{"total":36,"rows":[{"id":"2310.06839","title":"LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression","created":"2023-10-10","cited_by_count":453,"area":"inference"},{"id":"2501.01005","title":"FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving","created":"2025-01-02","cited_by_count":258,"area":"inference"},{"id":"2410.10781","title":"When Attention Sink Emerges in Language Models: An Empirical View","created":"2024-10-14","cited_by_count":208,"area":"inference"},{"id":"2402.16363","title":"LLM Inference Unveiled: Survey and Roofline Model Insights","created":"2024-02-26","cited_by_count":152,"area":"inference"},{"id":"2403.09054","title":"Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference","created":"2024-03-14","cited_by_count":126,"area":"inference"},{"id":"2401.06104","title":"Transformers are Multi-State RNNs","created":"2024-01-11","cited_by_count":120,"area":"inference"},{"id":"2312.15234","title":"Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems","created":"2023-12-23","cited_by_count":102,"area":"inference"},{"id":"2407.15891","title":"RazorAttention: Efficient KV Cache Compression Through Retrieval Heads","created":"2024-07-22","cited_by_count":100,"area":"inference"},{"id":"2407.21118","title":"Palu: Compressing KV-Cache with Low-Rank Projection","created":"2024-07-30","cited_by_count":64,"area":"inference"},{"id":"2406.07056","title":"Effectively Compress KV Heads for LLM","created":"2024-06-11","cited_by_count":30,"area":"inference"},{"id":"2406.02376","title":"Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs","created":"2024-06-04","cited_by_count":24,"area":"inference"},{"id":"2502.07578","title":"PIM Is All You Need: A CXL-Enabled GPU-Free System for Large Language Model Inference","created":"2025-02-11","cited_by_count":22,"area":"inference"},{"id":"2406.05317","title":"LoCoCo: Dropping In Convolutions for Long Context Compression","created":"2024-06-08","cited_by_count":19,"area":"inference"},{"id":"2512.03324","title":"Cache What Lasts: Token Retention for Memory-Bounded KV Cache in LLMs","created":"2025-12-03","cited_by_count":19,"area":"inference"},{"id":"2502.14317","title":"ParallelComp: Parallel Long-Context Compressor for Length Extrapolation","created":"2025-02-20","cited_by_count":14,"area":"inference"},{"id":"2403.01273","title":"NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention","created":"2024-03-02","cited_by_count":12,"area":"inference"},{"id":"2407.03157","title":"Let the Code LLM Edit Itself When You Edit the Code","created":"2024-07-03","cited_by_count":10,"area":"inference"},{"id":"2409.14364","title":"Position IDs Matter: An Enhanced Position Layout for Efficient Context Compression in Large Language Models","created":"2024-09-22","cited_by_count":9,"area":"inference"},{"id":"2404.15949","title":"CORM: Cache Optimization with Recent Message for Large Language Model Inference","created":"2024-04-24","cited_by_count":7,"area":"inference"},{"id":"2505.00570","title":"FreqKV: Key-Value Compression in Frequency Domain for Context Window Extension","created":"2025-05-01","cited_by_count":7,"area":"inference"},{"id":"2506.07334","title":"Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models","created":"2025-06-09","cited_by_count":6,"area":"inference"},{"id":"2603.17946","title":"CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention","created":"2026-03-18","cited_by_count":5,"area":"inference"},{"id":"2406.07528","title":"QuickLLaMA: Query-aware Inference Acceleration for Large Language Models","created":"2024-06-11","cited_by_count":4,"area":"inference"},{"id":"2405.11299","title":"The CAP Principle for LLM Serving: A Survey of Long-Context Large Language Model Serving","created":"2024-05-18","cited_by_count":3,"area":"inference"},{"id":"2604.10044","title":"LoopGuard: Breaking Self-Reinforcing Attention Loops via Dynamic KV Cache Intervention","created":"2026-04-11","cited_by_count":2,"area":"inference"},{"id":"2605.01858","title":"Decouple and Cache: KV Cache Construction for Streaming Video Understanding","created":"2026-05-03","cited_by_count":2,"area":"inference"},{"id":"2604.00235","title":"MAC-Attention: a Match-Amend-Complete Scheme for Fast and Accurate Attention Computation","created":"2026-03-31","cited_by_count":1,"area":"inference"},{"id":"2511.04686","title":"Stateful KV Cache Management for LLMs: Balancing Space, Time, Accuracy, and Positional Fidelity","created":"2025-10-23","cited_by_count":0,"area":"inference"},{"id":"2603.04759","title":"Stacked from One: Multi-Scale Self-Injection for Context Window Extension","created":"2026-03-05","cited_by_count":0,"area":"inference"},{"id":"2605.12471","title":"KV-Fold: One-Step KV-Cache Recurrence for Long-Context Inference","created":"2026-05-12","cited_by_count":0,"area":"inference"},{"id":"2608.17336","title":"TileMix: Tile-Centric Mixed-Precision Attention for LLM Inference Acceleration","created":"2026-08-18","cited_by_count":0,"area":"inference"},{"id":"2608.21541","title":"Beyond Sparse Weights: When Is Attention Compressible?","created":"2026-08-21","cited_by_count":0,"area":"inference"},{"id":"2608.28911","title":"SemKV: Semantic Mixed-Precision KV Cache Quantization Guided by the Quality Cliff for Long-Context LLM Inference","created":"2026-08-28","cited_by_count":0,"area":"inference"},{"id":"2609.05275","title":"Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference","created":"2026-09-04","cited_by_count":0,"area":"inference"},{"id":"2610.02953","title":"SlimKV: Joint Token-Feature KV Cache Compression with Reconstruction-Free Beacon Attention","created":"2026-10-02","cited_by_count":0,"area":"inference"},{"id":"2610.17966","title":"BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation","created":"2026-10-13","cited_by_count":0,"area":"inference"}],"next_cursor":null}