When2Think: Learning Difficulty-Aware Length Control for Efficient Hybrid Reasoning Models
When2Think post-training framework allocates reasoning depth by problem difficulty, raising AIME24 Pass@3 10.0% while cutting token usage 27.9%.
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Stories tagged #large-reasoning-models
BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference
BeaconKV introduces training-free KV cache compression using beacon queries, cutting long-reasoning inference memory up to 5.8x while preserving accuracy.