Paper Citation Record · LEDGER

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs

As of 11 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2412.14426.

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

pith.paper-citation-record.v1
2412.14426 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:17:56.885258Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:26.292793Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:58:28.692022Z

Reference resolution

70 of 70 outbound references displayed

verified exact2
verified fuzzy1
unresolved67
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c9289a3b-e935-408b-ba9e-bad28ee5d87a · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.611533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63cd8f86-3ab5-4867-b766-acdd172bc0bf · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.616062Z

Source-reported events for the cited work

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Observation 303d73e3-5754-46bf-8752-eeef6c53dbb2 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.619728Z

Source-reported events for the cited work

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Observation 8adcb9cd-4612-4848-a386-ee899882e757 · outbound

This paper cites Layer Normalization.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Layer Normalization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.623947Z

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Observation a5aed046-c239-484c-a7bc-34f800f0a2b7 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.679308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b8833fdd-0169-40ec-954c-00baab62ef24 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.667682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a2ae5180-97d8-4fe7-a1b8-f961657358f8 · outbound

This paper cites A Recent Survey of Heterogeneous Transfer Learning.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs A Recent Survey of Heterogeneous Transfer Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.635918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9af885bf-a9b0-4227-a291-f0d216e3742a · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.656175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a2fb8e0e-3045-4f6e-8d21-ac34c84b94e3 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.644139Z

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Observation 549926a7-4b52-495f-95a8-5848d8ad7df1 · outbound

This paper cites Hudson, Ehsan Adeli, and Russ Altman.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Hudson, Ehsan Adeli, and Russ Altman

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:17:57.645622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0eac82e-871e-4623-a15f-b5a8e0c36b6c · outbound

This paper cites Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.651892Z

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Observation 1a95f531-cea9-4155-a95d-4abf0ff81c17 · outbound

This paper cites The Llama 3 Herd of Models.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs The Llama 3 Herd of Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.655871Z

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Observation 8aa98df6-2906-4d90-aa23-8fd900d0a087 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.659701Z

Source-reported events for the cited work

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Observation cf6e3f4d-a2c4-484e-b4dd-b74911565472 · outbound

This paper cites DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:17:57.301545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a98869ee-5890-4ffb-8efa-8a4c842cadab · outbound

This paper cites Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.668390Z

Source-reported events for the cited work

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Observation 91a47d0d-71be-461e-886c-459e0791450b · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.672478Z

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Observation 6ab4995c-def5-47aa-a956-185212d6e4b4 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.676338Z

Source-reported events for the cited work

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Observation b37ec56e-6a91-4050-bb92-2c4f98328b54 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs LoRA: Low-Rank Adaptation of Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.683114Z

Source-reported events for the cited work

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Observation 683b9187-37ba-4485-9b2e-1c8203e9237a · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Categorical Reparameterization with Gumbel-Softmax

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.687043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c118b74d-40f4-45a1-bf3f-18eafd6e1160 · outbound

This paper cites Fine-tuning and Utilization Methods of Domain-specific LLMs.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Fine-tuning and Utilization Methods of Domain-specific LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.690667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49db6295-5c76-4c38-8295-a295f36e804e · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.694257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93c48780-4ff4-4c3a-8182-93d08f90c17b · outbound

This paper cites BillSum: A Corpus for Automatic Summarization of US Legislation.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs BillSum: A Corpus for Automatic Summarization of US Legislation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.697713Z

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Observation b7e4a9d6-c77f-4422-8853-593d3482ec46 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.614152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c881e8ae-cab6-4eac-bed4-5226ecc54c8d · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.704995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27d1d1e6-44e0-4e63-827c-c8028b711794 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.708764Z

Source-reported events for the cited work

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Observation 280e1223-3438-459c-ada2-a5486a6916d4 · outbound

This paper cites MoDeGPT: Modular Decomposition for Large Language Model Compression.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs MoDeGPT: Modular Decomposition for Large Language Model Compression

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.713172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da0e8439-8ab8-443b-815e-dbe792ecced0 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.716980Z

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Observation 93f7da0d-e75d-4dc6-94d6-209082789501 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.595791Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4cc9bc4b-72a8-4f25-aaa2-9d2145491a4f · outbound

This paper cites Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.724468Z

Source-reported events for the cited work

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Observation c2c8fd07-c239-4cbb-a92d-8498832db9be · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.728340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d40a94bb-efce-433d-8b19-ed7f2215c323 · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.732578Z

Source-reported events for the cited work

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Observation ec1fc60c-ff1c-44d7-a95a-aca181f4ea26 · outbound

This paper cites Full Parameter Fine-tuning for Large Language Models with Limited Resources.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Full Parameter Fine-tuning for Large Language Models with Limited Resources

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.736630Z

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Observation b7f973e8-24b5-413e-a151-b34d66e7bf39 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.740383Z

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Observation 87f712e0-d56e-4446-9c21-bb60fcb349a8 · outbound

This paper cites MultiLegalPile: A 689GB Multilingual Legal Corpus.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs MultiLegalPile: A 689GB Multilingual Legal Corpus

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.744222Z

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Observation 38d5e26f-2792-455d-bed0-3fc30e773878 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.748772Z

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Observation 470119a2-c773-4483-8f6f-b1ee3165b1d6 · outbound

This paper cites Lessons from Natural Language Inference in the Clinical Domain.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Lessons from Natural Language Inference in the Clinical Domain

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.752344Z

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Observation 6d01ff88-e681-47bf-afa1-1c5929237b8c · outbound

This paper cites Instruction Tuning With Loss Over Instructions.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Instruction Tuning With Loss Over Instructions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.756532Z

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Observation 427419b7-83bd-4d53-b60c-3292869875d5 · outbound

This paper cites Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Towards Greener LLMs: Bringing Energy-Efficiency to the Forefront of LLM Inference

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.760236Z

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Observation 68ed08ca-6355-4c80-b319-fb4a6ee67289 · outbound

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

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs A Simple and Effective Pruning Approach for Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.764087Z

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Observation 5c731372-b90e-4a39-abb0-645ba6acc1a6 · outbound

This paper cites Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.767904Z

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Observation 594f630d-fcc3-4e7d-a6d7-524449b19ec4 · outbound

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

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.771743Z

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Observation f4f178ba-9d3c-4cd1-83bd-e4acd5448f0e · outbound

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All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.570300Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f0dde0f9-d1da-4039-9442-fad864f0a71b · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.779369Z

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Observation f367fe39-b176-4c2b-91f3-8b6285a68126 · outbound

This paper cites Efficient Large Language Models: A Survey.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Efficient Large Language Models: A Survey

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.782840Z

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Observation 9551cab0-254d-45c4-af2b-2bac1d2e7678 · outbound

This paper cites InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.786438Z

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Observation 843a548b-0452-45c1-8534-b7771393c577 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.552744Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e5c9b38-b446-4b10-8099-640f51d7f2af · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.542394Z

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Observation 845cfa8f-c8de-456a-897c-1b35532c3dea · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.531706Z

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Observation 83e9cf2c-42e4-4833-aea6-9f22f4fbeae1 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.520559Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ee030299-06df-498a-a0fa-cb1f8474efc4 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.509748Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 38c11f8f-c024-4824-8556-9906d9c6ba7e · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.497789Z

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Observation 007519ed-e948-41df-bc45-59be154e448e · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.486122Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 84812da3-0fde-45c8-8409-794494107598 · outbound

This paper cites Decentralized Unsupervised Learning of Visual Representations.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Decentralized Unsupervised Learning of Visual Representations

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:17:56.970817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 972d6c36-d194-4285-a575-8e9bae01379d · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.474054Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6cb63d5b-86ee-40f3-9531-6f69f03e8588 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.463094Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b0fb088b-33c9-42a0-895d-7e90424f25e3 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.451714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 55b8f7e2-a70d-499d-81fd-e9660cb0f51e · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.440765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a6f2a0d2-813e-4e3e-9db9-84642c68707c · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.427710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ec1a0337-694e-41df-b196-081755840f5d · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.840266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a1918fc-8e77-4442-bd06-5dd353be74a5 · outbound

This paper cites Me LLaMA: Foundation Large Language Models for Medical Applications.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Me LLaMA: Foundation Large Language Models for Medical Applications

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.843858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e28f2532-787e-471c-95f7-31881f8f9748 · outbound

This paper cites When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.848531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8101fbc1-681a-4d21-a857-884d922595ce · outbound

This paper cites LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.852294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d0b60d6-6348-46fe-a089-b6b17270ee24 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.408687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c2a84c4f-14a3-489b-be15-6041bba1b0ea · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.397521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ec2cbba5-e095-4a16-8547-3db47f66d549 · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.386051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 31959962-6a31-4071-8b1a-b6c1bf7f08ae · outbound

This paper cites Fine-tuning Large Language Models for Domain-specific Machine Translation.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Fine-tuning Large Language Models for Domain-specific Machine Translation

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.869044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bda1745a-4b41-4103-a7f4-c1e8355b43fc · outbound

This paper cites an unresolved cited work.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:17:57.375382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 69d8a12b-4e14-4481-acb8-1336695b4934 · outbound

This paper cites TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.876510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b69eb500-fb4a-4b11-ac2f-e5208a58674e · outbound

This paper cites online" 'onlinestring :=.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs online" 'onlinestring :=

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.880801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2c9f6e7-4143-47d5-868d-4645b877299b · outbound

This paper cites write newline.

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs write newline

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T12:17:56.885258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation a68d6938-c538-4530-88c0-4d95d9b0da3a · inbound

Safe Screening Rules for Group SLOPE cites this paper.

Safe Screening Rules for Group SLOPE All-in-One Tuning and Structural Pruning for Domain-Specific LLMs

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T04:58:28.769663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.