Paper Citation Record · LEDGER

Preserving Diversity in Supervised Fine-Tuning of Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2408.16673.

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

pith.paper-citation-record.v1
2408.16673 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:54:49.789457Z

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

4
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 d7489688-7b8b-40ac-a258-ad77e3a60e29 · inbound

Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections cites this paper.

Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:54:49.789457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc92661-9452-4ddb-8023-0ea1e05792dd · inbound

Proximal Supervised Fine-Tuning cites this paper.

Proximal Supervised Fine-Tuning Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:42:50.911875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dd60545a-13ec-499a-b286-b236fd2f3ecf · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 231

Resolution: verified exact; arxiv_id, observed 2026-05-17T15:14:26.291241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a94e5761-366d-49d5-a994-e8ec1e812a07 · inbound

Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models cites this paper.

Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:28:13.692784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a4fba0c-935c-4824-9fa9-82de6c5492c5 · inbound

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification cites this paper.

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T12:50:25.797475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 369dbe8c-c147-46d5-bf26-054e0bd7f0a2 · inbound

Diversity in Large Language Models under Supervised Fine-Tuning cites this paper.

Diversity in Large Language Models under Supervised Fine-Tuning Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-09T20:37:32.121081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 17b506e7-58dc-4c97-ba94-70978163dd18 · inbound

Diversity in Large Language Models under Supervised Fine-Tuning cites this paper.

Diversity in Large Language Models under Supervised Fine-Tuning Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:11:18.202035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 577db776-cf3a-43ff-9d93-f3984d75868c · inbound

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context cites this paper.

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:20:57.870044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 61f1b2a5-2580-4c7e-8f03-af428296c6a0 · inbound

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context cites this paper.

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:57:31.532861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cbcddc21-6c03-4b60-9fd0-4b03b4ddcf26 · inbound

Annotations Mitigate Post-Training Mode Collapse cites this paper.

Annotations Mitigate Post-Training Mode Collapse Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:46:51.299112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 99ceac8e-cbba-46fd-b818-31b079f9a72a · inbound

Selective Off-Policy Reference Tuning with Plan Guidance cites this paper.

Selective Off-Policy Reference Tuning with Plan Guidance Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:47:05.228838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c860045c-631d-467a-b615-9ad8d4f6e97f · inbound

Selective Off-Policy Reference Tuning with Plan Guidance cites this paper.

Selective Off-Policy Reference Tuning with Plan Guidance Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:22:59.388253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 95274453-4a93-425c-9b30-dc2bd42e0e77 · inbound

RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting cites this paper.

RAFT: Data Refinement and Adaptive Distillation for Domain Fine-Tuning with Alleviated Forgetting Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T00:02:49.588763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 692e0b15-8492-4b6d-b3d7-e111f4107020 · inbound

BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning cites this paper.

BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:04:28.497310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f85fdf8e-bbee-47d3-9028-4bcd64ee1471 · inbound

When Reasoning Narrows the Move: Diversity Collapse in LLM Game Play cites this paper.

When Reasoning Narrows the Move: Diversity Collapse in LLM Game Play Preserving Diversity in Supervised Fine-Tuning of Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-01T12:36:11.617634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.