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Paper Citation Record · LEDGER

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods

As of 20 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.03373.

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

pith.paper-citation-record.v1
2505.03373 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:59:21.965294Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0014be80-f6cc-4f51-9f3d-5f436ed65982 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 1

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.827814Z digest=sha256:a651225230659852063df0b42f712c363bec29571d60eb16a92270d520f03e84

Observation cfcbb4df-f044-4e9e-9e60-9891d7be8953 · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.832820Z digest=sha256:2719add327e77617a2f2ae2b1af230488a36d7f26bcfaf7cac9fb4742d43f482

Observation e3dffc4a-13c8-4f3c-809f-baf3aa8b9067 · outbound

This paper cites Apple intelligence: Ai for the rest of us.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Apple intelligence: Ai for the rest of us

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-15T23:59:22.331147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.836857Z digest=sha256:46861f6ece4b4411382e64b0276e3be63d8bfb32cda61ea809dd9cbedc6df002

Observation 1ac7147b-2a27-4403-a302-ea6517f984a3 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Reference 4

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:59:21.840221Z digest=sha256:f8bb003c9f24748db38ebd549a437aec1670ae28ceb28e4ec406ff95a5c434f7

Observation 7f465b6f-224c-4484-83f4-3b892f709d3e · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 5

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.843725Z digest=sha256:d033ffe6e29334cb52f802963bac225d425edc8da50991ef3e3ca34cf2050cdf

Observation cad56c8c-5218-4d67-8f68-48696355c166 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 6

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no resolver link, observed 2026-08-15T23:59:21.846999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.846999Z digest=sha256:91bcb90cbb92b9f5a5e8f443426549b28c6b413958d119afb65702435f18bcb4

Observation be36bd54-8c57-48b0-b03f-73d6d2f80a21 · outbound

This paper cites Deepseek-v3 technical report.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Deepseek-v3 technical report

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:59:22.316697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.850633Z digest=sha256:2ffdce15a05ac3f9cd1f6a01b23f12c2e58d617c932b4a756bcfc8d30e8264ae

Observation 32bccd7b-cc3a-4321-be56-aa16c765c06d · outbound

This paper cites Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.853686Z digest=sha256:fb2986e7596d8a2bac19fea54b7903240caf7878aeb9ab1d736c29cdcc5a2ea4

Observation e22f9967-430b-4dfe-8406-39ad96c5d282 · outbound

This paper cites MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models

Reference 9

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source=arxiv_source observed=2026-08-15T23:59:21.857135Z digest=sha256:e5b8554e58cada6b706dbd563f8a8273c8b8be80380a9cee9ed0de4aca1dba8f

Observation 83fccc48-24f3-4d04-b926-8a2bfcb52b16 · outbound

This paper cites and Alistarh, D.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods and Alistarh, D

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:59:22.306345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.860663Z digest=sha256:6c68879122a6daeaf06668117d668f87441f60f41b9cea9cbaeab2595179f641

Observation 29e971b7-3997-4ad6-a263-2bea653ee8df · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.863882Z digest=sha256:1a5b5ff1606a62c05fea450999907ad95b53ab398f9cb69b362740457a1eca8e

Observation 85699077-fa2d-4f79-b23b-aa6c48e5e666 · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.866835Z digest=sha256:5bea9c0e9ecf794054fe75988baabb50d6fc25aad30ea5ca6b49edbb33ee963f

Observation fb714285-3e60-4041-b434-7d454bc27d02 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Gemini: A Family of Highly Capable Multimodal Models

Reference 13

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source=arxiv_source observed=2026-08-15T23:59:21.869662Z digest=sha256:1b7650ecada538b35f3d7a46ec7b31110517f15fc65e9fad231fb81ea8c2cab7

Observation 9d5d8998-0588-4316-a448-ac60a7a1d632 · outbound

This paper cites The Llama 3 Herd of Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods The Llama 3 Herd of Models

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.873012Z digest=sha256:291e6c6759aeca1f4da5ab8077261bc6972a59f110c463b38e46c0140eceed46

Observation bb9eb537-9fc1-42bd-96d5-0c89f323bbf9 · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.876157Z digest=sha256:c27d941583494c3c18d38a6b4f3aaa261c92c40745b614d572ecb8e78ada88fe

Observation 8a2b98f5-47a4-4ab2-bfcc-8c61d1a6ee32 · outbound

This paper cites FASP: Fast and Accurate Structured Pruning of Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods FASP: Fast and Accurate Structured Pruning of Large Language Models

Reference 16

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source=arxiv_source observed=2026-08-15T23:59:21.879051Z digest=sha256:2dcdb4c3255ffb463d3e672bbc2976516549ec4a58067a5714e77fc13df2ca36

Observation f8f2a5c6-1104-42bc-9e6d-73178991d407 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Adam: A Method for Stochastic Optimization

Reference 17

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source=arxiv_source observed=2026-08-15T23:59:21.882013Z digest=sha256:37009adbacadaa66478396830897117e04ac5790162a1f301b1b10e75787cee0

Observation 7e0735e5-b8a6-4491-a9a8-bac119b8cfae · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.885061Z digest=sha256:c68ca100814ad1586e74d9f9284fad41b7bf50f288b64e5dfa67327a0478c403

Observation 0b5de285-877d-40ac-b4a9-59e91ced00ae · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.888200Z digest=sha256:3c9a256fcdcda719b57c70d5e6c7fdf863716fc40a743c8999c7801e36dc30ee

Observation 7076de98-47f8-4453-995c-5c8cff13b7ab · outbound

This paper cites LLM-Pruner: On the Structural Pruning of Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods LLM-Pruner: On the Structural Pruning of Large Language Models

Reference 20

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:59:21.891302Z digest=sha256:0868a4bbf2d56cc2c42ef35d770bb6756f28c6c60a94f723cb3b5c830e804c04

Observation 0e2a46a9-0a87-4901-890a-89bc531f58c3 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 21

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:59:21.894461Z digest=sha256:ead97b36c492c8da374feafde24ef6158ffa9bdf8ee8506fcf64b2715f609aa9

Observation a9f57036-7d34-4bdf-9bb4-4c52de7322eb · outbound

This paper cites ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.897702Z digest=sha256:5adb921c6c2f499349ed3da214b56ce7742116a0df49915b93214d03c9cac79f

Observation 075fb19e-5d84-491d-845d-bcb61b4111dd · outbound

This paper cites Pointer Sentinel Mixture Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Pointer Sentinel Mixture Models

Reference 23

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source=arxiv_source observed=2026-08-15T23:59:21.900844Z digest=sha256:7e0861561c124316eb944e548c71084f9b76e893fcd761b357357f547ae184c5

Observation 621566ed-81d3-4b90-905f-5b30ce6f0545 · outbound

This paper cites Llama-3: Meta ai's latest language model.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Llama-3: Meta ai's latest language model

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:59:22.252228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.904115Z digest=sha256:385962d06df0963479c114902dcbc88dc1ea763f927e40512e1d63a754fe66b0

Observation 41b01414-4823-4bc1-9b2d-1f9ca2f9bf95 · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 25

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T23:59:21.907040Z digest=sha256:8828ddf017d78e9cae186f8bd21c1885d0cc2c2b89abf8025f8a554927f92215

Observation 9f10af0d-2536-4bfe-9ee7-8ad6543cde41 · outbound

This paper cites Accelerating Sparse Deep Neural Networks.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Accelerating Sparse Deep Neural Networks

Reference 26

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source=arxiv_source observed=2026-08-15T23:59:21.910051Z digest=sha256:d027ab56435f811c7bf6feb72bef67349ec5fe91efc143157c52557367671457

Observation e7d7942f-ec87-4eda-b0b5-9ff2b07e2106 · outbound

This paper cites Gpt-4 technical report.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Gpt-4 technical report

Reference 27

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raw_fallback, observed 2026-08-15T23:59:22.241904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.913467Z digest=sha256:2456ac08bc8794c42d6e08c8a2055d589c065b2c3360cf646e7025e0e88f55f5

Observation 31340767-9ee6-4ad2-b3b6-9c577efa1f83 · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-15T23:59:21.916678Z digest=sha256:be3811358eb3d632a072fe57d8d93deaf3d503930b4c62f18a47a04eefb1a5f8

Observation 8eed63e5-34a9-4de4-b0dc-b078e57e8e36 · outbound

This paper cites Qwen2.5 technical report.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Qwen2.5 technical report

Reference 29

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raw_fallback, observed 2026-08-15T23:59:22.225976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.919764Z digest=sha256:95dfa10ad9147cc436e1f737d74ffeacc6af8f2c31d90744c9105fa5dabc28af

Observation 0cb477fa-8706-4a0c-96e7-f377aa299330 · outbound

This paper cites L., Bhagavatula, C., and Choi, Y.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods L., Bhagavatula, C., and Choi, Y

Reference 30

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no resolver link, observed 2026-08-15T23:59:21.922871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.922871Z digest=sha256:706c6db250af8a814546624dc5e84a8d417b6f15f492dcd1732d2aff74d4aecf

Observation 2e705268-4f48-4fd6-b3ef-491f61173a47 · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-15T23:59:21.925899Z digest=sha256:f720aa88a0fe2f721fd1c85931404cfbc0fdfe8cae1470e3b7083e00902a418f

Observation 2a88c8d7-6d27-48a3-8d96-afe62660db23 · outbound

This paper cites Search for Efficient Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Search for Efficient Large Language Models

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.929165Z digest=sha256:bc9cd43e8a33a328127c83597320a374374b8d16a0b84b5a4f35f36b3dbdf8d2

Observation a796112b-bece-4df7-94c5-41206e66cfc0 · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods A Simple and Effective Pruning Approach for Large Language Models

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.932318Z digest=sha256:fe41939944518a6f5092910ff0a70ad86767073e1ff19757f725ce62b5c62586

Observation 8a8b9b27-fd04-4fa7-b1b5-3428d8ff95e6 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods LLaMA: Open and Efficient Foundation Language Models

Reference 34

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no resolver link, observed 2026-08-15T23:59:21.935578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.935578Z digest=sha256:bbcfdcb48dd2acceb248ce7d515149bd7048ffae9ceeb90708caaaa9514abecf

Observation 4610e7c1-db3b-458d-9640-06e034dcd8a2 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 35

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no resolver link, observed 2026-08-15T23:59:21.938854Z

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source=arxiv_source observed=2026-08-15T23:59:21.938854Z digest=sha256:d4ca3839397c537c3d5446302eb03dbfcb89b11f7e124572bdfd480b34e50b08

Observation 5599036f-1bed-4630-94ba-9a4b532d3f4c · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 36

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no resolver link, observed 2026-08-15T23:59:21.941873Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.941873Z digest=sha256:fe88364d61ec9f8406a51ea7561799c3f186c509048f48860c35847d595e9639

Observation cc56bfc5-33f8-41f4-908f-5b9832044e55 · outbound

This paper cites CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information

Reference 37

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no resolver link, observed 2026-08-15T23:59:21.945152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.945152Z digest=sha256:1a4d2d72154d113530a4868fa0af7a78882d326ae0fcdfac3eee20785943b181

Observation 7b321e2e-509c-4eee-8a56-795fdb8df737 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 38

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unresolved
no resolver link, observed 2026-08-15T23:59:21.948475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.948475Z digest=sha256:0c54cbcec57b404038758706b6962a5a0e9fc05e76bac510891fb36c6998294b

Observation 2f53fb20-b5da-4deb-9445-b0060ebfd290 · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods LaCo: Large Language Model Pruning via Layer Collapse

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T23:59:21.951720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.951720Z digest=sha256:414594045f5fcb636f604325c8b3396facbf78dfdcccff0454ee8ae4bc3ba8c1

Observation f046d744-6047-4049-bb16-dc644a7faccf · outbound

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

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods OPT: Open Pre-trained Transformer Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T23:59:21.955351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.955351Z digest=sha256:3e4a2f9eb01ebdb3bbfe83785a0f2bd27ca4283261f4b38f9cc21e04c9b99bc6

Observation 3c08c326-0638-4f05-b610-538d129b6267 · outbound

This paper cites FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T23:59:21.958580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.958580Z digest=sha256:38cd0f76e092b733df1da42d7e3b5f4518d08c04666ee2017b1af6450b7d6310

Observation 1c2d9fba-a45f-47dd-8389-04a8b1fd9a63 · outbound

This paper cites A Convex-optimization-based Layer-wise Post-training Pruner for Large Language Models.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods A Convex-optimization-based Layer-wise Post-training Pruner for Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T23:59:21.961549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.961549Z digest=sha256:c08fb3a4419b2a32ef710d4448224bbfcb452b2a9bad6a715dd14482c97712a2

Observation 72aa3154-9705-49dd-a307-a7f5a58483cf · outbound

This paper cites an unresolved cited work.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-15T23:59:22.205019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T23:59:21.965294Z digest=sha256:e39cb26f8da7f6df22d34afd9edf43290c0c5c3ac9a18bcbbc2c7841325e2b51

Pith citing papers

No inbound Pith citation observations are available.