1 citations · 2 across the 16 of their papers we have counts for
6 papers · 1 filter
SAGE: A Unified Algebra and Self-Adaptive Execution for AI Functions in SQL
Xiangqi Wang, Nhan H. Pham, Oktie Hassanzadeh +2
SQL systems increasingly expose AI functions for tasks such as classification, extraction, filtering, ranking, retrieval, joining, and summarization. Despite their diverse APIs, th…
TellOnce: Correcting Coding Agents Once, Improving Their Future Actions
Yujun Zhou, Kehan Guo, Haomin Zhuang +8
Interactive LLM agents increasingly work with users across tasks, yet remembering a previous correction does not ensure that the agent changes its behavior in the future. In a diag…
PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models
Han Bao, Penghao Zhang, Yue Huang +9
Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability to comprehend and reason abou…
SenseMath: Do LLMs Have Number Sense? Evaluating Shortcut Use, Judgment, and Generation
Haomin Zhuang, Xiangqi Wang, Yili Shen +2
Large language models often default to step-by-step computation even when efficient numerical shortcuts are available. This raises a basic question: do they exhibit number sense in…
Dual Optimal: Make Your LLM Peer-like with Dignity
Xiangqi Wang, Yue Huang, Haomin Zhuang +2
Current aligned language models exhibit a dual failure mode we term the Evasive Servant: they sycophantically validate flawed user beliefs while deflecting responsibility with boil…
ProbeLLM: Automating Principled Diagnosis of LLM Failures
Yue Huang, Zhengzhe Jiang, Yuchen Ma +8
Understanding how and why large language models (LLMs) fail is becoming a central challenge as models rapidly evolve and static evaluations fall behind. While automated probing has…