arXiv AI
Jun 9
End-to-End Context Compression at Scale
arXiv:2606. 09659v1 Announce Type: cross Abstract: Long-context language model inference is bottlenecked by memory, as the KV cache grows with context length.
End-to-End Context Compression at Scale
Long-context language model inference is bottlenecked by memory, as the KV cache grows with context length. Recent techniques to compress the KV cache fall short: they either degrade model quality substantially or require considerable time and compute to compress a single long prompt.
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arXiv AI
Jul 8
DepthWeave-KV: Token-Adaptive Cross-Layer Residual Factorization for Long-Context KV Cache Compression
arXiv:2607. 06523v1 Announce Type: new Abstract: Long-context language model inference is increasingly limited by the memory bandwidth and capacity required to store key-value caches, yet existing compression methods often apply uniform budgets across layers or tokens and degrade retrieval when lexical cues and semantic states require different preservation.
arXiv AI
Jun 24
CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference
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arXiv AI
Jul 31
ARC-Encoder: learning compressed text representations for large language models
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Hugging Face Trending Papers
Jun 23
CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference
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arXiv AI
Jul 8
FreqDepthKV: Frequency-Guided Depth Sharing for Robust KV Cache Compression in Long-Context LLM Inference
arXiv:2607. 06519v1 Announce Type: new Abstract: Long-context LLM inference is increasingly limited by the memory and bandwidth cost of KV caches, yet aggressive compression can remove the layer-specific evidence needed for retrieval and multi-step reasoning.
arXiv Machine Learning
Jul 3
Lynx: Progressive Speculative Quantization for accelerating KV Transfer in Long-Context Inference
arXiv:2607. 01831v1 Announce Type: cross Abstract: Long-context inference is increasingly common in large language model (LLM) serving, driven by retrieval-augmented generation and agentic systems.
arXiv Machine Learning
Jun 9
Still: Amortized KV Cache Compaction in a Single Forward Pass
arXiv:2606. 07878v1 Announce Type: new Abstract: The KV cache is the memory bottleneck of long-horizon language model deployment.
arXiv AI
Jul 3
Kara: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression
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arXiv Machine Learning
Jul 14
Controllably Efficient Language Models
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arXiv AI
Aug 11
VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference
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arXiv AI
Jun 2
ACON: Optimizing Context Compression for Long-horizon LLM Agents
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