Accelerating Large Language Models through Partially Linear Feed-Forward Network | Paper Citation Record

Observation 47ae6c4c-283a-4f1e-9acf-e30db799f366 · outbound

This paper cites org/wiki/Constant_folding.

Accelerating Large Language Models through Partially Linear Feed-Forward Network org/wiki/Constant_folding

Reference 1

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This paper cites [Online; accessed 2024- 11-01].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2024- 11-01]

Reference 2

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This paper cites [Online; ac- cessed 2025-01-09].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; ac- cessed 2025-01-09]

Reference 3

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This paper cites https://gcc.gnu.org/onlinedocs/gcc/ Optimize-Options.html.

Accelerating Large Language Models through Partially Linear Feed-Forward Network https://gcc.gnu.org/onlinedocs/gcc/ Optimize-Options.html

Reference 4

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This paper cites https://github.com/python/cpython?tab= readme-ov-file.

Accelerating Large Language Models through Partially Linear Feed-Forward Network https://github.com/python/cpython?tab= readme-ov-file

Reference 5

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This paper cites [Online; accessed 2024-11-24].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2024-11-24]

Reference 6

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This paper cites [Online; accessed 2025-01-14].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2025-01-14]

Reference 7

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This paper cites [Online; accessed 2024-12-16].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2024-12-16]

Reference 8

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This paper cites apache.org/sql/.

Accelerating Large Language Models through Partially Linear Feed-Forward Network apache.org/sql/

Reference 9

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This paper cites https://huggingface.co/docs/ transformers/index.

Accelerating Large Language Models through Partially Linear Feed-Forward Network https://huggingface.co/docs/ transformers/index

Reference 10

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This paper cites https://docs.rapids.ai/api/ cuml/stable/.

Accelerating Large Language Models through Partially Linear Feed-Forward Network https://docs.rapids.ai/api/ cuml/stable/

Reference 11

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Observation 010db526-213b-4a13-863c-b8a8ac4d08ba · outbound

This paper cites [Online; accessed 2025-01-09].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2025-01-09]

Reference 12

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This paper cites [Online; accessed 2024-11-01].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2024-11-01]

Reference 13

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Unresolved cited work

Reference 14

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This paper cites [Online; ac- cessed 2025-01-13].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; ac- cessed 2025-01-13]

Reference 15

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This paper cites [On- line; accessed 2025-01-09].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [On- line; accessed 2025-01-09]

Reference 16

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This paper cites [Online; accessed 2025-01-09].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2025-01-09]

Reference 17

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This paper cites [Online; accessed 2025-01-08].

Accelerating Large Language Models through Partially Linear Feed-Forward Network [Online; accessed 2025-01-08]

Reference 18

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Observation b4b13c58-2e90-40d2-a3d1-7788b69cd37f · outbound

This paper cites The falcon series of open language models, 2023.

Accelerating Large Language Models through Partially Linear Feed-Forward Network The falcon series of open language models, 2023

Reference 19

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

Accelerating Large Language Models through Partially Linear Feed-Forward Network Piqa: Reasoning about physical commonsense in natural language

Reference 20

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This paper cites Language Models are Few-Shot Learners.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Language Models are Few-Shot Learners

Reference 21

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This paper cites DSFormer: Effective Compression of Text-Transformers by Dense-Sparse Weight Factorization.

Accelerating Large Language Models through Partially Linear Feed-Forward Network DSFormer: Effective Compression of Text-Transformers by Dense-Sparse Weight Factorization

Reference 22

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This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Accelerating Large Language Models through Partially Linear Feed-Forward Network Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 23

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This paper cites Language modeling with gated convolutional networks.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Language modeling with gated convolutional networks

Reference 24

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This paper cites Llm.int8(): 8-bit matrix multiplication for transformers at scale.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Llm.int8(): 8-bit matrix multiplication for transformers at scale

Reference 25

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This paper cites The Llama 3 Herd of Models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network The Llama 3 Herd of Models

Reference 26

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This paper cites Sigmoid- weighted linear units for neural network function ap- proximation in reinforcement learning.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Sigmoid- weighted linear units for neural network function ap- proximation in reinforcement learning

Reference 27

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Observation 5c263d24-44cb-4662-9dfb-f2adc114ba08 · outbound

This paper cites Optq: Accurate quantization for generative pre-trained transformers.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Optq: Accurate quantization for generative pre-trained transformers

Reference 28

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This paper cites Gptq: Accurate post-training quantization for generative pre-trained transformers, 2023.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Gptq: Accurate post-training quantization for generative pre-trained transformers, 2023

Reference 29

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This paper cites A framework for few-shot language model evaluation, 07 2024.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A framework for few-shot language model evaluation, 07 2024

Reference 30

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This paper cites MiniLLM: On-Policy Distillation of Large Language Models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network MiniLLM: On-Policy Distillation of Large Language Models

Reference 31

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This paper cites How to access global memory efficiently in cuda c/c++ kernels | nvidia technical blog, 4 2014.

Accelerating Large Language Models through Partially Linear Feed-Forward Network How to access global memory efficiently in cuda c/c++ kernels | nvidia technical blog, 4 2014

Reference 32

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This paper cites Gaussian Error Linear Units (GELUs).

Accelerating Large Language Models through Partially Linear Feed-Forward Network Gaussian Error Linear Units (GELUs)

Reference 33

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This paper cites FineQuant: Unlocking Efficiency with Fine-Grained Weight-Only Quantization for LLMs.

Accelerating Large Language Models through Partially Linear Feed-Forward Network FineQuant: Unlocking Efficiency with Fine-Grained Weight-Only Quantization for LLMs

Reference 34

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This paper cites Self-normalizing neural networks.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Self-normalizing neural networks

Reference 35

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This paper cites Pruning vs quanti- zation: Which is better? Advances in neural information processing systems, 36:62414–62427, 2023.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Pruning vs quanti- zation: Which is better? Advances in neural information processing systems, 36:62414–62427, 2023

Reference 36

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This paper cites Efficient memory man- agement for large language model serving with page- dattention.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Efficient memory man- agement for large language model serving with page- dattention

Reference 37

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This paper cites Bloom: A 176b-parameter open-access multilingual language model.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Bloom: A 176b-parameter open-access multilingual language model

Reference 38

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This paper cites Losparse: Structured compression of large language models based on low-rank and sparse approximation.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Losparse: Structured compression of large language models based on low-rank and sparse approximation

Reference 39

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This paper cites A method for calculating the deriva- tive of activation functions based on piecewise linear approximation.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A method for calculating the deriva- tive of activation functions based on piecewise linear approximation

Reference 40

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Awq: Activation- aware weight quantization for on-device llm compres- sion and acceleration

Reference 41

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Deja vu: Con- textual sparsity for efficient llms at inference time

Reference 42

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Llm- pruner: On the structural pruning of large language mod- els

Reference 43

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Accelerating Large Language Models through Partially Linear Feed-Forward Network The penn treebank: an- notating predicate argument structure

Reference 44

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Pointer Sentinel Mixture Models

Reference 45

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Relu strikes back: Exploiting activation sparsity in large language models

Reference 46

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Implementation of a digital neuron with nonlinear activation function using piecewise linear approximation technique

Reference 47

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This paper cites On estimation of a probability den- sity function and mode.

Accelerating Large Language Models through Partially Linear Feed-Forward Network On estimation of a probability den- sity function and mode

Reference 48

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Unresolved cited work

Reference 49

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This paper cites Ma- trix compression via randomized low rank and low pre- cision factorization.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Ma- trix compression via randomized low rank and low pre- cision factorization

Reference 50

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This paper cites Glu variants improve transformer, 2020.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Glu variants improve transformer, 2020

Reference 51

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This paper cites Powerinfer: Fast large language model serving with a consumer-grade gpu.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Powerinfer: Fast large language model serving with a consumer-grade gpu

Reference 52

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This paper cites A simple and effective pruning approach for large lan- guage models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A simple and effective pruning approach for large lan- guage models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.975790Z

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This paper cites Variable kernel density estimation.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Variable kernel density estimation

Reference 54

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This paper cites Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 55

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Observation c9cb247a-04b8-46ed-907b-da86dcfe1aac · outbound

This paper cites Norm (mathemat- ics) - wikipedia, 9 2004.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Norm (mathemat- ics) - wikipedia, 9 2004

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.942046Z

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Observation 5d5e99fd-5c1c-4bd4-a127-7de77fb525ce · outbound

This paper cites Llama: Open and efficient foun- dation language models, 2023.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Llama: Open and efficient foun- dation language models, 2023

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.923335Z

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Observation b0d9b4fa-f029-4ca5-ba28-14f4c28ee7d3 · outbound

This paper cites Model Compression and Efficient Inference for Large Language Models: A Survey.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Model Compression and Efficient Inference for Large Language Models: A Survey

Reference 58

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Observation c208a281-ae88-4a78-8607-fa24e89187bb · outbound

This paper cites Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T19:29:57.469890Z

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Observation 196022ff-cf7d-4578-ba83-6afb1afda3c3 · outbound

This paper cites A Survey of Resource-efficient LLM and Multimodal Foundation Models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A Survey of Resource-efficient LLM and Multimodal Foundation Models

Reference 60

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Observation d809c6b8-c51d-4e3d-a727-71dfc47701ed · outbound

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Qwen2.5 Technical Report

Reference 61

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This paper cites Llmcbench: Benchmarking large language model compression for efficient deployment.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Llmcbench: Benchmarking large language model compression for efficient deployment

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.905501Z

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Observation 880d2a4f-b811-4098-81fe-7d2af96ea0c1 · outbound

This paper cites Zeroquant: Efficient and affordable post-training quantization for large-scale transformers.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Zeroquant: Efficient and affordable post-training quantization for large-scale transformers

Reference 63

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Observation b61e8c3d-98b9-45e5-b58f-7bab992c0e90 · outbound

This paper cites Outlier weighed layerwise sparsity (OWL): A missing secret sauce for pruning LLMs to high sparsity.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Outlier weighed layerwise sparsity (OWL): A missing secret sauce for pruning LLMs to high sparsity

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.877191Z

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Observation a7f3fe86-1afd-43a3-9585-2e055337003d · outbound

This paper cites ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization.

Accelerating Large Language Models through Partially Linear Feed-Forward Network ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization

Reference 65

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Observation ae8c5ab6-16aa-4c53-8d15-ab52856f56d3 · outbound

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Accelerating Large Language Models through Partially Linear Feed-Forward Network A novel sigmoid function approx- imation suitable for neural networks on fpga

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.858841Z

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Observation e6207a2a-4e7b-49e9-a5c3-422b04599a81 · outbound

This paper cites Inves- tigating layer importance in large language models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Inves- tigating layer importance in large language models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.841083Z

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Observation c3fd90f2-2ebd-4c22-aec3-8dbf4e0f84e1 · outbound

This paper cites Plug-and-play: An efficient post-training pruning method for large lan- guage models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Plug-and-play: An efficient post-training pruning method for large lan- guage models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:29:57.823674Z

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Observation 16628c73-4829-48be-bc05-9294ae5df128 · outbound

This paper cites A Survey on Efficient Inference for Large Language Models.

Accelerating Large Language Models through Partially Linear Feed-Forward Network A Survey on Efficient Inference for Large Language Models

Reference 69

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Observation 0f360ec6-00c8-4083-9147-66736c8aa1f8 · outbound

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Accelerating Large Language Models through Partially Linear Feed-Forward Network Unresolved cited work

Reference 2023

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