Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Optimal Design for Reward Modeling in RLHF
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2410.17055.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:52:07.047257Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T01:09:19.289406Z
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 bbf0ea32-ac3b-4a49-a023-863327bcc65f · inbound
Selective Reviews of Bandit Problems in AI via a Statistical View cites this paper.
Selective Reviews of Bandit Problems in AI via a Statistical View Optimal Design for Reward Modeling in RLHF
Reference 114
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:49:45.616529Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8200673f-888a-4bb2-83bf-38d5e3a7f425 · 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 Optimal Design for Reward Modeling in RLHF
Reference 118
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:51:52.606552Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31a84014-6480-4388-aaaa-8d299a07ea28 · inbound
PILAF: Optimal Human Preference Sampling for Reward Modeling cites this paper.
PILAF: Optimal Human Preference Sampling for Reward Modeling Optimal Design for Reward Modeling in RLHF
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:03:53.198647Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ecd1b06-ec90-4b65-b23f-5ce5c1ffac1a · inbound
A Survey on Progress in LLM Alignment from the Perspective of Reward Design cites this paper.
A Survey on Progress in LLM Alignment from the Perspective of Reward Design Optimal Design for Reward Modeling in RLHF
Reference 125
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:52:07.047257Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c58e1577-1621-4ef2-9eb0-c87452a42a56 · inbound
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain cites this paper.
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain Optimal Design for Reward Modeling in RLHF
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:33:54.491558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c3994666-13af-4383-80f3-607b41a01877 · inbound
Eliciting Truthful Feedback for Preference-Based Learning via the VCG Mechanism cites this paper.
Eliciting Truthful Feedback for Preference-Based Learning via the VCG Mechanism Optimal Design for Reward Modeling in RLHF
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T09:12:22.082616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4192b025-d1c3-4f6d-8276-58b6253b1bc3 · inbound
Reinforcement Learning from Human Feedback: A Statistical Perspective cites this paper.
Reinforcement Learning from Human Feedback: A Statistical Perspective Optimal Design for Reward Modeling in RLHF
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:13:13.666333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6e9067c7-4567-4bfe-ae86-6977d6cac3c2 · inbound
Goal-Conditioned Supervised Learning for LLM Fine-Tuning cites this paper.
Goal-Conditioned Supervised Learning for LLM Fine-Tuning Optimal Design for Reward Modeling in RLHF
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:39:10.107245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation eb3e82c5-b9af-46c4-9e5c-052b03094655 · inbound
How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis cites this paper.
How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis Optimal Design for Reward Modeling in RLHF
Reference 27
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T12:04:38.765753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation efda342b-a451-4167-9d3d-ef5f417e3c6b · inbound
Which Pairs to Compare for LLM Post-Training? cites this paper.
Which Pairs to Compare for LLM Post-Training? Optimal Design for Reward Modeling in RLHF
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T01:09:19.293176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.