TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks | Paper Citation Record

Observation e1f0e729-223f-4bee-8858-ce512183436f · outbound

This paper cites URL https://huggingface.co/docs/transformers/perplexity.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks URL https://huggingface.co/docs/transformers/perplexity

Reference 1

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Observation db6fd0df-5211-41b5-8823-5c3d79ef54df · outbound

This paper cites GPT-4 Technical Report.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks GPT-4 Technical Report

Reference 2

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Observation 02d71e93-905a-4b71-974c-470125c9f663 · outbound

This paper cites Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers

Reference 3

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Observation e6bd628b-c225-450c-a3f3-7c4bd75b14b7 · outbound

This paper cites Careful Selection of Knowledge to solve Open Book Question Answering.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Careful Selection of Knowledge to solve Open Book Question Answering

Reference 4

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Observation f03f9715-ffd1-49bc-8139-080463acaf2f · outbound

This paper cites Iterative bregman projections for regularized transportation problems.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Iterative bregman projections for regularized transportation problems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.984563Z

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Observation a9651dbc-92c8-4822-912f-e78517e79537 · outbound

This paper cites Fast as CHITA: Neural Network Pruning with Combinatorial Optimization.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Fast as CHITA: Neural Network Pruning with Combinatorial Optimization

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:46:48.209452Z

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Observation f6adcfc5-07ee-4559-a8bf-78450911aa3e · outbound

This paper cites Piqa: Reasoning about physical commonsense in natural language.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Piqa: Reasoning about physical commonsense in natural language

Reference 7

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Observation 48563408-e2af-4e86-b260-5f8b976f2ea0 · outbound

This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Distributed optimization and statistical learning via the alternating direction method of multipliers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:43.185022Z

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Observation a71963ff-b7d5-40de-9195-1b26730d92b6 · outbound

This paper cites The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:43.285559Z

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Observation a554a8e5-56d6-47c0-a7c1-b9ac123bb1dd · outbound

This paper cites Language models are few-shot learners.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Language models are few-shot learners

Reference 10

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Observation 612d9439-67b0-4c3e-804e-7eaea0007cef · outbound

This paper cites Venom: A vectorized n: M format for unleashing the power of sparse tensor cores.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Venom: A vectorized n: M format for unleashing the power of sparse tensor cores

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.800995Z

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Observation c95a7367-1d0a-469c-8c2b-a143c7ade818 · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks End-to-end autonomous driving: Challenges and frontiers

Reference 12

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Observation a5d4588c-9805-42b2-9e7a-d0eeda82057a · outbound

This paper cites A survey on deep neural network pruning: Taxonomy, comparison, analysis, and recommendations.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks A survey on deep neural network pruning: Taxonomy, comparison, analysis, and recommendations

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.684719Z

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Observation e9d70a9f-d26f-42aa-9045-eb1163b7924a · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 14

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Observation e91fc62c-6534-4e0e-98ee-a8039a87ccf5 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 15

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Observation 5cc5f60e-dd80-4983-8457-74b9caae3aee · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Sinkhorn distances: Lightspeed computation of optimal transport

Reference 16

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Observation bec69b01-c218-4d63-be8e-3144c812a94b · outbound

This paper cites SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 17

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Observation e5bd4ce3-5950-408a-99c4-d4f056f40fee · outbound

This paper cites The Llama 3 Herd of Models.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks The Llama 3 Herd of Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:43.933912Z

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Observation ebb61e49-2fdc-42f6-b1c8-07ec465e8b28 · outbound

This paper cites An algorithm for restricted least squares regression.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks An algorithm for restricted least squares regression

Reference 19

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Observation 866b21a9-759e-4362-b102-2b0812570de3 · outbound

This paper cites Efficient n: M sparse dnn training using algorithm, architecture, and dataflow co-design.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Efficient n: M sparse dnn training using algorithm, architecture, and dataflow co-design

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.519150Z

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Observation 0c32e2dd-39d0-4a26-80ae-9762599cd6bd · outbound

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

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Sparsegpt: Massive language models can be accurately pruned in one-shot

Reference 21

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Observation 41e852dc-4260-4466-a8c1-b8dccb2fa200 · outbound

This paper cites A framework for few-shot language model evaluation, 12 2023.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks A framework for few-shot language model evaluation, 12 2023

Reference 22

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Observation 8c1bb971-0e93-4560-b3b7-a28429c551be · outbound

This paper cites Knowledge distillation: A survey.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Knowledge distillation: A survey

Reference 23

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Observation ccefec65-aebe-4c78-8ccb-6eaba0401c49 · outbound

This paper cites Gurobi Optimizer Reference Manual , 2022.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Gurobi Optimizer Reference Manual , 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.350805Z

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Observation 34ae7980-b392-4401-a22b-b5a8b767efbe · outbound

This paper cites Learning both weights and connections for efficient neural network.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Learning both weights and connections for efficient neural network

Reference 25

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Observation ad146490-024c-474b-b676-5a6578ba2650 · outbound

This paper cites Second order derivatives for network pruning: Optimal brain surgeon.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Second order derivatives for network pruning: Optimal brain surgeon

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:44.590828Z

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TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Unresolved cited work

Reference 27

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Observation 0ceaeec2-1bed-4570-95c7-cc9478a32d68 · outbound

This paper cites Accelerating Transformer Pre-training with 2:4 Sparsity.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Accelerating Transformer Pre-training with 2:4 Sparsity

Reference 28

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Observation 46d8d1f0-d5a4-43d6-856d-995c96b9ad9e · outbound

This paper cites Elsa: Exploiting layer-wise n: m sparsity for vision transformer acceleration.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Elsa: Exploiting layer-wise n: m sparsity for vision transformer acceleration

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.166869Z

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Observation dd0ee617-9d04-49da-93d0-8c1343d4fed4 · outbound

This paper cites Accelerated sparse neural training: A provable and efficient method to find n: m transposable masks.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Accelerated sparse neural training: A provable and efficient method to find n: m transposable masks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:51.029678Z

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Observation e10be430-0765-4f02-b679-4d7428cd94e9 · outbound

This paper cites Accurate post training quantization with small calibration sets.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Accurate post training quantization with small calibration sets

Reference 31

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Observation 350444bb-375c-4c8e-94ba-4677a58bbc39 · outbound

This paper cites Efficient gpu kernels for n: M-sparse weights in deep learning.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Efficient gpu kernels for n: M-sparse weights in deep learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:50.670755Z

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Observation 1618e5c5-1cda-4f39-92d9-d30296cb4144 · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 33

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Observation 2ed6ea2a-5491-453e-bd3e-07ddea94b3e5 · outbound

This paper cites Tb-stc: Transposable block-wise n: M structured sparse tensor core.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Tb-stc: Transposable block-wise n: M structured sparse tensor core

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:50.524132Z

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Observation 35dc61ae-7218-4f22-ab10-2d8667b8564c · outbound

This paper cites cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia

Reference 35

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Observation b557936a-4f0a-4448-b1fc-9e13bc1d81cd · outbound

This paper cites Step: learning n: M structured sparsity masks from scratch with precondition.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Step: learning n: M structured sparsity masks from scratch with precondition

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:50.333329Z

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Observation 976b74cf-9585-4876-94e4-e4dc744cbd38 · outbound

This paper cites NM-SpMM: Accelerating Matrix Multiplication Using N:M Sparsity with GPGPU.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks NM-SpMM: Accelerating Matrix Multiplication Using N:M Sparsity with GPGPU

Reference 37

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Observation da8f57ea-6399-4965-bcbe-effad6ab3cf7 · outbound

This paper cites Determining optimal channel partition for 2: 4 fine grained structured sparsity.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Determining optimal channel partition for 2: 4 fine grained structured sparsity

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:50.177328Z

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Observation 5d774289-cd90-4c6b-836e-316870bd10b6 · outbound

This paper cites A Fast and Accurate Splitting Method for Optimal Transport: Analysis and Implementation.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks A Fast and Accurate Splitting Method for Optimal Transport: Analysis and Implementation

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:46:47.839135Z

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Observation bb0aff04-6f42-452e-9996-a60be29c3e7a · outbound

This paper cites The penn treebank: Annotating predicate argument structure.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks The penn treebank: Annotating predicate argument structure

Reference 40

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Observation 7cf6acc1-50d5-41c6-8c1c-8dec0d2ee065 · outbound

This paper cites ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 41

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Observation bcd0d025-805d-4571-bd7a-5a6cf94f3b7b · outbound

This paper cites OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization

Reference 42

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Observation f1c35d6d-b232-4689-8ce2-7ba4c7804a63 · outbound

This paper cites Pointer sentinel mixture models.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Pointer sentinel mixture models

Reference 43

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Observation 474a2f02-cac8-40a5-92b7-e2b064a86632 · outbound

This paper cites Accelerating Sparse Deep Neural Networks.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Accelerating Sparse Deep Neural Networks

Reference 44

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TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Nvidia a100 tensor core gpu architecture

Reference 45

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Observation 21a36ac4-7335-4925-8bed-28d568c80446 · outbound

This paper cites Accelerating condensed interior-point methods on simd/gpu architectures.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Accelerating condensed interior-point methods on simd/gpu architectures

Reference 46

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Observation 7ed03a03-579c-4b25-be53-3be1bcf42114 · outbound

This paper cites Automatic differentiation in pytorch.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Automatic differentiation in pytorch

Reference 47

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This paper cites A Survey on Recognizing Textual Entailment as an NLP Evaluation.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks A Survey on Recognizing Textual Entailment as an NLP Evaluation

Reference 48

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TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Channel permutations for n: m sparsity

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:49.659994Z

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Observation 631e4852-e3e4-4a94-9515-13a1c2fdcad6 · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Robust speech recognition via large-scale weak supervision

Reference 50

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TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Unresolved cited work

Reference 51

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Observation 0f899900-2fb2-4aa1-8e3e-3f3fa0a992d7 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Winogrande: An adversarial winograd schema challenge at scale

Reference 52

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Observation 54938bf5-8007-41e7-a70d-55a2ea6af930 · outbound

This paper cites Combinatorial optimization: polyhedra and efficiency, volume 24.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Combinatorial optimization: polyhedra and efficiency, volume 24

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:49.327369Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eadf387a-624b-4ea1-81c2-9c0a79e4f7cc · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks A Simple and Effective Pruning Approach for Large Language Models

Reference 54

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Observation 4f9bef89-66d2-45c0-af76-578a6e95566e · outbound

This paper cites Dominosearch: Find layer-wise fine-grained n: M sparse schemes from dense neural networks.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Dominosearch: Find layer-wise fine-grained n: M sparse schemes from dense neural networks

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:49.161055Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d71f289-9990-4f06-bcd0-e7e2ab475f48 · outbound

This paper cites Manifold regularized dynamic network pruning.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Manifold regularized dynamic network pruning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:48.976297Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 83b8b7c9-5e7f-479d-a4c5-ff635677cee7 · outbound

This paper cites Optimal transport: old and new, volume 338.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Optimal transport: old and new, volume 338

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:48.807436Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b94c9c1f-39e6-4838-b14a-288052c423d3 · outbound

This paper cites Learning structured sparsity in deep neural networks.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Learning structured sparsity in deep neural networks

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:46.910676Z

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Observation 886369b4-f666-4131-9d79-5dc575772d54 · outbound

This paper cites Sustainable ai: Environmental implications, challenges and opportunities.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Sustainable ai: Environmental implications, challenges and opportunities

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:48.645502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b3b9b980-907f-4d67-b9a8-61e595cbddbe · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:47.036380Z

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Observation 855cb346-29fb-439e-8814-f67f8e1f482d · outbound

This paper cites Bi-directional masks for efficient n: M sparse training.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Bi-directional masks for efficient n: M sparse training

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:48.493426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fe987263-940b-4fa5-962d-91ebb5ad712a · outbound

This paper cites Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T12:46:47.171415Z

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Unavailable: canonical work link unavailable.

Observation d81de07e-0fe4-4a8b-a9f1-9147babd3184 · outbound

This paper cites Sparse tensor core: Algorithm and hardware co-design for vector-wise sparse neural networks on modern gpus.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Sparse tensor core: Algorithm and hardware co-design for vector-wise sparse neural networks on modern gpus

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:46:48.361558Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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