Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
$\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2407.08639.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T23:02:23.432721Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T07:12:28.794227Z
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 ef134bbb-3b20-4cc5-98f7-5003f38a2c54 · inbound
R.I.P.: Better Models by Survival of the Fittest Prompts cites this paper.
R.I.P.: Better Models by Survival of the Fittest Prompts $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T23:02:23.432721Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d6b33bf-3fec-43d2-9bf1-692c3fee2721 · inbound
Refining Alignment Framework for Diffusion Models with Intermediate-Step Preference Ranking cites this paper.
Refining Alignment Framework for Diffusion Models with Intermediate-Step Preference Ranking $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T18:55:14.737534Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a3e7e6a-baa7-4362-8964-7cf7b57cd679 · inbound
LongDPO: Unlock Better Long-form Generation Abilities for LLMs via Critique-augmented Stepwise Information cites this paper.
LongDPO: Unlock Better Long-form Generation Abilities for LLMs via Critique-augmented Stepwise Information $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T13:25:52.097604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8882991-f408-49fa-a646-9d5517477e26 · inbound
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment cites this paper.
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T18:23:50.415535Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34d1da5e-9660-4de1-8f71-242207ba596a · inbound
Adaptive Margin RLHF via Preference over Preferences cites this paper.
Adaptive Margin RLHF via Preference over Preferences $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T14:52:23.688099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43b0d0fb-1411-4b10-97f6-3786b9ae1168 · 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 $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:56:05.455019Z
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 4f9bf3a9-0d75-4e9b-a1fc-cd3af649db25 · 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 $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:21:26.495774Z
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 7ab647a7-099c-4336-85f5-f71521799a71 · 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 $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T07:12:28.796709Z
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 d0c9cb75-268b-48a9-baaf-601c0a28d473 · 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 $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T14:53:22.786099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.