Author

Aishwarya H. Balwani

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Jul 2026

Probing the Origins of Reasoning Performance: Representational Quality for Mathematical Problem-Solving in RL vs. SFT Fine-Tuned Models

This work presents two converging lines of evidence that linear probes trained on layer-wise hidden states reveal that RL models tend to achieve higher accuracy in predicting answer correctness compared to SFT models, indicating more linearly separable and structured representations.

Antyabha Rahman, Akshaj Gurugubelli, Omar Ankit et al. · arXiv.org · 0 citations

Preprint Aug 2026

The Tell-Tale Trace: Detecting Reasoning Failures in LLMs Using Chain-of-Thought Dynamics

Results show that capability failures can manifest as distributed, task-dependent changes in the structure of visible reasoning, and that CoT dynamics agnostic to whether the verbalized trace reflects the model's internal computations can help diagnose and correct failures.

Shashwat Sourav, Aishwarya H. Balwani · 1 citation