TrimR uses a lightweight verifier to detect redundant thoughts in reasoning models and truncates them, cutting runtime by up to 70% without retraining.
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TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling
TrimR uses a lightweight verifier to detect redundant thoughts in reasoning models and truncates them, cutting runtime by up to 70% without retraining.