3 papers
cs.CL2026
Evaluating and Improving LLM Self-Modeling
Siqi Zeng, Andre N. Assis, Rowan Wang
We study self-modeling: an LLM's ability to answer questions about its own behavior. We focus on verifiable behavioral questions, such as whether a prompt edit would change the mod…
cs.SE2026
ClayBuddy: A Framework, Evaluation, & Mitigation of Coding Agent Failures
Kenneth Ge, Andre Assis
Widespread deployment of AI agents in software engineering is surfacing a long tail of rare but highly dangerous misalignment bugs. Since sampling this behavior is intractable, we…
cs.CL2025
Detecting and Characterizing Planning in Language Models
Jatin Nainani, Sankaran Vaidyanathan, Connor Watts +2
Modern large language models (LLMs) have demonstrated impressive performance across a wide range of multi-step reasoning tasks. Recent work suggests that LLMs may perform planning…