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Paper Citation Record · LEDGER

LLM-Pruner: On the Structural Pruning of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2305.11627.

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

pith.paper-citation-record.v1
2305.11627 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:21.943627Z

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

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

74
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 18b2373a-5818-4b45-b7d5-29e5e1dcfae5 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:28:39.374466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T20:28:38.900026Z digest=sha256:52c9091f9d8bae5df5380fe9ab7346b33ebdb4002afa205cb1aca32feb6a2a0e

Observation 5b7a9f93-8e13-4cb8-85c2-7aaa24cbf910 · inbound

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs cites this paper.

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:34:01.132821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-24T06:33:48.456209Z digest=sha256:8cb60ed5052b1492a30608423092839a305e7b8dcca7c5b9287351ed3c615abe

Observation c92e7249-6d5b-4c76-a9ae-2a1d8ec24ec9 · inbound

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security cites this paper.

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 253

Resolution
verified exact
arxiv_id, observed 2026-05-17T00:57:26.726551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T00:57:26.303195Z digest=sha256:d2f5fe8936c12f00633bcb6e1371f40a369fc2e733ff647fe223f8dacedbba80

Observation 6b6e9b1d-0818-485e-b782-db74ee69e692 · inbound

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration cites this paper.

CE-LSLM: Efficient Large-Small Language Model Inference and Communication via Cloud-Edge Collaboration LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:21.943627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:42:21.943627Z digest=sha256:b646534ea45d49ca512b726ce8041b5a0e3f69d1b7d7c0b7d8e7f3910ccfccba

Observation 7be6e0e3-43ae-4cf7-91b1-9025df43c6bd · inbound

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones cites this paper.

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:23.406830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:20:23.406830Z digest=sha256:154046e5adc6b6de27d8960d7d842fe7fecd6e4cc6eaa4ae7145ab932bb7b1b4

Observation 20dea1d0-7f61-4bd7-9a72-5ed531dfa1aa · inbound

The Case for Instance-Optimized LLMs in OLAP Databases cites this paper.

The Case for Instance-Optimized LLMs in OLAP Databases LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T19:39:31.279688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:39:31.279688Z digest=sha256:1c385b2a4ffcc975d73dbee2991529902b5eb56bf95d43f687db0ddd075e04ce

Observation 2e3d2b29-e9fa-4350-8b6a-64625e583a2e · inbound

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity cites this paper.

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T18:20:00.319815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:20:00.319815Z digest=sha256:3dca853ac88e3783f059252df884afe6b18441faa5e08bf614b17732f0f16838

Observation 316e5680-4332-4071-952e-c9fd654e1171 · inbound

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering cites this paper.

A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:17:30.339991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:17:30.339991Z digest=sha256:dc06a1b5f9c78e70c42888b14f8f47ce4da4132382cc3b347d3eec8c84281733

Observation f2d54b24-6f97-4cc4-8a80-9fbb479816d7 · inbound

Enhancing Large Multimodal Models with Adaptive Sparsity and KV Cache Compression cites this paper.

Enhancing Large Multimodal Models with Adaptive Sparsity and KV Cache Compression LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T13:30:43.024746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:30:43.024746Z digest=sha256:e01b7f290f00c12de6419de596320d7e425d35a7b5cab88d7b81e901981033dd

Observation 2b01fd41-63b5-46fd-b96a-276f6c95ef06 · inbound

CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering cites this paper.

CLARIFY: A Specialist-Generalist Framework for Accurate and Lightweight Dermatological Visual Question Answering LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T16:31:34.252943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:31:34.252943Z digest=sha256:92201f453c0bbafd73338a31e417626a7f1818a50d05174f64747b8722dc85be

Observation 29c8c2d7-ed2a-4609-8bc0-4e1936135af8 · inbound

Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM cites this paper.

Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-04T11:24:20.613129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T11:24:20.613129Z digest=sha256:d56537bfac7bafb5211f76edc351765cdadd2ca486894d02787ff3d08de86ff7

Observation 9e41dd5c-4aa4-40b2-b200-12d63ee3e27c · inbound

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs cites this paper.

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T21:32:46.231928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:32:46.231928Z digest=sha256:dc7aa99548209e9ffdc121d8a7ef973c56bd441cb19851c012376a5cec3a307a

Observation 09ff751e-021a-4c1e-baab-3ebbd12ad3af · 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 LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-02T14:17:03.155117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T00:33:19.474677Z digest=sha256:d38a3d9f5f79fa96f46b6e9b55cd4220a07b799408ea376865608798ec9060b2

Observation 6779bea9-088d-4b3e-a0b5-715bd7c9a87e · inbound

CascadeFormer: Depth-Tapered Transformers Motivated by Gradient Fan-in Asymmetry cites this paper.

CascadeFormer: Depth-Tapered Transformers Motivated by Gradient Fan-in Asymmetry LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-26T05:29:00.089072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:22:26.818078Z digest=sha256:2a0d81d9c1e609032f8fe3108a48b2931011a80f2e5dcc1f4f37f98cff52fab2

Observation e4b0301e-a34d-4b0b-9a68-95469e3bc857 · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 72

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T15:25:48.369109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T01:29:42.919461Z digest=sha256:9417df3b2b8ba3b13476bc2135b971d5468640bf1bc9241f46d40c2bc2119717

Observation 8c91917d-19a6-404a-9aaf-7fe65b81cfc1 · inbound

Fairness Pruning: Locating Demographic Bias in GLU-MLP Layers via Differential Activations cites this paper.

Fairness Pruning: Locating Demographic Bias in GLU-MLP Layers via Differential Activations LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-31T11:25:39.488624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T11:25:39.488624Z digest=sha256:a8db76210a459f72400d7ff82b040f0790858627ed7f19a25585ca29bbb24fab