UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge | Paper Citation Record

Observation e32df82e-0b82-4bde-b96e-a6fc77a698a9 · outbound

This paper cites Attention is all you need,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Attention is all you need,

Reference 1

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Observation 36b613a3-f314-42a5-aeaf-e9b2e1b0b291 · outbound

This paper cites GPT-4 Technical Report.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge GPT-4 Technical Report

Reference 3

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Observation a455d192-1b8b-4c51-a974-5444b2ff48f5 · outbound

This paper cites Edgellm: Fast on-device llm inference with speculative decoding,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Edgellm: Fast on-device llm inference with speculative decoding,

Reference 4

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This paper cites Tenet: An efficient sparsity-aware lut-centric architec- ture for ternary llm inference on edge,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Tenet: An efficient sparsity-aware lut-centric architec- ture for ternary llm inference on edge,

Reference 5

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This paper cites Efficient inference for edge large language models,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Efficient inference for edge large language models,

Reference 6

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Observation 3573c1ed-d213-43fe-a8a0-7e6dd3caa118 · outbound

This paper cites Hqp: Sensitivity-aware hybrid quantization and pruning for ultra-low-latency edge ai inference,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Hqp: Sensitivity-aware hybrid quantization and pruning for ultra-low-latency edge ai inference,

Reference 7

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Observation 7256c3b9-6579-4967-b4c3-72bcde7efa2e · outbound

This paper cites Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency

Reference 8

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Observation b6dab895-3ee1-4ebe-bd9e-cebfc9fc7376 · outbound

This paper cites A unified and resource-aware framework for adaptive inference optimization on edge devices,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge A unified and resource-aware framework for adaptive inference optimization on edge devices,

Reference 9

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Observation 57d5f87a-7660-4883-bf2d-aff7ae0f1811 · outbound

This paper cites Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices

Reference 10

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Observation 48e8ba41-e9f3-4d7f-ad30-6138c2f9806e · outbound

This paper cites H2eal: Hybrid-bonding architecture with hybrid sparse attention for efficient long-context llm inference,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge H2eal: Hybrid-bonding architecture with hybrid sparse attention for efficient long-context llm inference,

Reference 11

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Observation d735169a-fb09-4d58-b1c0-f61e8b9e3d60 · outbound

This paper cites Gptq: Accurate post-training quantization for generative pre-trained transformers,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Gptq: Accurate post-training quantization for generative pre-trained transformers,

Reference 12

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Observation 778cd9c9-cea3-4f58-906c-e3619c3399f9 · outbound

This paper cites Awq: Activation-aware weight quanti- zation for on-device LLM compression and acceleration,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Awq: Activation-aware weight quanti- zation for on-device LLM compression and acceleration,

Reference 13

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Observation 53f80e26-2ee7-465b-b94e-33f9963f40e2 · outbound

This paper cites Qserve: W4a8kv4 quantization and system co-design for efficient llm serving,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Qserve: W4a8kv4 quantization and system co-design for efficient llm serving,

Reference 14

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Observation d368b82d-868b-453d-8ba0-de167cbda201 · outbound

This paper cites FlatQuant: Flatness Matters for LLM Quantization.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge FlatQuant: Flatness Matters for LLM Quantization

Reference 15

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Observation f1c7cdd9-0473-491b-aedb-ad8728347b6c · outbound

This paper cites LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Reference 16

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Observation 6cdfe297-8f34-48e2-950f-3814763d6db7 · outbound

This paper cites SmoothQuant: Accurate and efficient post-training quantization for large language models,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge SmoothQuant: Accurate and efficient post-training quantization for large language models,

Reference 17

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Observation 046f9a38-d0fb-48d5-ae75-62d1045143ce · outbound

This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Sparsegpt: Massive language models can be accurately pruned in one-shot,

Reference 18

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Observation bb98d5e5-50cf-4d10-a4c9-069f951d2b3c · outbound

This paper cites Unleashing network/accelerator co-exploration potential on fpgas: A deeper joint search,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Unleashing network/accelerator co-exploration potential on fpgas: A deeper joint search,

Reference 19

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Observation cf7b5df2-95e6-4630-af16-49bcb67304b7 · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge PaLM-E: An Embodied Multimodal Language Model

Reference 20

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This paper cites Foundation models in autonomous driving: A survey on scenario generation and scenario analysis,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Foundation models in autonomous driving: A survey on scenario generation and scenario analysis,

Reference 21

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Observation 44a86edf-1e17-4d32-9cb3-94e35d5ba7b7 · outbound

This paper cites Intelligent Assistant Language Understanding On Device.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Intelligent Assistant Language Understanding On Device

Reference 22

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Observation 4f410ef4-782c-4eb8-9ae9-3e3918c0dd92 · outbound

This paper cites Private llm inference on consumer black- well gpus: A practical guide for cost-effective local deployment in smes,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Private llm inference on consumer black- well gpus: A practical guide for cost-effective local deployment in smes,

Reference 23

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Observation 5df39e1f-77ec-492d-913f-d281794a4cc8 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Efficient memory management for large language model serving with pagedattention,

Reference 24

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Observation 096f2b0e-e92e-48ec-9a70-4aef88b8f3e1 · outbound

This paper cites Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,

Reference 25

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Observation 64b24222-b831-4819-b475-270e1a2c6a8a · outbound

This paper cites Wrp: Weight recover prune for structured sparsity,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Wrp: Weight recover prune for structured sparsity,

Reference 26

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Observation 73ef787b-cd4f-4dcb-a3d3-5df2d51b054a · outbound

This paper cites Structured pruning for large language models using coupled components elimination and minor fine-tuning,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Structured pruning for large language models using coupled components elimination and minor fine-tuning,

Reference 27

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Observation c213d2d9-454f-4641-86e3-b607f2ef8cec · outbound

This paper cites Unisparta: A unified sparse tensor program tuning framework,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Unisparta: A unified sparse tensor program tuning framework,

Reference 28

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Observation 9f400c61-4807-41f8-8509-6baea235b01b · outbound

This paper cites Closertome: A unified framework for accurate and transferable latency prediction across heterogeneous devices,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Closertome: A unified framework for accurate and transferable latency prediction across heterogeneous devices,

Reference 29

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Observation 87a07782-4901-43b4-b6c3-1f6bdbf0b776 · outbound

This paper cites Sparse gpu kernels for deep learning,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Sparse gpu kernels for deep learning,

Reference 30

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Observation 476a3036-6e4d-4ff3-8694-2888c44c5441 · outbound

This paper cites Dtc-spmm: Bridging the gap in accelerating general sparse matrix multiplication with tensor cores,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Dtc-spmm: Bridging the gap in accelerating general sparse matrix multiplication with tensor cores,

Reference 31

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Observation 9dc8fdac-502c-4518-a87a-36225c41839f · outbound

This paper cites High Performance Unstructured SpMM Computation Using Tensor Cores.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge High Performance Unstructured SpMM Computation Using Tensor Cores

Reference 32

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Observation d625940a-3aa5-4f92-93e4-2177901cead1 · outbound

This paper cites Acc-spmm: Accelerating general-purpose sparse matrix-matrix multiplication with gpu tensor cores,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Acc-spmm: Accelerating general-purpose sparse matrix-matrix multiplication with gpu tensor cores,

Reference 33

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Observation 9a51e21c-3b40-411b-b54c-891c67399322 · outbound

This paper cites V oltrix: Sparse {Matrix-Matrix}multiplication on tensor cores with asynchronous and balanced kernel optimization,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge V oltrix: Sparse {Matrix-Matrix}multiplication on tensor cores with asynchronous and balanced kernel optimization,

Reference 34

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Observation ca3a53d4-3eb1-4f08-b9c0-1b8529d384b0 · outbound

This paper cites {SparTA}:{Deep-Learning}model sparsity via{Tensor- with-Sparsity-Attribute},.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge {SparTA}:{Deep-Learning}model sparsity via{Tensor- with-Sparsity-Attribute},

Reference 35

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Observation e644f87f-7eff-4d7d-83f3-95f372ccef9c · outbound

This paper cites cusparse library user guide,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge cusparse library user guide,

Reference 36

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Observation 685a4805-e82b-42ba-8f36-c622fb9910e5 · outbound

This paper cites cuSPARSELt,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge cuSPARSELt,

Reference 37

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Observation adbbfad2-d07e-4028-99f4-d68fe5a3c4eb · outbound

This paper cites Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity

Reference 38

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Observation 040defa0-ce08-4624-9015-0898cbafeab1 · outbound

This paper cites Spinfer: Leveraging low-level sparsity for efficient large language model inference on gpus,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Spinfer: Leveraging low-level sparsity for efficient large language model inference on gpus,

Reference 39

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Observation b9119f88-8de1-4c92-bbe8-22b3a84e8f60 · outbound

This paper cites Sputnik: Sparse matrix multiplication on gpus,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Sputnik: Sparse matrix multiplication on gpus,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.714739Z

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Observation 8fcc6f41-34f2-4be4-9336-81e88b79fe16 · outbound

This paper cites Nvidia jetson agx orin developer kit,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Nvidia jetson agx orin developer kit,

Reference 41

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Observation 8156f3f9-4bd9-431b-86ac-7285f34dd375 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 42

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Observation 86034bed-f3e5-4c73-8d50-8c8053f20aab · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge OPT: Open Pre-trained Transformer Language Models

Reference 43

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Observation b6761266-fdb3-45b4-9124-e88596bb7f7f · outbound

This paper cites Qwen2 Technical Report.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Qwen2 Technical Report

Reference 44

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Observation a1e28cf9-2e28-41fb-99b9-4fa3ed02c662 · outbound

This paper cites Llama 3: Open foundation and instruction-tuned models,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Llama 3: Open foundation and instruction-tuned models,

Reference 45

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Observation d504adc6-2e79-4e11-bd1f-0cd281c722d6 · outbound

This paper cites Cutlass: Cuda templates for linear algebra subroutines and solvers,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Cutlass: Cuda templates for linear algebra subroutines and solvers,

Reference 46

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Observation d85dbe4e-a52c-4760-8aff-b0bb09672f72 · outbound

This paper cites cublas library user guide,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge cublas library user guide,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.604215Z

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Observation d43fd8cd-d093-4e7e-819c-db8ce32c10cb · outbound

This paper cites Fastertransformer,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Fastertransformer,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.576894Z

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Observation ffc38f0b-64fa-4337-8039-4a66f96141f2 · outbound

This paper cites A simple and effective pruning approach for large language models,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge A simple and effective pruning approach for large language models,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.554020Z

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Observation 2e7f0333-732b-4d8f-8bc7-9e1ba16b237d · outbound

This paper cites Atom: Low-bit quantization for efficient and accurate llm serving,.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge Atom: Low-bit quantization for efficient and accurate llm serving,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.532365Z

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Observation bd7c9003-2240-4437-a743-b7f1649931cb · outbound

This paper cites He examines various aspects of embedded systems, with a focus on performance, availability, flexibility, and energy efficiency.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge He examines various aspects of embedded systems, with a focus on performance, availability, flexibility, and energy efficiency

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.488007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f1cdba3-8dda-42f6-86bb-783c038b9f1a · outbound

This paper cites He is currently pursuing the Eng.D.

UnionSparse: An Index-Efficient Sparsity Framework for Low-Bit Sparse LLM Inference on Edge He is currently pursuing the Eng.D

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:11:15.510650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

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Outbound references

Pith citing papers