Paper Citation Record · LEDGER

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment

As of 10 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 3 inbound Pith citation observations for arXiv:2502.00203.

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

pith.paper-citation-record.v1
2502.00203 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:56:28.769248Z

measured 28 of 28 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-23T03:50:03.720389Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:52:29.440835Z

Reference resolution

25 of 25 outbound references displayed

verified exact0
verified fuzzy2
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69e45135-5d22-49a7-bf09-00d5fa0e46f6 · outbound

This paper cites Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.697231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3627262-c55a-41e9-b908-abca547f4dd9 · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.710631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e749a7b-8e54-4a70-b955-848fab332b7b · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment KTO: Model Alignment as Prospect Theoretic Optimization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.713883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3f408ca-681e-4cd4-8491-8de269854632 · outbound

This paper cites Robust Preference Optimization through Reward Model Distillation.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Robust Preference Optimization through Reward Model Distillation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.717046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ab1b5b4-5906-4666-9f96-4d2cedd5778c · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Measuring Massive Multitask Language Understanding

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.725883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20a1f14d-6478-4baf-afa2-647e70f491c5 · outbound

This paper cites RewardBench: Evaluating Reward Models for Language Modeling.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment RewardBench: Evaluating Reward Models for Language Modeling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.732083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e3f52cc-106b-49cc-a082-07622696c53c · outbound

This paper cites On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.735011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ddadaa7-79ca-4955-90c9-4269033b9fd9 · outbound

This paper cites Understanding Reference Policies in Direct Preference Optimization.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Understanding Reference Policies in Direct Preference Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.738108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27b6e860-e0be-41eb-967f-f367df79c73a · outbound

This paper cites SimPO: Simple Preference Optimization with a Reference-Free Reward.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment SimPO: Simple Preference Optimization with a Reference-Free Reward

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.740814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5fae76-ad93-4da6-9fe2-5c56c71041ef · outbound

This paper cites The Llama 3 Herd of Models.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment The Llama 3 Herd of Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.743682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c0fcfeb-f141-4e29-a27c-39268687e145 · outbound

This paper cites Nemotron-4 340B Technical Report.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Nemotron-4 340B Technical Report

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.746367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 384bfe6f-d557-4d0b-9b7d-d8d4b5c0f8af · outbound

This paper cites GPT-4 Technical Report.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment GPT-4 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.749374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94b9be56-243b-4c62-9fa7-7ebc6fdeee8b · outbound

This paper cites BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.752139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc797453-adac-4bdb-ab5e-8508b2d32668 · outbound

This paper cites Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.755116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 782e18f3-73c0-4f7e-9288-22e51973d69b · outbound

This paper cites Proximal Policy Optimization Algorithms.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Proximal Policy Optimization Algorithms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.758042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e702691-ad86-4d0c-9497-413ef50c3867 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.760860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12010ffa-1fd9-42e5-addc-0cff30feee9b · outbound

This paper cites UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.763679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9207d0b3-f7ff-4bed-bf8f-158b6cd46bd3 · outbound

This paper cites Derivation of the distance functions for the multi-response scenario Squared Distance with Leave-One-Out (sqloo).

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Derivation of the distance functions for the multi-response scenario Squared Distance with Leave-One-Out (sqloo)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:56:28.934595Z

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 a69ea086-f250-4866-94bb-414bd814c046 · outbound

This paper cites WPO: Enhancing RLHF with Weighted Preference Optimization.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment WPO: Enhancing RLHF with Weighted Preference Optimization

Reference 1992

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.766564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6527333-4fa8-4f80-8b2e-aa2ad2bf0918 · outbound

This paper cites Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.729035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c759edbc-5ff6-4263-80e9-adbb94926641 · outbound

This paper cites Self- play fine-tuning converts weak language models to strong language models.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Self- play fine-tuning converts weak language models to strong language models

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T19:56:28.943209Z

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 7551adda-81c8-4e25-a0e7-ed146cf186c2 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Evaluating Large Language Models Trained on Code

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.704450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92d1c810-93ec-4e19-b669-115200e9cb7e · outbound

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

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.720194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58aef049-732a-4b19-bbe3-52df308e82d4 · outbound

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

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.701124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202baf4c-ee47-40ec-a812-86f42ce925fb · outbound

This paper cites Direct Language Model Alignment from Online AI Feedback.

Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment Direct Language Model Alignment from Online AI Feedback

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-09T19:56:28.723018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation af1d7231-a962-4122-a1fb-96b00ac11ab6 · inbound

The Differences Between Direct Alignment Algorithms are a Blur cites this paper.

The Differences Between Direct Alignment Algorithms are a Blur Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:52:29.449642Z

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 a01f68e3-aa5b-46ee-b15d-5caafd728814 · inbound

Multiplayer Nash Preference Optimization cites this paper.

Multiplayer Nash Preference Optimization Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:11:24.076019Z

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 5af4bffb-29f1-4d3a-8af2-9b417ce00858 · inbound

NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.

NVIDIA Nemotron 3: Efficient and Open Intelligence Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T01:40:42.424355Z

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.