Adaptive Mass-Segmented KV Compression for Long-Context Reasoning
cs.LG, cs.AI
Submitted: 2026-05-22
Updated: 2026-09-29
Comments: Accepted at NeurIPS 2026
Code: https://github.com/EIT-NLP/AdaptiveMassSegment
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Efficient Memory Management for Large Language Model Serving with PagedAttention
- KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- R-KV: Redundancy-aware KV Cache Compression for Reasoning Models
- TriAttention: Efficient Long Reasoning with Trigonometric KV Compression
- FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
- Efficient Streaming Language Models with Attention Sinks
- PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling
- Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference
- Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning
- SnapKV: LLM Knows What You are Looking for Before Generation
- SABlock: Semantic-Aware KV Cache Eviction with Adaptive Compression Block Size
- ClusterKV: Manipulating LLM KV Cache in Semantic Space for Recallable Compression
- TreeKV: Smooth Key-Value Cache Compression with Tree Structures
- HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference
- Expected Attention: KV Cache Compression by Estimating Attention from Future Queries Distribution
- ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference
- KeyDiff: Key Similarity-Based KV Cache Eviction for Long-Context LLM Inference in Resource-Constrained Environments
- SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation
- G-KV: Decoding-Time KV Cache Eviction with Global Attention
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