AMS KV compression adaptively partitions the cache by attention mass regions and assigns quotas to protect contiguous reasoning blocks during long-context LLM inference.
Transformers are multi-state RNNs
2 Pith papers cite this work. Polarity classification is still indexing.
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Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
citing papers explorer
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Adaptive Mass-Segmented KV Compression for Long-Context Reasoning
AMS KV compression adaptively partitions the cache by attention mass regions and assigns quotas to protect contiguous reasoning blocks during long-context LLM inference.
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Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.