Paper Citation Record · LEDGER

Disentangling Length from Quality in Direct Preference Optimization

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2403.19159.

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

pith.paper-citation-record.v1
2403.19159 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:57:29.682556Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:40:07.153004Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cd80fb21-6efd-4b9a-b2a4-3b7ed043da32 · inbound

Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization cites this paper.

Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:05:46.916143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbf0c15e-e879-4f34-b07e-e854e4c04e5f · inbound

MPO: Multilingual Safety Alignment via Reward Gap Optimization cites this paper.

MPO: Multilingual Safety Alignment via Reward Gap Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:57:29.682556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a76c2dc1-1aba-4b8a-88f1-67ae4cc22924 · inbound

MidPO: Dual Preference Optimization for Safety and Helpfulness in Large Language Models via a Mixture of Experts Framework cites this paper.

MidPO: Dual Preference Optimization for Safety and Helpfulness in Large Language Models via a Mixture of Experts Framework Disentangling Length from Quality in Direct Preference Optimization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T11:29:01.345378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef4479f0-cb24-4db8-a1dd-270a815a3ae6 · inbound

Aligning Large Language Models with Implicit Preferences from User-Generated Content cites this paper.

Aligning Large Language Models with Implicit Preferences from User-Generated Content Disentangling Length from Quality in Direct Preference Optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:52.110646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7faebdb5-bce8-4568-9819-96e8c32d9373 · inbound

Unlocking Recursive Thinking of LLMs: Alignment via Refinement cites this paper.

Unlocking Recursive Thinking of LLMs: Alignment via Refinement Disentangling Length from Quality in Direct Preference Optimization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T06:07:02.051648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2444c89a-c34f-44c2-a429-af7a17a9eb79 · inbound

Explicit Preference Optimization: No Need for an Implicit Reward Model cites this paper.

Explicit Preference Optimization: No Need for an Implicit Reward Model Disentangling Length from Quality in Direct Preference Optimization

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:40:17.966403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51e5e0f4-f6c6-48d5-9ce1-3c8eade8b949 · inbound

ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization cites this paper.

ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:14:44.113845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 561a7e33-73f4-4e69-9cfa-a42e91b4fffd · inbound

Bridging Offline and Online Reinforcement Learning for LLMs cites this paper.

Bridging Offline and Online Reinforcement Learning for LLMs Disentangling Length from Quality in Direct Preference Optimization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.964261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc58b32c-1150-498e-97fb-8a1730d2472d · inbound

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap cites this paper.

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap Disentangling Length from Quality in Direct Preference Optimization

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:50:47.708523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3cc6d8ee-4de4-4718-ae7a-cdf3005b8489 · inbound

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints cites this paper.

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints Disentangling Length from Quality in Direct Preference Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T21:33:14.576084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a85e76b-341b-4052-832a-3d4680e1b659 · inbound

Multiplayer Nash Preference Optimization cites this paper.

Multiplayer Nash Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:11:24.001156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f71c7d4f-3a4f-42b5-899e-613e0bf4b900 · inbound

Factored Causal Representation Learning for Robust Reward Modeling in RLHF cites this paper.

Factored Causal Representation Learning for Robust Reward Modeling in RLHF Disentangling Length from Quality in Direct Preference Optimization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-21T14:20:13.569063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 89d6fd95-903d-42a4-a73f-dbddd0e393f0 · inbound

AlignCultura: Towards Culturally Aligned Large Language Models? cites this paper.

AlignCultura: Towards Culturally Aligned Large Language Models? Disentangling Length from Quality in Direct Preference Optimization

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:56:05.154961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2a2d5ec-c627-4f8c-985f-2ce357cd246b · inbound

Gradient-Gated DPO: Stabilizing Preference Optimization in Language Models cites this paper.

Gradient-Gated DPO: Stabilizing Preference Optimization in Language Models Disentangling Length from Quality in Direct Preference Optimization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:20:41.700043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ae7dc73-eaa8-434b-82b5-c44ced77521b · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:56:05.480733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dcb49329-1564-43f4-98c1-f57db2b90c7f · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:21:26.487774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2910cfc1-58e0-4fb9-9087-1b443aeb8bef · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T07:12:28.831414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 12a70180-3549-4dcf-8df7-01cb3c4ee7cb · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization Disentangling Length from Quality in Direct Preference Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T14:53:24.400757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7777d650-97ff-4cb3-bdd2-66774e0b157d · inbound

Response Time Enhances Alignment with Heterogeneous Preferences cites this paper.

Response Time Enhances Alignment with Heterogeneous Preferences Disentangling Length from Quality in Direct Preference Optimization

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:45:59.553809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation abd32b47-9cb9-46ea-8461-5683afdb32b6 · inbound

Reinforcement Learning for Scalable and Trustworthy Intelligent Systems cites this paper.

Reinforcement Learning for Scalable and Trustworthy Intelligent Systems Disentangling Length from Quality in Direct Preference Optimization

Reference 101

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:51:38.226241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4915950a-6e37-4019-b487-ba51da449163 · inbound

Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training cites this paper.

Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training Disentangling Length from Quality in Direct Preference Optimization

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T06:32:24.288800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 228e011e-8d83-4c58-a34d-0abd2e02fe4e · inbound

AdaDPO: Self-Adaptive Direct Preference Optimization with Balanced Gradient Updates cites this paper.

AdaDPO: Self-Adaptive Direct Preference Optimization with Balanced Gradient Updates Disentangling Length from Quality in Direct Preference Optimization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:33:24.381122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e6b289a2-75ca-4e9f-b630-5d3ef85d82b5 · inbound

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation cites this paper.

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation Disentangling Length from Quality in Direct Preference Optimization

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:40:07.154736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d9a76b1-c24c-4b06-8528-4ab91745e03a · inbound

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation cites this paper.

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation Disentangling Length from Quality in Direct Preference Optimization

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:35:39.562457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67241da9-311f-417b-a35d-b930d892e7e1 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Disentangling Length from Quality in Direct Preference Optimization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-11T13:53:36.775836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9477601-761a-464d-ba86-7f81ed5390dd · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Disentangling Length from Quality in Direct Preference Optimization

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T08:40:35.672115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f75957c-fcb7-430b-ad0a-edbae361afb7 · inbound

Test-Time Scaling via Error Localization cites this paper.

Test-Time Scaling via Error Localization Disentangling Length from Quality in Direct Preference Optimization

Reference 183

Resolution: unresolved; no resolver link, observed 2026-08-01T07:28:36.689869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.