Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2410.15595.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T12:41:20.729703Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T06:15:00.866473Z
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 519dfa99-5557-425f-8788-51f51b6b75ce · inbound
T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts cites this paper.
T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f028a299-d28d-459f-84e3-0fa6a25f4242 · inbound
A Systematic Examination of Preference Learning through the Lens of Instruction-Following cites this paper.
A Systematic Examination of Preference Learning through the Lens of Instruction-Following A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:41:20.729703Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d3620bb-1f7d-453e-98d8-255766d04571 · inbound
An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems cites this paper.
An Overview and Discussion on Using Large Language Models for Implementation Generation of Solutions to Open-Ended Problems A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 145
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:51:52.728580Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5245b116-1829-4987-b49d-f4d9e617ab9a · inbound
Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information cites this paper.
Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:32:56.533627Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34e2bed6-a7a6-4cbe-bce3-07af2c1df1bc · inbound
Optimal Transport-Based Token Weighting scheme for Enhanced Preference Optimization cites this paper.
Optimal Transport-Based Token Weighting scheme for Enhanced Preference Optimization A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:31:22.245835Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 771e57d2-c34f-4158-9bea-d118b007f221 · inbound
Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy cites this paper.
Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:24:23.510307Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e4f5b25-ea62-4f09-bbf0-0c4acd5eda14 · inbound
From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations cites this paper.
From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 53a7ab6b-16a0-4246-bd5b-83e320dda34c · inbound
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 98c858db-038a-4c6e-9a94-6d9fc951bdf2 · inbound
Active Causal Experimentalist (ACE): Learning Intervention Strategies via Direct Preference Optimization cites this paper.
Active Causal Experimentalist (ACE): Learning Intervention Strategies via Direct Preference Optimization A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 2015
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:26:01.675314Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3013383f-6f4a-4153-95b5-e41680157898 · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 106
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 72b588ce-8bf1-44d0-8e97-596c09337a06 · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 106
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 942de73f-1e2a-400a-883e-7b98baa62f04 · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 106
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 02f081b9-9386-4801-9343-faad5808d4b8 · inbound
Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion cites this paper.
Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5d75473b-9ac6-4a3d-b4b1-9e20570849a5 · inbound
Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion cites this paper.
Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bbb00dc8-427e-4690-98d6-7d2477d6ca53 · inbound
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 189
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 88539dbc-8626-4e97-ba06-9cded6ea9dac · inbound
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d2a656bc-9798-4349-a83e-5b4be92d3abf · inbound
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 6
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-30T22:25:06.439296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ab5e5094-07ec-4c79-9063-00f45ac2f4b2 · inbound
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 7
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-30T22:25:06.431552Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 97fe8aa6-09c7-463d-80d0-c2b16d2dc714 · inbound
Reliable Neural-Codec Text-to-Speech by ASR Self-Verification and Distillation: Near-Zero Catastrophic Failures Across Models and Codecs cites this paper.
Reliable Neural-Codec Text-to-Speech by ASR Self-Verification and Distillation: Near-Zero Catastrophic Failures Across Models and Codecs A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T23:19:02.875664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e86b1d7e-f9db-4e1d-b288-cefa5e6e7f8a · inbound
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 233
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T08:09:40.699362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 65e0b408-5a26-4e3f-ae87-b9879ef5963c · inbound
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design cites this paper.
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T10:59:18.707247Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.