3 papers
cs.CL2026
PA3: Policy-Aware Agent Alignment through Chain-of-Thought
Shubhashis Roy Dipta, Daniel Bis, Kun Zhou +4
Conversational assistants powered by large language models (LLMs) excel at tool-use tasks but struggle with adhering to complex, business-specific rules. While models can reason ov…
cs.LG2026
Know When You're Wrong: Aligning Confidence with Correctness for LLM Error Detection
Xie Xiaohu, Liu Xiaohu, Yao Benjamin
As large language models (LLMs) are increasingly deployed in critical decision-making systems, the lack of reliable methods to measure their uncertainty presents a fundamental trus…
cs.CL2026
Beyond Perfect APIs: A Comprehensive Evaluation of LLM Agents Under Real-World API Complexity
Doyoung Kim, Zhiwei Ren, Jie Hao +11
We introduce WildAGTEval, a benchmark designed to evaluate large language model (LLM) agents' function-calling capabilities under realistic API complexity. Unlike prior work that a…