Papers by Vaibhav Saxena

2 papers
Think Like You Execute: Verifiable Chain of Thought from Program Traces (2026.acl-industry)

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Challenge: Current synthetic Chain-of-Thought (CoT) training data often consists of plausible-sounding explanations generated by teacher models, not verifiable accounts of actual program behavior.
Approach: They propose to ground CoT generation directly in program execution traces to improve reasoning capabilities.
Outcome: The proposed pipeline improves performance on live code benchmarks and on cruxEval-output and cruxeval-input.
Towards Robust Knowledge Representations in Multilingual LLMs for Equivalence and Inheritance based Consistent Reasoning (2025.naacl-long)

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Challenge: Recent advances in Large Language Models have led to impressive linguistic capabilities and emergent reasoning behaviors.
Approach: They propose to use "equivalence" and "inheritance" to evaluate LLMs' representations . they propose to combine "equal" and 'inheritory' to improve consistency across languages .
Outcome: The proposed representations show that they produce conflicting answers across languages . the proposed representation improves performance across languages and improves learning and knowledge sharing.

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