Paper Citation Record · LEDGER

Instruction-Following Pruning for Large Language Models

As of 22 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 5 inbound Pith citation observations for arXiv:2501.02086.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.02086 v3

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:19:29.214129Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:23.951879Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-10T12:07:03.716884Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy4
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c40f70b-b299-45d7-a625-03c7af48acb6 · outbound

This paper cites C., Guo, M., Lee-Thorp, J., Tay, Y ., et al.

Instruction-Following Pruning for Large Language Models C., Guo, M., Lee-Thorp, J., Tay, Y ., et al

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:19:29.837118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c00ead1b-5903-493e-8707-0d8e9b761ecb · outbound

This paper cites Program Synthesis with Large Language Models.

Instruction-Following Pruning for Large Language Models Program Synthesis with Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.070757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f24cf5a-f1ca-4c56-ad05-5c641a508b10 · outbound

This paper cites The only difference is the feed-forward dimension.

Instruction-Following Pruning for Large Language Models The only difference is the feed-forward dimension

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:19:29.795248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6d890257-98ec-46d8-99a9-0aa13044fb23 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Instruction-Following Pruning for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.084576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9fcd72e-c02b-44c5-b3bc-2222c5a0d937 · outbound

This paper cites Everybody prune now: Structured pruning of llms with only forward passes.arXiv preprint arXiv:2402.05406,.

Instruction-Following Pruning for Large Language Models Everybody prune now: Structured pruning of llms with only forward passes.arXiv preprint arXiv:2402.05406,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.093111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c66b875-2d13-408a-833d-bbbbcfb3d03b · outbound

This paper cites Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation.

Instruction-Following Pruning for Large Language Models Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.096334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7155b0dc-f940-4d62-85b8-6cf00566a0fc · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Instruction-Following Pruning for Large Language Models Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.106341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d701fc8-72e1-4143-9276-4bb69a05f808 · outbound

This paper cites Apple intelligence foundation language models.

Instruction-Following Pruning for Large Language Models Apple intelligence foundation language models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.111304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fb52c7e-17e5-418d-95a2-dae3bea00fde · outbound

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

Instruction-Following Pruning for Large Language Models Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.124167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e09d598-f261-40c7-96ea-972fc3019240 · outbound

This paper cites CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models.

Instruction-Following Pruning for Large Language Models CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.128331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e86c242f-7b64-44a0-a6dd-3eb363a45e12 · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Instruction-Following Pruning for Large Language Models GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.133068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c109257c-7a89-4c89-a680-499c5e8e0782 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Instruction-Following Pruning for Large Language Models DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.141016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3996f77f-02ff-497c-991b-e6f29934006a · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

Instruction-Following Pruning for Large Language Models ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.144827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 297d8ae4-19df-4a4a-8b00-37afeafade35 · outbound

This paper cites ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models.

Instruction-Following Pruning for Large Language Models ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.149008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c839691f-71a6-4cad-b12c-148ef8832737 · outbound

This paper cites Exploring Sparsity in Recurrent Neural Networks.

Instruction-Following Pruning for Large Language Models Exploring Sparsity in Recurrent Neural Networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.153224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aea19de-0288-4599-807a-36fb0a015e30 · outbound

This paper cites Searching for Activation Functions.

Instruction-Following Pruning for Large Language Models Searching for Activation Functions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.158144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bf3653d-b88e-41e3-b0b3-20fc966cfc23 · outbound

This paper cites GLU Variants Improve Transformer.

Instruction-Following Pruning for Large Language Models GLU Variants Improve Transformer

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.162049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e48bf37d-762c-42aa-9a6f-26e6ffb3ccc8 · outbound

This paper cites ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models.

Instruction-Following Pruning for Large Language Models ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.166818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9236a10-5b54-4624-9e8a-905eb3f06318 · outbound

This paper cites LLM Pruning and Distillation in Practice: The Minitron Approach.

Instruction-Following Pruning for Large Language Models LLM Pruning and Distillation in Practice: The Minitron Approach

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.171100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0006281a-f2dc-48b0-8bb6-762f063298b7 · outbound

This paper cites EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing.

Instruction-Following Pruning for Large Language Models EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.176245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77932845-af3d-414a-beae-58613ce6306a · outbound

This paper cites Qwen2 Technical Report.

Instruction-Following Pruning for Large Language Models Qwen2 Technical Report

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.184404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4d6b3ae-cb66-4216-9a5a-22965c674f09 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Instruction-Following Pruning for Large Language Models Instruction-Following Evaluation for Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.187457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5146d308-32f4-4c59-8eb4-a345faf62b1c · outbound

This paper cites Sirius: Contextual Sparsity with Correction for Efficient LLMs.

Instruction-Following Pruning for Large Language Models Sirius: Contextual Sparsity with Correction for Efficient LLMs

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.191182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 819d994b-8d42-4f80-ac85-f8663dd62e5a · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Instruction-Following Pruning for Large Language Models To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.195589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 144d69b7-5adc-4121-93d6-2e5665b4abc1 · outbound

This paper cites Appendix A.1.

Instruction-Following Pruning for Large Language Models Appendix A.1

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:19:29.809537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d3946b2c-3f1b-4cd0-9251-508d40e35b6e · outbound

This paper cites an unresolved cited work.

Instruction-Following Pruning for Large Language Models Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:19:29.779739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ed6807dc-b9e4-4d3d-b63e-94aa6504f8b6 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Instruction-Following Pruning for Large Language Models Gaussian Error Linear Units (GELUs)

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.115556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2227c287-ee8c-4c52-9c56-b3dc8b4e9488 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Instruction-Following Pruning for Large Language Models Distilling the Knowledge in a Neural Network

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.119957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4e0a824-e120-402b-b9de-36975fbc8b21 · outbound

This paper cites ST-MoE: Designing Stable and Transferable Sparse Expert Models.

Instruction-Following Pruning for Large Language Models ST-MoE: Designing Stable and Transferable Sparse Expert Models

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.199657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eab8472a-0f9c-4082-a7f1-7396a547589d · outbound

This paper cites MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation.

Instruction-Following Pruning for Large Language Models MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.075540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d5ee176-b941-4062-8b20-f45c0aeaf464 · outbound

This paper cites Structured pruning of large language models.

Instruction-Following Pruning for Large Language Models Structured pruning of large language models

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:19:29.824207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4c6b787f-4e74-4448-8ead-52139073b97a · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Instruction-Following Pruning for Large Language Models From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.137128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ca31374-41af-44ca-a294-90bd5d29365e · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Instruction-Following Pruning for Large Language Models DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.088698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5be8dfdc-4be1-4fc7-a9f3-cae7d9eb90a4 · outbound

This paper cites The Llama 3 Herd of Models.

Instruction-Following Pruning for Large Language Models The Llama 3 Herd of Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.101459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35bdb79b-114d-41de-8089-e534004d4489 · outbound

This paper cites ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models.

Instruction-Following Pruning for Large Language Models ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.065424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cacc37a-f449-43f4-9ee3-7e8a3747469f · outbound

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

Instruction-Following Pruning for Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.080217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5c6e9611-ed64-4256-9730-dffd85d5381e · inbound

Get Experience from Practice: LLM Agents with Record & Replay cites this paper.

Get Experience from Practice: LLM Agents with Record & Replay Instruction-Following Pruning for Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:23.951879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04212e8d-8b81-405f-b888-4f7744e76d8c · inbound

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning cites this paper.

Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning Instruction-Following Pruning for Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:54:14.254607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d632509-9cc7-4abe-9675-f75f8954adf7 · inbound

Fragile Knowledge, Robust Instruction-Following: The Width Pruning Dichotomy in Llama-3.2 cites this paper.

Fragile Knowledge, Robust Instruction-Following: The Width Pruning Dichotomy in Llama-3.2 Instruction-Following Pruning for Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-16T18:58:19.017918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f87028e6-38f2-49b8-aa6c-3f5df5b83b12 · inbound

Understanding Layer Patching in Model Size Interpolation cites this paper.

Understanding Layer Patching in Model Size Interpolation Instruction-Following Pruning for Large Language Models

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T12:07:03.718737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9f2d315c-a744-44a2-b2e3-7246a5d8d1a6 · inbound

Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers cites this paper.

Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers Instruction-Following Pruning for Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-07-30T11:48:49.482980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.