Paper Citation Record · LEDGER

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 34 inbound Pith citation observations for arXiv:2402.17193.

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

pith.paper-citation-record.v1
2402.17193 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 34 of 34 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:40:02.212661Z

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
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External citation measurements

28
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 fc439722-f989-49bc-ac60-f821482c395a · inbound

OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones? cites this paper.

OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones? When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T04:40:02.212661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4deda63a-2504-47eb-b4ac-31f8b8f0b4bd · inbound

Political-LLM: Large Language Models in Political Science cites this paper.

Political-LLM: Large Language Models in Political Science When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 212

Resolution: unresolved; no resolver link, observed 2026-08-11T19:52:04.709432Z

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

All-in-One Tuning and Structural Pruning for Domain-Specific LLMs cites this paper.

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 19cd457d-ea9d-4d08-be66-a3eb4c070df3 · inbound

The Scaling Law for LoRA Base on Mutual Information Upper Bound cites this paper.

The Scaling Law for LoRA Base on Mutual Information Upper Bound When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T21:58:52.619058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8e020f0-331e-440f-8dba-ddacd42d4c06 · inbound

Fun-tuning: Characterizing the Vulnerability of Proprietary LLMs to Optimization-based Prompt Injection Attacks via the Fine-Tuning Interface cites this paper.

Fun-tuning: Characterizing the Vulnerability of Proprietary LLMs to Optimization-based Prompt Injection Attacks via the Fine-Tuning Interface When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:46.775775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f84d06a-b3ae-490e-b5f9-7b1fbebefa3d · inbound

Trust at Your Own Peril: A Mixed Methods Exploration of the Ability of Large Language Models to Generate Expert-Like Systems Engineering Artifacts and a Characterization of Failure Modes cites this paper.

Trust at Your Own Peril: A Mixed Methods Exploration of the Ability of Large Language Models to Generate Expert-Like Systems Engineering Artifacts and a Characterization of Failure Modes When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-07T21:21:31.626024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96678b31-7f61-47ec-836f-8d7a661f6b12 · inbound

Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments cites this paper.

Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:11:49.688072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eb936d18-b3e8-45db-b6e0-b3f147d79c15 · inbound

Can Past Experience Accelerate LLM Reasoning? cites this paper.

Can Past Experience Accelerate LLM Reasoning? When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:59.151322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b00469a-94eb-41f4-85f0-20990a9834f4 · inbound

Rethinking the Understanding Ability across LLMs through Mutual Information cites this paper.

Rethinking the Understanding Ability across LLMs through Mutual Information When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:21:38.805940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7010431b-99de-49de-b0f4-33e42bccc211 · inbound

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training cites this paper.

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:30.128496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ae00e73-c389-42c5-bcd6-bf017a90b608 · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 115

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:55.846119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d9beb9d-d86f-4265-902d-382070cf6e09 · inbound

Gradients: When Markets Meet Fine-tuning -- A Distributed Approach to Model Optimisation cites this paper.

Gradients: When Markets Meet Fine-tuning -- A Distributed Approach to Model Optimisation When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:27:33.435879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a4aae37-78b6-4252-b9ca-173ed32a0b5f · inbound

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation cites this paper.

A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.544087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 876146e2-2f24-4fdf-8937-203e3db08918 · inbound

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 246

Resolution: unresolved; no resolver link, observed 2026-08-07T00:40:36.690386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c951fbed-399d-4aea-9353-023fb92de5e1 · inbound

Collaborative Editable Model cites this paper.

Collaborative Editable Model When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:24:12.965494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0caa0043-5f84-482e-b6ae-cc4d4164c229 · inbound

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation cites this paper.

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:40:25.565467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29f86ffd-cb2c-43b0-badf-3f835637a52e · inbound

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora cites this paper.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:44:00.581983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f94e2fab-c2ad-48f9-94ec-1794aed310c2 · inbound

Training language models to be warm and empathetic makes them less reliable and more sycophantic cites this paper.

Training language models to be warm and empathetic makes them less reliable and more sycophantic When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T12:18:39.305805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d497f33-5882-4898-a173-b1973938d212 · inbound

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward cites this paper.

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T19:21:54.052630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f2c420c-3731-4453-acf6-e1ad4a8fa0fe · inbound

Scaling behavior of large language models in emotional safety classification across sizes and tasks cites this paper.

Scaling behavior of large language models in emotional safety classification across sizes and tasks When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:23.698181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 273a9bd2-18d5-4fb3-881d-65896d093983 · inbound

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View cites this paper.

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T13:46:16.378471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 684a0b87-1f6b-484e-b0cf-109664cb90b1 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 212

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T00:31:24.761092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0c3f770d-e2a9-4d52-9c99-4da5c185d371 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 212

Resolution: unresolved; no resolver link, observed 2026-08-03T18:19:30.200157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03428e5c-038a-483a-819f-a5e9c5e8a868 · inbound

Sustainable Code Generation Using Large Language Models: A Systematic Literature Review cites this paper.

Sustainable Code Generation Using Large Language Models: A Systematic Literature Review When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T18:50:16.541781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 22144df3-e8fd-4fe4-87ad-d9e600eb5019 · inbound

Cross-Lingual Transfer and Parameter-Efficient Adaptation in the Turkic Language Family: A Theoretical Framework for Low-Resource Language Models cites this paper.

Cross-Lingual Transfer and Parameter-Efficient Adaptation in the Turkic Language Family: A Theoretical Framework for Low-Resource Language Models When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:09:57.864007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 57fdf641-9e70-4ef6-af82-bcf1f6898954 · inbound

Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation cites this paper.

Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T10:44:37.961327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 54106b31-3a65-4f25-9807-760488a0d7ed · inbound

Rectification Difficulty and Optimal Sample Allocation in LLM-Augmented Surveys cites this paper.

Rectification Difficulty and Optimal Sample Allocation in LLM-Augmented Surveys When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:41:36.670394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 89ec2e04-7f40-42f3-90e3-ea99147d3eeb · inbound

TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications cites this paper.

TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:06:18.870039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 65eec70c-7920-4546-ba76-ac031f6ac6f4 · inbound

Learning from Less: Measuring the Effectiveness of RLVR in Low Data and Compute Regimes cites this paper.

Learning from Less: Measuring the Effectiveness of RLVR in Low Data and Compute Regimes When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:10:09.622862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b6b8785f-2467-4613-8957-8c38e5a410db · inbound

Clinically Interpretable Sepsis Early Warning via LLM-Guided Simulation of Temporal Physiological Dynamics cites this paper.

Clinically Interpretable Sepsis Early Warning via LLM-Guided Simulation of Temporal Physiological Dynamics When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T01:20:37.231815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 455e431d-c49b-4bb3-8c8a-4c6c6675fd0e · inbound

Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning cites this paper.

Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T06:09:41.202991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation db3b11df-0022-416b-bd59-f64784d43b2b · inbound

When Top-1 Fails: Calibrating LoRA Monitors for Masked Diffusion LMs cites this paper.

When Top-1 Fails: Calibrating LoRA Monitors for Masked Diffusion LMs When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:19:56.325146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 10f96673-d50f-449a-9585-0b9a6916c0a4 · inbound

On the Vulnerability of Parameter-Level Defenses to Model Merging cites this paper.

On the Vulnerability of Parameter-Level Defenses to Model Merging When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:24:22.508587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a6b17bc3-4a2c-486d-8ad8-8cf713f0d35a · inbound

TacReasoner: A Dynamic Tactile-Language Framework for Interactive Reasoning in Real-World Scenarios cites this paper.

TacReasoner: A Dynamic Tactile-Language Framework for Interactive Reasoning in Real-World Scenarios When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-11T08:20:49.438388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.