Paper Citation Record · LEDGER

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning

As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 3 inbound Pith citation observations for arXiv:2501.15296.

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

pith.paper-citation-record.v1
2501.15296 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:32:54.116272Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:42:22.520527Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

39 of 39 outbound references displayed

verified exact1
verified fuzzy5
unresolved33
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation c90cd5c5-fee2-4b75-aa68-5b2f05fa4e5d · outbound

This paper cites The Falcon Series of Open Language Models.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning The Falcon Series of Open Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.972672Z

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Observation 5c4a6b51-3e89-4818-9c8d-83f4561dfc3b · outbound

This paper cites SliceGPT: Compress Large Language Models by Deleting Rows and Columns.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.976863Z

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Observation 3bacd362-1ff9-41ec-baa2-ac6d76f11fca · outbound

This paper cites Layer Normalization.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Layer Normalization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.981410Z

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Observation 3a40122f-d631-4c8b-9584-2adc0b5e2790 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Piqa: Reasoning about physical commonsense in natural language

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.984957Z

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Observation 090afa5d-ea06-4645-a531-60778b7cf458 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.988448Z

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Observation db838245-713d-4bb7-91fd-2e8e2374dd91 · outbound

This paper cites SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.992042Z

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Observation 451f9d46-3ab0-48b3-a96d-b8b4a776ace0 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning A framework for few-shot language model evaluation, 07 2024

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.995836Z

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Observation c7fd3d33-1c89-4423-87d4-8038a7507366 · outbound

This paper cites Textbooks Are All You Need.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Textbooks Are All You Need

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:53.999050Z

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Observation dc52e6f3-ee4a-4bd3-bbd8-ca630d15a058 · outbound

This paper cites Deep Residual Learning for Image Recognition.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Deep Residual Learning for Image Recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.002418Z

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Observation 44ff6135-48b0-4416-bb3f-6c64b23aa840 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Measuring Massive Multitask Language Understanding

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.005965Z

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Observation d3f84b8a-df3b-43fc-9314-75860f2ef7ee · outbound

This paper cites Language model compression with weighted low-rank factorization.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Language model compression with weighted low-rank factorization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.009491Z

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Observation 060ada23-c151-4d2c-b960-bdabfb67adde · outbound

This paper cites Lo RA : Low-rank adaptation of large language models.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Lo RA : Low-rank adaptation of large language models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.012974Z

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Observation e9123af5-47ac-4fb4-96d4-8159c899cf01 · outbound

This paper cites Auto-Encoding Variational Bayes.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Auto-Encoding Variational Bayes

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.016285Z

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Observation 88db8791-81bb-45ff-959d-d5ee1c98a97b · outbound

This paper cites Levesque, Ernest Davis, and Leora Morgenstern.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Levesque, Ernest Davis, and Leora Morgenstern

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:32:54.639028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3de2cf23-0200-4663-87a9-6228fbc40e9b · outbound

This paper cites Decoupled Weight Decay Regularization.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Decoupled Weight Decay Regularization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.022935Z

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Observation 81646c9e-d24d-4a40-a316-9ee493e0e8f1 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Llm-pruner: On the structural pruning of large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:32:54.628594Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 68ee4151-6a5f-415d-8408-157623c4b4cd · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Llm-pruner: On the structural pruning of large language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:32:54.618167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c430f2b7-198d-4ce3-90f5-5cb175e85a01 · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.033130Z

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Observation 0bb44596-f95f-4c08-9129-611d2e721665 · outbound

This paper cites Matrix Differential Calculus with Applications in Statistics and Econometrics.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Matrix Differential Calculus with Applications in Statistics and Econometrics

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:32:54.607613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 707a8322-dc35-44aa-9938-e7c90043dfbc · outbound

This paper cites Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:32:54.597106Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 64f82259-48a8-4581-89d0-d40c5f991e1a · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.043605Z

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Observation 44ae986e-7a52-449d-a980-e5e3fcf19e91 · outbound

This paper cites Pointer Sentinel Mixture Models.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Pointer Sentinel Mixture Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.047169Z

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Observation 8679894c-91c8-4a07-942e-f65e10d8099b · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.050968Z

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Observation 76a41ed2-d822-4a0a-9045-c2fa95b8e695 · outbound

This paper cites GPT-4 Technical Report.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning GPT-4 Technical Report

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.054507Z

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Observation 437f71b4-966f-461e-a0ff-39dc0f9db9a7 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Winogrande: An adversarial winograd schema challenge at scale

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.058302Z

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Observation fa552a96-365c-4a30-b7ea-010e2f21ef37 · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.061587Z

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Observation 96a56a86-f5c6-4e27-9bae-bfb055fb9867 · outbound

This paper cites Stanford alpaca: An instruction-following llama model, 2023.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Stanford alpaca: An instruction-following llama model, 2023

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.065744Z

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Observation cc89f117-50de-4ec9-b98b-9db725ac7923 · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning LLaMA: Open and Efficient Foundation Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.069037Z

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Observation 1a125fd0-53eb-440d-843a-64f88a20597d · outbound

This paper cites Attention Is All You Need.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Attention Is All You Need

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.072761Z

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Observation 6d2a101d-b56e-4084-8eed-39b736f496a3 · outbound

This paper cites SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.080721Z

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Observation a54e1e25-beda-442a-b306-8a37ebfb157b · outbound

This paper cites Williams.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Williams

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.084758Z

Source-reported events for the cited work

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Observation 45fe3f12-09fc-4ac2-b5e5-895f8e406136 · outbound

This paper cites LaCo: Large Language Model Pruning via Layer Collapse.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning LaCo: Large Language Model Pruning via Layer Collapse

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.088498Z

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Unavailable: canonical work link unavailable.

Observation 971ca880-df12-4489-b086-b6e35d2ff84e · outbound

This paper cites ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.092131Z

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Observation bf5a6222-f591-45ce-a97c-e377cc0666ca · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.096589Z

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Observation 1262c97d-8014-4fb2-ba6b-27770a41c93b · outbound

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

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning OPT: Open Pre-trained Transformer Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.100519Z

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Observation ef313bc8-d80b-47b3-bb95-70dafb2e30f1 · outbound

This paper cites write newline.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning write newline

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.104402Z

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Observation 61d7e6f2-3537-4763-be34-7863e3da0968 · outbound

This paper cites @esa (Ref.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning @esa (Ref

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.108469Z

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Observation 005ec50c-7427-4d31-ac55-6ede1052a655 · outbound

This paper cites an unresolved cited work.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning Unresolved cited work

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T14:32:54.112594Z

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Observation 2b428907-fa4b-4b1c-bc47-f61a9b708727 · outbound

This paper cites We report the results with LLaMA-2-7B with RFT on Wikitext2 and Alpaca datasets in Table wikitext_with_rft and Table alpaca_with_rft , respectively.

You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning We report the results with LLaMA-2-7B with RFT on Wikitext2 and Alpaca datasets in Table wikitext_with_rft and Table alpaca_with_rft , respectively

Reference 40

Resolution: verified exact; raw_fallback, observed 2026-08-10T14:32:54.253434Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 052e0a74-8ea6-4abe-9850-bfc6f7250a8c · inbound

EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models cites this paper.

EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T04:42:22.520527Z

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Observation e2fe82bc-5295-4c01-9e41-ac0d4e3c25be · inbound

SecRL-Prune: Structured Reinforcement Learning-Based Pruning of CodeLLMs for Preserving Adversarial Code Mutation cites this paper.

SecRL-Prune: Structured Reinforcement Learning-Based Pruning of CodeLLMs for Preserving Adversarial Code Mutation You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-28T01:31:29.791122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 05067279-0961-484b-b232-cfb3d156823d · inbound

SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models cites this paper.

SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T16:41:28.839158Z

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Unavailable: canonical work link unavailable.