Papers by Anand Chaanan Singh

1 papers
Slim-SC: Thought Pruning for Efficient Scaling with Self-Consistency (2025.emnlp-main)

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Challenge: Recent studies show that Test-Time Scaling (TTS) can improve reasoning performance without retraining the model.
Approach: They propose a step-wise pruning strategy that identifies and removes redundant chains using inter-chain similarity at the thought level.
Outcome: The proposed method reduces inference latency and KVC usage by up to 45% and 26% with R1-Distill while maintaining or improving accuracy.

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