Paper Citation Record · LEDGER

DarwinLM: Evolutionary Structured Pruning of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 12 inbound Pith citation observations for arXiv:2502.07780.

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

pith.paper-citation-record.v1
2502.07780 v4

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:39:09.589461Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:30.868615Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:56:20.572153Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy5
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d3fb247d-1691-48b8-b1c7-755605812f6b · outbound

This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

DarwinLM: Evolutionary Structured Pruning of Large Language Models GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.437345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2451882-0cac-4f90-a4ba-224a94ab4565 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

DarwinLM: Evolutionary Structured Pruning of Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.460074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db021aec-52ff-4927-8bf1-e0deb80a309b · outbound

This paper cites org/records/10256836,.

DarwinLM: Evolutionary Structured Pruning of Large Language Models org/records/10256836,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.466314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 223e63a8-696d-4224-8b7e-fc995043ecd2 · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models OLMo: Accelerating the Science of Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.472396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 363b53d1-08ec-468d-b165-0972311ae340 · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.491926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d4359af-9896-4b52-8bc2-5495b300cff5 · outbound

This paper cites Structural pruning of large language models via neural architecture search.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Structural pruning of large language models via neural architecture search

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:39:10.449395Z

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 fcaebf1a-5306-4fd8-ad94-9dc109472f79 · outbound

This paper cites The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.502096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6190810f-3a5d-43b6-9db0-ef7be1017dd3 · outbound

This paper cites Evolving knowledge distillation with large lan- guage models and active learning.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Evolving knowledge distillation with large lan- guage models and active learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:39:10.432198Z

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 196ec8e1-f710-4fcd-b2c8-adfee11451db · outbound

This paper cites LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.

DarwinLM: Evolutionary Structured Pruning of Large Language Models LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.512897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b9858a8-0484-4a0d-9041-bcaa8dd21d10 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

DarwinLM: Evolutionary Structured Pruning of Large Language Models The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.518281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3431147f-267a-4fe2-a761-1108e0950ca8 · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.524078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef10a020-0b0d-4ab6-bab3-62f1db9d6120 · outbound

This paper cites Compact Language Models via Pruning and Knowledge Distillation.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Compact Language Models via Pruning and Knowledge Distillation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.529197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb00abb2-6fcb-446a-a9c4-8c439587ff42 · outbound

This paper cites EvoPress: Accurate Dynamic Model Compression via Evolutionary Search.

DarwinLM: Evolutionary Structured Pruning of Large Language Models EvoPress: Accurate Dynamic Model Compression via Evolutionary Search

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.540751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 108c2495-b135-40d6-82b3-694becfe4038 · outbound

This paper cites Bi-mamba: Towards accurate 1-bit state space models.arXiv preprint arXiv:2411.11843,.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Bi-mamba: Towards accurate 1-bit state space models.arXiv preprint arXiv:2411.11843,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.545868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58193d75-dc75-4323-97be-a0ac34e8e8ec · outbound

This paper cites Structured pruning for efficient gen- erative pre-trained language models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Structured pruning for efficient gen- erative pre-trained language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:39:10.415806Z

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 828d6cbe-e6b8-4cdf-a62e-e7b029ee1ff7 · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.557254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41190357-c3f6-47f7-829e-4829ddf01ad5 · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.562177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da1be7dd-e7cd-4801-b113-a482fb707da8 · outbound

This paper cites Structured pruning of large language models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Structured pruning of large language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:39:10.398694Z

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 e71af61a-2d47-4b8b-bd8b-b36223a7677b · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models A Survey on Knowledge Distillation of Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.575087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cb60127-53c8-4de8-a755-96f38856c977 · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.579673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe03e990-bbfc-4e29-9321-221dd8473041 · outbound

This paper cites Appendix A.1.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Appendix A.1

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:39:10.381075Z

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 ade80e4c-e3e9-4ee6-923a-8afec18e7052 · outbound

This paper cites an unresolved cited work.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-08T11:39:10.365627Z

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 bc97ac90-e404-4897-a187-fa695b7a0e1d · outbound

This paper cites Measuring Massive Multitask Language Understanding.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Measuring Massive Multitask Language Understanding

Reference 1992

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.481680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cf598d5-b791-4bbd-88c9-2138a6bc45ae · outbound

This paper cites Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.486140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4552d4dc-05a5-4eb7-bc4e-0d23c51ccdaf · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.448488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a98c19f7-83ca-4d59-b96f-281ba108c7d5 · outbound

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

DarwinLM: Evolutionary Structured Pruning of Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.443255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a665f90-3402-4a0b-ae9a-782d207b496f · outbound

This paper cites Crowdsourcing Multiple Choice Science Questions.

DarwinLM: Evolutionary Structured Pruning of Large Language Models Crowdsourcing Multiple Choice Science Questions

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.570614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea83cfa1-fd80-46ad-866c-e46b5f1aba58 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

DarwinLM: Evolutionary Structured Pruning of Large Language Models DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.534277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec62ba22-deda-4977-b2b9-60ad4611c1e8 · outbound

This paper cites The Llama 3 Herd of Models.

DarwinLM: Evolutionary Structured Pruning of Large Language Models The Llama 3 Herd of Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.454237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0879de0-20b5-4512-9560-2606bf0d14a3 · outbound

This paper cites The Unreasonable Ineffectiveness of the Deeper Layers.

DarwinLM: Evolutionary Structured Pruning of Large Language Models The Unreasonable Ineffectiveness of the Deeper Layers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T11:39:09.477311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7287e1bf-ca2c-471b-976e-a5f585d31d34 · inbound

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up cites this paper.

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:30.868615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fac348a-30da-4891-b39c-dc1be7a6b1fc · inbound

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot cites this paper.

SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T04:48:39.329408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d47a72e-4edb-46e3-88a7-31f2a37c23a3 · inbound

GeLaCo: An Evolutionary Approach to Layer Compression cites this paper.

GeLaCo: An Evolutionary Approach to Layer Compression DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:20.865857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f06c780-054b-4572-b047-7384f857302a · inbound

Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation cites this paper.

Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-04T13:31:03.739460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f8332c6-dd3d-461e-b033-92098bb6e568 · inbound

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE cites this paper.

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 e5a9ee51-7911-40f9-96c3-8162cffc11dc · inbound

Rethinking Layer Redundancy in Large Language Models: Calibration Objectives and Search for Depth Pruning cites this paper.

Rethinking Layer Redundancy in Large Language Models: Calibration Objectives and Search for Depth Pruning DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 bccd3aef-50c5-445c-805e-02e4b87a9c02 · inbound

Rethinking Layer Redundancy in Large Language Models: Calibration Objectives and Search for Depth Pruning cites this paper.

Rethinking Layer Redundancy in Large Language Models: Calibration Objectives and Search for Depth Pruning DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 9fa2839f-7d51-4a28-9297-01b2e5b8239e · inbound

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training cites this paper.

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 996fc274-a8a9-41e8-8298-eb093bc6e64f · inbound

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training cites this paper.

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 b6a78910-92e7-4f60-adcf-55776626944c · inbound

TAPIOCA: Why Task- Aware Pruning Improves OOD model Capability cites this paper.

TAPIOCA: Why Task- Aware Pruning Improves OOD model Capability DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 7a26f8be-893f-4462-9376-c4eaf0260501 · inbound

From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression cites this paper.

From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 118

Resolution: verified exact; arxiv_id, observed 2026-07-16T01:22:24.421594Z

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 8cd6f8d9-dfc2-4d3a-983f-4a5728b10c99 · inbound

Omega-S: A Functional Resilience Index for LLM Fine-Tuning cites this paper.

Omega-S: A Functional Resilience Index for LLM Fine-Tuning DarwinLM: Evolutionary Structured Pruning of Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T10:26:24.624287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.