GUI testing is essential for software quality but suffers from high manual costs. While Multi-modal Large Language Model (MLLM) agents excel in navigation, they fail to…

cs.LG2025

PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling

Yuxuan Yue, Zukang Xu, Zhihang Yuan +3

Large Language Models (LLMs) face significant challenges in edge deployment due to their massive parameter scale. Vector Quantization (VQ), a clustering-based quantization method,…

cs.CR2025

CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges

Yu Li, Qizhi Pei, Mengyuan Sun +6

Large language models (LLMs) have demonstrated remarkable capabilities, especially the recent advancements in reasoning, such as o1 and o3, pushing the boundaries of AI. Despite th…

cs.CL2025

A Strategic Coordination Framework of Small LLMs Matches Large LLMs in Data Synthesis

Xin Gao, Qizhi Pei, Zinan Tang +5

While data synthesis and distillation are promising strategies to enhance small language models, current approaches heavily rely on Large Language Models (LLMs), which suffer from…

cs.LG2025

RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack

Weichen Dai, Zijie Dai, Zhijie Huang +6

While current large language models (LLMs) demonstrate remarkable linguistic capabilities through training on massive unstructured text corpora, they remain inadequate in leveragin…