Adaptive Pruning for Large Language Models with Structural Importance Awareness | Paper Citation Record

Observation 073edcdf-dc7e-475e-87c0-d039b834d1a9 · outbound

This paper cites LaMDA: Language Models for Dialog Applications.

Adaptive Pruning for Large Language Models with Structural Importance Awareness LaMDA: Language Models for Dialog Applications

Reference 1

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Observation fc28afb6-5268-47de-94c9-71d4c68310dc · outbound

This paper cites A survey on large language models: Applications challenges limitations and practical usage,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness A survey on large language models: Applications challenges limitations and practical usage,

Reference 2

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Observation 441ab76e-2d40-4f1d-837b-4e5220518175 · outbound

This paper cites Emergent Abilities of Large Language Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Emergent Abilities of Large Language Models

Reference 3

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Observation 85410af1-fd87-4a18-87ac-2b5caedb1fe4 · outbound

This paper cites Toward Democratized Generative AI in Next-Generation Mobile Edge Networks.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Toward Democratized Generative AI in Next-Generation Mobile Edge Networks

Reference 4

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This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 5

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Observation a4e5ffac-7606-4a52-b881-6b0ddd144b97 · outbound

This paper cites The Internet of Things in the Era of Generative AI: Vision and Challenges.

Adaptive Pruning for Large Language Models with Structural Importance Awareness The Internet of Things in the Era of Generative AI: Vision and Challenges

Reference 6

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Observation 14ea9a7b-1394-471f-a9f5-c15cbf9b7f43 · outbound

This paper cites An Overview of Neural Network Compression.

Adaptive Pruning for Large Language Models with Structural Importance Awareness An Overview of Neural Network Compression

Reference 7

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Observation 32605587-ea3b-4149-b7b3-719e86068f08 · outbound

This paper cites Structured Model Pruning of Convolutional Networks on Tensor Processing Units.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Structured Model Pruning of Convolutional Networks on Tensor Processing Units

Reference 8

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Observation 13448688-33b4-45c2-937f-ef99db3c1537 · outbound

This paper cites Personalized federated learning by structured and unstructured pruning under data heterogeneity,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Personalized federated learning by structured and unstructured pruning under data heterogeneity,

Reference 9

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Observation 5cc73ea6-3d05-4c43-926e-fa4aebd18140 · outbound

This paper cites Generative AI agents with large language model for satellite networks via a mixture of experts transmission,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Generative AI agents with large language model for satellite networks via a mixture of experts transmission,

Reference 10

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Observation 7636205e-bf7f-47c6-b8b1-01925ea1c075 · outbound

This paper cites Optimal brain damage,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Optimal brain damage,

Reference 11

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Observation 68a5ce05-739e-4b1b-a5ff-79d542b52cef · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 12

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Observation 65279d03-b12d-495d-a2f5-a655726d0313 · outbound

This paper cites The design and implementation of xiaoice an empathetic social chatbot,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness The design and implementation of xiaoice an empathetic social chatbot,

Reference 13

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Observation 057a39e1-12d9-408d-8c2d-6101c497cbeb · outbound

This paper cites Interactive AI with retrieval-augmented generation for next generation networking,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Interactive AI with retrieval-augmented generation for next generation networking,

Reference 14

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Observation 4f3bd275-67b9-443a-8fae-6d9b95763df9 · outbound

This paper cites Dynamic Sparse Graph for Efficient Deep Learning.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Dynamic Sparse Graph for Efficient Deep Learning

Reference 15

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Observation 557fb637-0df5-4f22-8163-ee05a4c2271c · outbound

This paper cites ZipLM: Inference-aware struc- tured pruning of language models,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness ZipLM: Inference-aware struc- tured pruning of language models,

Reference 16

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Observation ba7fd398-c25e-47f8-a622-a99d64d335bb · outbound

This paper cites Fluctuation-based adaptive structured pruning for large language models,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Fluctuation-based adaptive structured pruning for large language models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.306752Z

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Observation 51998fd5-72e1-4bfe-9335-32dfd11a0b93 · outbound

This paper cites Llm-pruner: On the structural pruning of large language models,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Llm-pruner: On the structural pruning of large language models,

Reference 18

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Observation ba84c68a-cd27-4a91-97fc-d1bf73f2be5b · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness LLaMA: Open and Efficient Foundation Language Models

Reference 19

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Observation 0322c16c-379e-439f-8abf-0a8e32f42e42 · outbound

This paper cites Vicuna: An open-source chatbot impressing GPT-4 with 90%* ChatGPT quality.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Vicuna: An open-source chatbot impressing GPT-4 with 90%* ChatGPT quality

Reference 20

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Observation 70d5377f-2ac2-48cb-9dc4-7bc0009de8c8 · outbound

This paper cites GLM: General Language Model Pretraining with Autoregressive Blank Infilling.

Adaptive Pruning for Large Language Models with Structural Importance Awareness GLM: General Language Model Pretraining with Autoregressive Blank Infilling

Reference 21

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Observation 5029b7f6-781b-464d-bba8-13c6e11480cc · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness A Simple and Effective Pruning Approach for Large Language Models

Reference 22

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Observation fd86edbd-afe3-4e80-9515-3aa0d252ae93 · outbound

This paper cites LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery.

Adaptive Pruning for Large Language Models with Structural Importance Awareness LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Reference 23

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Observation 2e640b37-f791-430c-a7b6-7e6cfb912106 · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness Sparsegpt: Massive language models can be accurately pruned in one-shot,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.268925Z

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Observation 95f21e58-03fb-4d9a-a45b-125bb377c610 · outbound

This paper cites Pruning Large Language Models via Accuracy Predictor.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Pruning Large Language Models via Accuracy Predictor

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:40:41.959346Z

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Observation 9188a738-4415-480a-8953-5da0b3cc5094 · outbound

This paper cites Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods

Reference 26

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Observation b459aaff-7bd0-4e27-8a53-9cb80e905329 · outbound

This paper cites MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models

Reference 27

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Observation ef2647dc-de31-4975-92cf-0b3532afae0a · outbound

This paper cites EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting.

Adaptive Pruning for Large Language Models with Structural Importance Awareness EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting

Reference 28

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Observation 70c6fafe-75d3-49f8-add8-3a0de9d099d9 · outbound

This paper cites AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models

Reference 29

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Observation 79cf3993-c5f9-42d9-97d4-bb5bd7a00855 · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 30

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Observation 95633254-7792-4b09-bcff-3ce9b5407997 · outbound

This paper cites Parameter-efficient transfer learning for NLP,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Parameter-efficient transfer learning for NLP,

Reference 31

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Observation 531f9cbf-895a-4675-aa7c-5db333386c2a · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness LoRA: Low-Rank Adaptation of Large Language Models

Reference 32

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Observation 1c92b357-3bb3-432a-8dd5-b846009c0fdd · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Qlora: Efficient finetuning of quantized llms

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.241965Z

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Observation f8bf1718-5c81-42fd-9c73-30a66ac0168b · outbound

This paper cites A fast post-training pruning framework for transformers,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness A fast post-training pruning framework for transformers,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.227619Z

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Observation a5debc4e-cfba-418f-9e4f-b71da7c164ab · outbound

This paper cites UPop: Unified and progressive pruning for compressing vision-language transformers,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness UPop: Unified and progressive pruning for compressing vision-language transformers,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.213326Z

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Observation 50d3ed81-b638-4028-bb1f-0633cab759f4 · outbound

This paper cites Polynomial-type Lya- punov–Krasovskii functional and Jacobi–Bessel inequality: Further re- sults on stability analysis of time-delay systems,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Polynomial-type Lya- punov–Krasovskii functional and Jacobi–Bessel inequality: Further re- sults on stability analysis of time-delay systems,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.198453Z

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Observation e0eaf831-e285-4543-ba80-c97e9418c190 · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 37

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Observation cf19a336-786d-4ff3-83ec-1f7202f2d6fd · outbound

This paper cites An empirical study of LLaMA3 quantization: from LLMs to MLLMs.

Adaptive Pruning for Large Language Models with Structural Importance Awareness An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Reference 38

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Observation 6f4d5a8d-c23e-4369-843d-624e53216ca8 · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:41.635431Z

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Observation 4ca98292-ee6b-4efb-b9cd-7a8a15bbf069 · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 40

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Observation 6296675f-c466-4244-b6b1-500e43d12c84 · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 41

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Observation 53a38563-41af-40de-99a5-862fa485a99f · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness Piqa: Reasoning about physical commonsense in natural language,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.184979Z

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Observation 9f274ee5-694a-4e66-ab61-501d6df4867a · outbound

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

Adaptive Pruning for Large Language Models with Structural Importance Awareness Winogrande: An adversarial winograd schema challenge at scale,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.170890Z

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Observation 75438ffa-64d2-4ce7-9a52-ae66b0fb40c3 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:41.660706Z

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Observation 3b8769b0-e9ac-4723-b3aa-5f4e1d2bc212 · outbound

This paper cites Building a large annotated corpus of English: The penn treebank,.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Building a large annotated corpus of English: The penn treebank,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:42.156814Z

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Observation 7a25c146-ac19-466a-b943-83a9ea2d0839 · outbound

This paper cites Pointer Sentinel Mixture Models.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Pointer Sentinel Mixture Models

Reference 46

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Observation fb3df22c-ffb6-41ab-907b-54d2ed26202c · outbound

This paper cites LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning.

Adaptive Pruning for Large Language Models with Structural Importance Awareness LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:41.677113Z

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Observation 125a3234-417a-44e4-9eb1-f28ab8cab719 · outbound

This paper cites Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books.

Adaptive Pruning for Large Language Models with Structural Importance Awareness Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:41.682230Z

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Observation 457bb50a-2c30-4a43-990d-1efd9bf03ba3 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Adaptive Pruning for Large Language Models with Structural Importance Awareness WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:41.686204Z

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