Paper Citation Record · LEDGER

How to Evaluate Reward Models for RLHF

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2410.14872.

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

pith.paper-citation-record.v1
2410.14872 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:33:53.358755Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T06:25:27.821937Z

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 1be5e7df-2b31-4e5b-af58-5138884f6000 · inbound

Qwen2.5 Technical Report cites this paper.

Qwen2.5 Technical Report How to Evaluate Reward Models for RLHF

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:25:27.824781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 245b1fac-f3ff-4cb2-bdb8-45ead85e4fab · inbound

Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators cites this paper.

Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators How to Evaluate Reward Models for RLHF

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:33:53.358755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9676dbaa-35e9-43c3-98e6-a78b00c7fb3e · inbound

On the Robustness of Reward Models for Language Model Alignment cites this paper.

On the Robustness of Reward Models for Language Model Alignment How to Evaluate Reward Models for RLHF

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T22:26:59.277720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246eac89-1703-458f-8d1c-c5afa4793d67 · inbound

WorldPM: Scaling Human Preference Modeling cites this paper.

WorldPM: Scaling Human Preference Modeling How to Evaluate Reward Models for RLHF

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:12:52.589817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32242d9b-6592-4ddc-8418-e2dfbe177a3e · inbound

RewardBench 2: Advancing Reward Model Evaluation cites this paper.

RewardBench 2: Advancing Reward Model Evaluation How to Evaluate Reward Models for RLHF

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T11:22:16.817153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 284e87a8-4613-42db-9312-a2f323338b5d · inbound

RewardAnything: Generalizable Principle-Following Reward Models cites this paper.

RewardAnything: Generalizable Principle-Following Reward Models How to Evaluate Reward Models for RLHF

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:06.769759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dafde6d9-7c3b-4dae-ac77-f8f20c1952cf · inbound

Bridging Offline and Online Reinforcement Learning for LLMs cites this paper.

Bridging Offline and Online Reinforcement Learning for LLMs How to Evaluate Reward Models for RLHF

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:05.645832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54c68ee6-2f9c-4abb-964f-6da8ef9c2e91 · inbound

Active Query Selection for Crowd-Based Reinforcement Learning cites this paper.

Active Query Selection for Crowd-Based Reinforcement Learning How to Evaluate Reward Models for RLHF

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T16:02:25.948964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03dbc1b8-32d0-41cb-8622-38e8d95efb1e · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data How to Evaluate Reward Models for RLHF

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:17.876896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 195b989d-6a45-47a2-9d0e-40a5a1bab2c3 · inbound

CompliBench: Benchmarking LLM Judges for Compliance Violation Detection in Dialogue Systems cites this paper.

CompliBench: Benchmarking LLM Judges for Compliance Violation Detection in Dialogue Systems How to Evaluate Reward Models for RLHF

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:26:02.353928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.