Author

Subbarao Kambhampati

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#artificial intelligence Preprint Sep 2026

Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces

Chain-of-thought traces are widely read as records of how models reach their answers, informing debugging, agent auditing, and claims about reasoning. Testing this interpretation is difficult because natural-language thinking traces are rarely mechanically verifiable. We revisit it in iGSM, a synthetic grade-school mat...

Ratish Puduppully, Pranabendu Misra, Paarth Iyer et al. · 0 citations

#artificial intelligence Preprint Jan 2023

A Mental Model Based Framework of Trust

A mental model-based framework of trust is proposed that captures multidimensional aspects of trust and can be used to infer human trust and can also be used as a foundation for any trust-aware decision-making framework.

Z. Zahedi, S. Sreedharan, Erin K. Chiou et al. · 8 citations

#artificial intelligence Jun 2026

Masked Distillation: Internalizing the Chain-of-Thought in Language Models

This work introduces \textit{masked distillation}, a knowledge-distillation framework in which a student LLM is trained to predict only the solution tokens conditioned on the question, while a reasoning teacher provides feedback on the student's responses after conditioning on the question and its own CoT trace.

Durgesh Kalwar, Vardhan Palod, Subbarao Kambhampati · arXiv.org · 0 citations