Paper Citation Record · LEDGER

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2502.04357.

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

pith.paper-citation-record.v1
2502.04357 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:32:47.980568Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy1
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ec1d8ef-30e2-4d74-a1e8-a9787bb5b65f · outbound

This paper cites Scalable Ensembling For Mitigating Reward Overoptimisation.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Scalable Ensembling For Mitigating Reward Overoptimisation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.815161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a45fd102-318c-4a34-ac81-ab1bff7d3bb1 · outbound

This paper cites RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.848862Z

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Observation 740ba855-2b7f-4785-8f0a-a938e5a28e0b · outbound

This paper cites RLHF Workflow: From Reward Modeling to Online RLHF.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs RLHF Workflow: From Reward Modeling to Online RLHF

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.854763Z

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Observation 63b25d2b-3b20-4b58-be64-a4dc1fdbd324 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Universal Language Model Fine-tuning for Text Classification

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.870940Z

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Observation 8dc45675-9d25-4c49-be35-f7f3e5710963 · outbound

This paper cites LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.892435Z

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Observation d8610c8a-67c7-4f11-894a-7304a70c704c · outbound

This paper cites Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.897367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93c01cb5-4458-43ae-9a23-55364f6abbff · outbound

This paper cites Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.903311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5469c96b-8161-467c-ab2f-18e5acfa753a · outbound

This paper cites Generative Reward Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Generative Reward Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.909420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d6b8332-5e9b-4309-bc3c-b8e45aa4390d · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Efficient Estimation of Word Representations in Vector Space

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.914729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 535875a3-e053-4e8f-8882-9686a245d96a · outbound

This paper cites Active Preference Learning for Large Language Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Active Preference Learning for Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.920478Z

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Unavailable: canonical work link unavailable.

Observation eb2610df-38d2-44ef-95a4-26cf73d61a6f · outbound

This paper cites an unresolved cited work.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:32:48.521803Z

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 0376cf34-9ce7-4b62-a313-8f94310bd832 · outbound

This paper cites Rethinking Bradley-Terry Models in Preference-Based Reward Modeling: Foundations, Theory, and Alternatives.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Rethinking Bradley-Terry Models in Preference-Based Reward Modeling: Foundations, Theory, and Alternatives

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.943542Z

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Unavailable: canonical work link unavailable.

Observation d499de53-74e5-4414-9332-c343e3d29346 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.948743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff9dfb75-04a8-4166-a8ae-d6d1ef3c2093 · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs WaveNet: A Generative Model for Raw Audio

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.954111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5842996-e851-443c-bc8d-630bf3aa9e5c · outbound

This paper cites Secrets of RLHF in Large Language Models Part II: Reward Modeling.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Secrets of RLHF in Large Language Models Part II: Reward Modeling

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.959132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d3c12fb-96dc-4564-94f4-9bdabdee110e · outbound

This paper cites Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.964012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 092df6bd-e88b-4aae-885b-4a2b3ff2ef0a · outbound

This paper cites Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.969450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0de104c-e2b0-423f-8b48-3982a8e8f688 · outbound

This paper cites Generative Verifiers: Reward Modeling as Next-Token Prediction.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Generative Verifiers: Reward Modeling as Next-Token Prediction

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.975340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45a48ba9-d9d9-43f3-b378-08ce8b1b1ee4 · outbound

This paper cites Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.980568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e238bb2b-38b7-4b13-ba6f-0de4e32cb726 · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.826867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da49c087-30ab-44db-a2ae-fcca4e1ecc80 · outbound

This paper cites Red Teaming Language Models with Language Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Red Teaming Language Models with Language Models

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.937569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d98f3d92-adc3-4ff9-ade5-ae8b43c7dd97 · outbound

This paper cites Mitigating the alignment tax of rlhf.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Mitigating the alignment tax of rlhf

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:32:48.540662Z

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 93890cd6-f7ca-4de8-91e6-db57fbf7eceb · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.865198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5258d64d-76db-48d4-accb-5a59a590a8eb · outbound

This paper cites Reward Model Ensembles Help Mitigate Overoptimization.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Reward Model Ensembles Help Mitigate Overoptimization

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.837706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84a95113-7295-4417-9801-6b5db597809e · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs LoRA: Low-Rank Adaptation of Large Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.876159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8910208e-b3f3-44f8-a999-9658650905ba · outbound

This paper cites OpenAI o1 System Card.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs OpenAI o1 System Card

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.881802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7daa53e-fbc0-42f7-9b19-acbe282a8b69 · outbound

This paper cites Universal Sentence Encoder.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Universal Sentence Encoder

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.832124Z

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Observation 5702f126-caa3-4064-9d95-00667a1ce62f · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.821353Z

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Observation 54600f9e-9665-49c2-8dac-a1a8bb733340 · outbound

This paper cites OffsetBias: Leveraging Debiased Data for Tuning Evaluators.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs OffsetBias: Leveraging Debiased Data for Tuning Evaluators

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.926599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 911ebb87-91d6-44e2-b8eb-35204a5ed526 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.843461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e101d40-dd11-4c11-b33c-761b28fc3665 · outbound

This paper cites The Llama 3 Herd of Models.

Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs The Llama 3 Herd of Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T11:32:47.859773Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.