{"total":38,"rows":[{"id":"2502.11089","title":"Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention","created":"2025-02-16","cited_by_count":407,"area":null},{"id":"2502.02770","title":"Twilight: Adaptive Attention Sparsity with Hierarchical Top-$p$ Pruning","created":"2025-02-04","cited_by_count":49,"area":null},{"id":"2504.17768","title":"The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs","created":"2025-04-24","cited_by_count":29,"area":null},{"id":"2412.14468","title":"HashAttention: Semantic Sparsity for Faster Inference","created":"2024-12-19","cited_by_count":24,"area":null},{"id":"2507.19595","title":"Efficient Attention Mechanisms for Large Language Models: A Survey","created":"2025-07-25","cited_by_count":22,"area":null},{"id":"2502.08246","title":"Inference-time sparse attention with asymmetric indexing","created":"2025-02-12","cited_by_count":11,"area":null},{"id":"2508.02215","title":"LeanK: Learnable K Cache Channel Pruning for Efficient Decoding","created":"2025-08-04","cited_by_count":7,"area":null},{"id":"2605.07363","title":"MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference","created":"2026-05-08","cited_by_count":7,"area":null},{"id":"2505.17810","title":"VIBE: Vector Index Benchmark for Embeddings","created":"2025-05-23","cited_by_count":6,"area":null},{"id":"2508.02124","title":"Trainable Dynamic Mask Sparse Attention","created":"2025-08-04","cited_by_count":6,"area":null},{"id":"2510.05688","title":"vAttention: Verified Sparse Attention","created":"2025-10-07","cited_by_count":6,"area":null},{"id":"2502.06766","title":"Exploiting Sparsity for Long Context Inference: Million Token Contexts on Commodity GPUs","created":"2025-02-10","cited_by_count":5,"area":null},{"id":"2502.09647","title":"Unveiling Simplicities of Attention: Adaptive Long-Context Head Identification","created":"2025-02-11","cited_by_count":5,"area":null},{"id":"2507.03285","title":"Memory Mosaics at scale","created":"2025-07-04","cited_by_count":5,"area":null},{"id":"2606.04511","title":"SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference","created":"2026-06-03","cited_by_count":5,"area":null},{"id":"2512.17452","title":"KV Admission: Learning What to Write for Efficient Long-Context LLM Inference","created":"2025-12-19","cited_by_count":4,"area":null},{"id":"2502.12085","title":"APB: Accelerating Distributed Long-Context Inference by Passing Compressed Context Blocks across GPUs","created":"2025-02-17","cited_by_count":3,"area":null},{"id":"2505.24179","title":"SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling","created":"2025-05-30","cited_by_count":3,"area":null},{"id":"2602.06283","title":"SOCKET: SOft Collision Kernel EsTimator for Sparse Attention","created":"2026-02-06","cited_by_count":3,"area":null},{"id":"2607.21475","title":"Error Certificates for KV-Cache Eviction via Randomized Design","created":"2026-07-23","cited_by_count":2,"area":null},{"id":"2502.16931","title":"Machine learning and high dimensional vector search","created":"2025-02-24","cited_by_count":1,"area":null},{"id":"2506.15704","title":"Learn from the Past: Fast Sparse Indexing for Large Language Model Decoding","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2510.18830","title":"MTraining: Distributed Dynamic Sparse Attention for Efficient Ultra-Long Context Training","created":"2025-10-21","cited_by_count":1,"area":null},{"id":"2511.00819","title":"Optimizing Native Sparse Attention with Latent Attention and Local Global Alternating Strategies","created":"2025-11-02","cited_by_count":1,"area":null},{"id":"2604.03260","title":"Why Attend to Everything? Focus is the Key","created":"2026-03-12","cited_by_count":1,"area":null},{"id":"2604.05438","title":"Residual-Mass Accounting for Partial-KV Decoding","created":"2026-04-07","cited_by_count":1,"area":null},{"id":"2605.09472","title":"Positional LSH: Binary Block Matrix Approximation for Attention with Linear Biases","created":"2026-05-10","cited_by_count":1,"area":null},{"id":"2605.24930","title":"H$^{2}$MT: Semantic Hierarchy-Aware Hierarchical Memory Transformer","created":"2026-05-24","cited_by_count":1,"area":null},{"id":"2607.24555","title":"LOCKS: Page-Local Compact Key Summaries for Efficient Long-Context Decoding","created":"2026-07-27","cited_by_count":1,"area":null},{"id":"2504.17449","title":"HMI: Hierarchical Knowledge Management for Efficient Multi-Tenant Inference in Pretrained Language Models","created":"2025-04-24","cited_by_count":0,"area":null},{"id":"2605.24168","title":"Inference Time Context Sparsity: Illusion or Opportunity?","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2608.04405","title":"Training-Free Hashing-Based Attention via Binary Principal Components","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.01925","title":"CRISP: Cliff-awaRe Input-adaptive Sparse Prefilling with Structural-Mass-Motivated Routing","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.33746","title":"PQ-HSA: Reusing Product-Quantized Scores for Hybrid Sparse-Approximate Attention","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2609.34063","title":"Counterexamples to Local Reconstruction Gain as a Proxy for Final Fidelity in Residual Completion","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.35629","title":"SANTA++: Sampling Attention through Representative Keys","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.37261","title":"Efficiently Approximating Attention Is Hard","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.01230","title":"HHR: Hierarchical Hash Retrieval for Efficient LLM Generation","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}