Paper Citation Record · LEDGER

Enhancing LLM Safety via Constrained Direct Preference Optimization

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2403.02475.

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

pith.paper-citation-record.v1
2403.02475 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:30:16.012101Z

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

0
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 e3322188-3172-48ef-b84e-540124df4156 · inbound

Jailbreak Attacks and Defenses Against Large Language Models: A Survey cites this paper.

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:20:44.762062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f1d5073-9f8a-45ce-be38-8a0bd2e8880e · inbound

Learning Safety Constraints for Large Language Models cites this paper.

Learning Safety Constraints for Large Language Models Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:30:16.012101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 094a5a8d-af98-4b91-83a0-bad6ed9f6a95 · inbound

Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints cites this paper.

Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:21:58.706600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1939382-08e1-4005-bcf6-ae0c11ce47c8 · inbound

The Geometry of Harmfulness in LLMs through Subconcept Probing cites this paper.

The Geometry of Harmfulness in LLMs through Subconcept Probing Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T15:01:47.808584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4424de3d-0056-46e5-a14a-8c910b95c668 · inbound

Enhancing Speech Large Language Models through Reinforced Behavior Alignment cites this paper.

Enhancing Speech Large Language Models through Reinforced Behavior Alignment Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:24:23.468405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 964885b8-7802-4657-802f-425b10c0d969 · inbound

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation cites this paper.

FlashEvaluator: Expanding Search Space with Parallel Sequence-Level Evaluation Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T19:23:43.246430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18defa3c-fc79-471c-a584-7aee7dcfa815 · inbound

MGDA-Decoupled: Geometry-Aware Multi-Objective Optimisation for DPO-based LLM Alignment cites this paper.

MGDA-Decoupled: Geometry-Aware Multi-Objective Optimisation for DPO-based LLM Alignment Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-10T01:40:55.342322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9416754a-97e6-429e-a76f-6904dcf0ae8a · inbound

Scalable First-Order Interior Point Trust Region Algorithms for Linearly Constrained Optimization cites this paper.

Scalable First-Order Interior Point Trust Region Algorithms for Linearly Constrained Optimization Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:06:22.066349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5e38fd8-be65-4be7-a4e7-ea14c221efc2 · inbound

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces cites this paper.

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:46:54.874567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 85cbb6ca-3aa2-4830-b59b-5f800a6df652 · inbound

Safe Inference-Time Alignment via Lagrangian Reward Augmentation cites this paper.

Safe Inference-Time Alignment via Lagrangian Reward Augmentation Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 104

Resolution: unresolved; no resolver link, observed 2026-07-12T07:05:47.150308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad6ebef-9d33-4b6d-b1cb-bb49ba592132 · inbound

Every Sample Counts: Supervised Fine-Tuning of Language Models with Pointwise Constraints cites this paper.

Every Sample Counts: Supervised Fine-Tuning of Language Models with Pointwise Constraints Enhancing LLM Safety via Constrained Direct Preference Optimization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T05:26:06.829382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.