MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention | Paper Citation Record

Observation 9b2ac96e-76a3-4183-bfa8-0a575b874f14 · inbound

PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling cites this paper.

PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 15

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RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval cites this paper.

RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 92

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DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads cites this paper.

DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 24

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Observation 726bed92-0016-47fd-bf64-5646b9ccce34 · inbound

Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity cites this paper.

Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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Observation 117ea9d5-a022-4e3d-b118-60286fc7f7ba · inbound

Boosting Long-Context Management via Query-Guided Activation Refilling cites this paper.

Boosting Long-Context Management via Query-Guided Activation Refilling MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 11

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A Silver Bullet or a Compromise for Full Attention? A Comprehensive Study of Gist Token-based Context Compression cites this paper.

A Silver Bullet or a Compromise for Full Attention? A Comprehensive Study of Gist Token-based Context Compression MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 18

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Observation 9cf4cfec-b40e-49b2-aef5-aeff1eecc7fd · inbound

Bootstrap Your Own Context Length cites this paper.

Bootstrap Your Own Context Length MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 18

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Observation c70bb0c2-05b7-47f3-a30e-f3e8c6faca67 · inbound

FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models cites this paper.

FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Vision Language Models MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 14

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Observation 1fbe6fb6-d8c0-41bd-b5d2-ce0472f62f3e · inbound

AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference cites this paper.

AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 15

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Scaling Inference-Efficient Language Models cites this paper.

Scaling Inference-Efficient Language Models MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 21

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Observation c4f212c6-33a8-4b7f-830c-206048453844 · inbound

FastKV: Decoupling of Context Reduction and KV Cache Compression for Prefill-Decoding Acceleration cites this paper.

FastKV: Decoupling of Context Reduction and KV Cache Compression for Prefill-Decoding Acceleration MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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Observation cd041ad0-0ee2-45fc-9301-b0f8a83ec79d · inbound

Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity cites this paper.

Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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A Training-Free Length Extrapolation Approach for LLMs: Greedy Attention Logit Interpolation (GALI) cites this paper.

A Training-Free Length Extrapolation Approach for LLMs: Greedy Attention Logit Interpolation (GALI) MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 13

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Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation cites this paper.

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 22

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Observation 33ca09d6-542e-4079-a12d-02af750dd0e8 · inbound

CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective cites this paper.

CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 22

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Observation 869c4170-945e-4fed-824b-5686e7ea904b · inbound

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding cites this paper.

APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 20

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Observation d83b80b3-601d-441d-b7cf-6f2b72df8a91 · inbound

LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs cites this paper.

LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 19

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Observation 6ed5391c-3d37-4a5c-be11-bce0d9996892 · inbound

InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU cites this paper.

InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 13

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Observation 681f0673-0b72-43a4-abd7-1ab0cb30250d · inbound

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention cites this paper.

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 83

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T23:46:30.161102Z

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Observation 7277d24d-9352-4285-820c-0cb3f6496af7 · inbound

MoBA: Mixture of Block Attention for Long-Context LLMs cites this paper.

MoBA: Mixture of Block Attention for Long-Context LLMs MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 23

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Observation 9b1d3248-b234-4373-9449-4043757d043a · inbound

LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams cites this paper.

LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 7

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Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation cites this paper.

Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 25

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Observation 8aa330f3-898e-4217-8508-1b36ea25a20b · inbound

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference cites this paper.

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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Observation aeec097a-a6a7-4685-b0a1-af1c8d334661 · inbound

Reward Model Generalization for Compute-Aware Test-Time Reasoning cites this paper.

Reward Model Generalization for Compute-Aware Test-Time Reasoning MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 35

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Observation 7c98ba6d-c323-4975-9849-0c133478a1d6 · inbound

AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity cites this paper.

AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 9

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Observation 4999cafd-4f82-4a86-8e13-90bd51e734a5 · inbound

SeerAttention-R: Sparse Attention Adaptation for Long Reasoning cites this paper.

SeerAttention-R: Sparse Attention Adaptation for Long Reasoning MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 29

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Learn from the Past: Fast Sparse Indexing for Large Language Model Decoding cites this paper.

Learn from the Past: Fast Sparse Indexing for Large Language Model Decoding MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 10

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From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation cites this paper.

From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 18

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Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification cites this paper.

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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Pay Attention to Attention Distribution: A New Local Lipschitz Bound for Transformers cites this paper.

Pay Attention to Attention Distribution: A New Local Lipschitz Bound for Transformers MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 17

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Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series cites this paper.

Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 7

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Synergy: End-to-end Concept Model cites this paper.

Synergy: End-to-end Concept Model MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 9

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NABLA: Neighborhood Adaptive Block-Level Attention cites this paper.

NABLA: Neighborhood Adaptive Block-Level Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 19

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DeltaLLM: A Training-Free Framework Exploiting Temporal Sparsity for Efficient Edge LLM Inference cites this paper.

DeltaLLM: A Training-Free Framework Exploiting Temporal Sparsity for Efficient Edge LLM Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 10

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ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference cites this paper.

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 25

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Observation ca52ff46-90bc-4a78-ae48-08d8c6da7500 · inbound

Enhancing Reliability in LLM-Integrated Robotic Systems: A Unified Approach to Security and Safety cites this paper.

Enhancing Reliability in LLM-Integrated Robotic Systems: A Unified Approach to Security and Safety MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 18

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Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs cites this paper.

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 24

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Observation 691b9a4c-d2e9-45d6-876a-a9f44abdf1c1 · inbound

Prism: Spectral-Aware Block-Sparse Attention cites this paper.

Prism: Spectral-Aware Block-Sparse Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 4

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Observation 83f6ced1-9abc-41e9-a942-c1eb01f4f7dd · inbound

PrefixWall: Mitigating Prefix Caching Side Channels in Shared LLM Systems cites this paper.

PrefixWall: Mitigating Prefix Caching Side Channels in Shared LLM Systems MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-21T12:15:06.744912Z

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Observation e8fe1080-28b1-4054-957e-2b2ed372cf7f · inbound

Three non-Hermitian random matrix universality classes of complex edge statistics: Spacing ratios and distributions cites this paper.

Three non-Hermitian random matrix universality classes of complex edge statistics: Spacing ratios and distributions MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 9

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Observation 5b77b6de-5270-476c-8eec-3f8775bcb0e7 · inbound

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention cites this paper.

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:43:00.751161Z

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Observation 371997cc-fc2a-45a3-a6fc-09deef0a4244 · inbound

StreamIndex: Memory-Bounded Compressed Sparse Attention via Streaming Top-k cites this paper.

StreamIndex: Memory-Bounded Compressed Sparse Attention via Streaming Top-k MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T06:15:37.731448Z

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Observation 3bcb5b8b-a10f-4efd-8c81-1b156e449bba · inbound

Long Context Pre-Training with Lighthouse Attention cites this paper.

Long Context Pre-Training with Lighthouse Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.397118Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6e946a6a-3acd-40b1-887a-3f10d559de34 · inbound

Sparse Attention as a Range Searching Problem: Towards an Inference-Efficient Index for KV Cache cites this paper.

Sparse Attention as a Range Searching Problem: Towards an Inference-Efficient Index for KV Cache MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:15:50.429219Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 44cbbdd6-45e9-46b0-93d7-d27c7a5d104e · inbound

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention cites this paper.

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T10:53:13.547437Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 82c0a072-b8d5-43c0-a43e-a8a86834bd94 · inbound

IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference cites this paper.

IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:03:59.863178Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f543456c-1afd-4396-ba3f-1c23272a88e3 · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 134

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:32:46.749346Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 40b9c12d-7e6f-48da-b1f5-6d1606fbe75d · inbound

How Much Dense Attention is Necessary? Oracle-Guided Sparse Prefill for Full/GQA Layers in Hybrid Long-Context Models cites this paper.

How Much Dense Attention is Necessary? Oracle-Guided Sparse Prefill for Full/GQA Layers in Hybrid Long-Context Models MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:17:09.159889Z

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Observation 220dc4c9-14fb-475a-915e-5bbb705f6507 · inbound

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance cites this paper.

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:37:31.268022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e4a10a0d-e597-4083-a80a-1d11a8bd2bbf · inbound

From Rigid to Dynamic: Entropy-Guided Adaptive Inference for Long-Context LLMs cites this paper.

From Rigid to Dynamic: Entropy-Guided Adaptive Inference for Long-Context LLMs MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-27T17:01:07.726301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d46ba56a-1e4d-4629-a0b0-f65436b9c3a7 · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 132

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T05:09:36.976767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 91bc4a43-88c4-4dc1-a536-759e80b6eaf9 · inbound

Token-Operations-Oriented Inference Optimization Techniques for Large Models cites this paper.

Token-Operations-Oriented Inference Optimization Techniques for Large Models MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 132

Resolution: unresolved; no resolver link, observed 2026-08-02T10:49:13.460701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46920f48-52ae-436b-9d5a-203aa039cf3a · inbound

NLL-Guided Full-Attention Layer Selection for Training-Free Sliding-Window Adaptation cites this paper.

NLL-Guided Full-Attention Layer Selection for Training-Free Sliding-Window Adaptation MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:03:51.719634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 517cc6a6-ee9e-4000-bfeb-1fec7201f700 · inbound

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM cites this paper.

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:24:21.385249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8ea4c474-9722-4fe5-a252-a84a522b42ae · inbound

Hierarchical Global Attention (HGA) cites this paper.

Hierarchical Global Attention (HGA) MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:55:28.774424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0fcff984-9533-4404-b38f-594b5faea618 · inbound

Uncertainty-gated selection for block-sparse attention cites this paper.

Uncertainty-gated selection for block-sparse attention MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T22:15:14.580916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45063632-881f-418d-8182-17cf68216e57 · inbound

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents cites this paper.

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-07-10T01:36:44.231104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8f387e1f-e50b-47f9-88e7-abfa0bf8fff3 · inbound

KAP: Bridging the Knowledge Selection-Runtime Consumption Gap in LLM Systems cites this paper.

KAP: Bridging the Knowledge Selection-Runtime Consumption Gap in LLM Systems MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T19:52:40.866676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a485c77-41fc-46fd-a732-9357902f67c8 · inbound

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference cites this paper.

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T20:50:03.978556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac14ab7f-d113-4e76-9b76-816b3b767422 · inbound

OasisKV: Scaling In-Decode KV Cache Beyond HBM with Lookahead Sparse Prefetching cites this paper.

OasisKV: Scaling In-Decode KV Cache Beyond HBM with Lookahead Sparse Prefetching MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T00:32:37.605595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers