Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2503.12854.
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 2026-08-03T06:30:56.289259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T23:33:49.468251Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T19:02:33.817155Z
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 e2d8a1c9-c418-4448-bdfa-652d2a27dfff · inbound
Sample-efficient LLM Optimization with Reset Replay cites this paper.
Sample-efficient LLM Optimization with Reset Replay Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T23:41:54.738087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 921189dd-55a7-47c7-8c07-88391aa3e3ff · inbound
TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework cites this paper.
TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:33:49.468251Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae29fb2c-7c16-4ba5-b2d9-2e85298977f4 · inbound
Your Self-Play Algorithm is Secretly an Adversarial Imitator: Understanding LLM Self-Play through the Lens of Imitation Learning cites this paper.
Your Self-Play Algorithm is Secretly an Adversarial Imitator: Understanding LLM Self-Play through the Lens of Imitation Learning Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:49:25.124148Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa1fc4f7-5128-4fc3-9ee6-e1f725596d84 · inbound
IRIS: Interpolative R\'enyi Iterative Self-play for Large Language Model Fine-Tuning cites this paper.
IRIS: Interpolative R\'enyi Iterative Self-play for Large Language Model Fine-Tuning Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:41:05.074027Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 41a09afb-bd6c-4ae4-bfab-0ba069dbc723 · inbound
LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models cites this paper.
LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 7
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:16:25.953549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation fd439143-50f9-432f-86e7-ec30bd916e06 · inbound
Confidence-Aware Alignment Makes Reasoning LLMs More Reliable cites this paper.
Confidence-Aware Alignment Makes Reasoning LLMs More Reliable Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:55:53.895403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 8c53353d-3041-44a5-9005-e0d8f5f1affb · inbound
How Much Online RL is Enough? Informative Rollouts for Offline Preference Optimization in RLVR cites this paper.
How Much Online RL is Enough? Informative Rollouts for Offline Preference Optimization in RLVR Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 13
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-21T06:24:00.555652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 173be850-c0a6-47df-9987-16f2e2589fb1 · 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 Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T03:45:17.528307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation a6ce62f4-2f0c-435d-9727-edc4d7977589 · inbound
Enhancing LLM Metacognition via Cognitive Pairwise Training cites this paper.
Enhancing LLM Metacognition via Cognitive Pairwise Training Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T19:02:33.820741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.