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AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent
Haipeng Luo, Huawen Feng, Qingfeng Sun +6
Large Reasoning Models (LRMs) like o3 and DeepSeek-R1 have achieved remarkable progress in reasoning tasks with long cot. However, they remain computationally inefficient and strug…
MONICA: Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models
Jingyu Hu, Shu Yang, Xilin Gong +3
Large Reasoning Models (LRMs) suffer from sycophantic behavior, where models tend to agree with users' incorrect beliefs and follow misinformation rather than maintain independent…
Investigating CoT Monitorability in Large Reasoning Models
Shu Yang, Junchao Wu, Xilin Gong +4
Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex tasks by engaging in extended reasoning before producing final answers. Beyond improving abilities…
PathFuzzing: Worst Case Analysis by Fuzzing Symbolic-Execution Paths
Zimu Chen, Di Wang
Estimating worst-case resource consumption is a critical task in software development. The worst-case analysis (WCA) problem is an optimization-based abstraction of this task. Fuzz…
A Program Logic for Under-approximating Worst-case Resource Usage
Ziyue Jin, Di Wang
Understanding and predicting the worst-case resource usage is crucial for software quality; however, existing methods either over-approximate with potentially loose bounds or under…