Paper Citation Record · LEDGER

Provably Robust DPO: Aligning Language Models with Noisy Feedback

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2403.00409.

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

pith.paper-citation-record.v1
2403.00409 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:03:47.464904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T11:09:46.406911Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 2a42b6b5-f3ad-4eb1-96b3-e897de916829 · inbound

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization cites this paper.

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:16:17.252104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c4164c7-dd8d-4467-a398-af8bbeda1ebf · inbound

How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators cites this paper.

How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:57:29.679899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6e9ef6e6-ad4d-4ddd-ac35-445bbf735d62 · inbound

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment cites this paper.

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T18:23:49.795434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f6217b9-2b21-4366-b350-b0d52c2f1c40 · inbound

A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO cites this paper.

A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:19:08.819245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55493028-8900-4233-ab07-3174d5ea4748 · inbound

Incentivizing High-Quality Human Annotations with Golden Questions cites this paper.

Incentivizing High-Quality Human Annotations with Golden Questions Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T13:42:19.320740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c07e7b14-0763-4b65-88e6-5d97b0cb27d7 · inbound

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment cites this paper.

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T13:44:56.673138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18383f47-ebb8-49be-82e0-db1deea0be98 · inbound

On Symmetric Losses for Robust Policy Optimization with Noisy Preferences cites this paper.

On Symmetric Losses for Robust Policy Optimization with Noisy Preferences Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:27:53.423556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e72950c1-3456-4bd4-8789-0c0fb597fb4a · inbound

A Technical Survey of Reinforcement Learning Techniques for Large Language Models cites this paper.

A Technical Survey of Reinforcement Learning Techniques for Large Language Models Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T19:59:31.844690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 879ddf9d-ee39-4e6d-bd23-4b8d4c93c977 · inbound

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates cites this paper.

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:01:34.180564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a0f62a07-09a5-43fe-8a7f-b05f5f17f77f · inbound

Margin Adaptive DPO: Leveraging Reward Model for Granular Control in Preference Optimization cites this paper.

Margin Adaptive DPO: Leveraging Reward Model for Granular Control in Preference Optimization Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T11:27:22.570045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1db7cef-8d31-405d-91c7-233f62db05e9 · inbound

Users as Annotators: LLM Preference Learning from Comparison Mode cites this paper.

Users as Annotators: LLM Preference Learning from Comparison Mode Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-18T08:21:06.992814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1f275270-dd03-4b92-9031-d2d2159fd45e · inbound

Multilingual Safety Alignment via Self-Distillation cites this paper.

Multilingual Safety Alignment via Self-Distillation Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T05:45:22.410770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 10a79da6-4279-4b68-9ab8-028dec443f34 · inbound

Multilingual Safety Alignment via Self-Distillation cites this paper.

Multilingual Safety Alignment via Self-Distillation Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 45

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:41:00.754016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59f00d15-ee8a-4cfe-8867-7658461bc1a0 · 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 Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T06:32:24.273715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a29d9f3b-da26-431f-b3c0-00d7387e32e4 · inbound

TPMM-DPO: Trajectory-aware Preference-guided Model Merging for Iterative Direct Preference Optimization cites this paper.

TPMM-DPO: Trajectory-aware Preference-guided Model Merging for Iterative Direct Preference Optimization Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-25T03:45:17.586731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66a041cc-61ca-4ecb-90bd-fc72154bdac8 · inbound

Which Pairs to Compare for LLM Post-Training? cites this paper.

Which Pairs to Compare for LLM Post-Training? Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T01:09:19.254368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d736ac7-41f0-4a83-9703-22e57c8659ea · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 190

Resolution: verified exact; arxiv_id, observed 2026-07-04T11:09:46.408648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 23266883-97f4-4d2f-8f72-348a70fd816d · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 190

Resolution: unresolved; no resolver link, observed 2026-08-02T10:27:18.410065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f903dc6c-5203-4d51-8355-c19cb17ee593 · inbound

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels cites this paper.

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T15:37:01.391649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b17ee32-4086-4ec1-9545-b8151cf549fd · inbound

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels cites this paper.

Metadata-Free Meta-Reweighted Direct Preference Optimization under Noisy Preference Labels Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T08:00:53.937134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bff2af43-1386-4c93-8032-bc0d540df63a · inbound

Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation cites this paper.

Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation Provably Robust DPO: Aligning Language Models with Noisy Feedback

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T15:03:47.464904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.