Paper Citation Record · LEDGER

Direct Advantage Regression: Aligning LLMs with Online AI Reward

As of 19 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2504.14177.

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

pith.paper-citation-record.v1
2504.14177 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:00:34.711691Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

54 of 54 outbound references displayed

verified exact0
verified fuzzy4
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External citation measurements

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Outbound references

Observation f67c0f3a-d532-48a4-a3dc-e0644bbc088d · outbound

This paper cites Back to basics: Revisiting reinforce style optimization for learning from human feedback in llms, 2024.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Back to basics: Revisiting reinforce style optimization for learning from human feedback in llms, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:00:35.951192Z

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Observation 78f90cf9-0683-4843-9857-75deac2d3d4d · outbound

This paper cites A General Theoretical Paradigm to Understand Learning from Human Preferences.

Direct Advantage Regression: Aligning LLMs with Online AI Reward A General Theoretical Paradigm to Understand Learning from Human Preferences

Reference 2

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Observation 146d267f-f2b3-4cd1-b680-36f4a59acfc3 · outbound

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

Direct Advantage Regression: Aligning LLMs with Online AI Reward Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

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Observation f0cc1340-df53-43f0-b848-1762fafa1f8f · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Constitutional AI: Harmlessness from AI Feedback

Reference 4

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Observation b3641164-07a0-4499-ac7b-ed9b8202db4a · outbound

This paper cites Language Models are Few-Shot Learners.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Language Models are Few-Shot Learners

Reference 5

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Observation 64188103-c8e8-4033-ac65-247f4f919641 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 6

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Observation 3c207f77-5e88-462b-9a07-a23162186ff2 · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 7

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Observation 62a67080-c3a3-4199-9a4a-e2c24cd6fc9a · outbound

This paper cites Bootstrapping Language Models with DPO Implicit Rewards.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Bootstrapping Language Models with DPO Implicit Rewards

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.252305Z

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Observation 1ee19758-c12f-4241-8e2c-22849ea4afd8 · outbound

This paper cites OPTune: Efficient Online Preference Tuning.

Direct Advantage Regression: Aligning LLMs with Online AI Reward OPTune: Efficient Online Preference Tuning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.259371Z

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Observation b1a6ddfb-930d-43be-9f07-d598e35b906a · outbound

This paper cites GRATH: Gradual Self-Truthifying for Large Language Models.

Direct Advantage Regression: Aligning LLMs with Online AI Reward GRATH: Gradual Self-Truthifying for Large Language Models

Reference 10

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Observation 79bee758-fb04-48c2-b7e9-39f29f96472d · outbound

This paper cites Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.281660Z

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Observation 47a838fc-ef96-4b8e-b869-677ec81c36e4 · outbound

This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.

Direct Advantage Regression: Aligning LLMs with Online AI Reward UltraFeedback: Boosting Language Models with Scaled AI Feedback

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.290438Z

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Observation 88d9a818-1973-4e64-9c2c-5823feadb2e0 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Direct Advantage Regression: Aligning LLMs with Online AI Reward FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.296889Z

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Observation ab6b6760-305f-4e42-bc1e-e73676c10f70 · outbound

This paper cites The Llama 3 Herd of Models.

Direct Advantage Regression: Aligning LLMs with Online AI Reward The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.303916Z

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Observation b14e1d8f-a538-42e8-bc4e-bb8f264f61b7 · outbound

This paper cites Accelerate: Training and inference at scale made simple, efficient and adaptable.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Accelerate: Training and inference at scale made simple, efficient and adaptable

Reference 15

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Observation ca4695f6-5b45-4b13-ba43-bf7e576d529a · outbound

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

Direct Advantage Regression: Aligning LLMs with Online AI Reward Direct Language Model Alignment from Online AI Feedback

Reference 16

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Observation b53c1a16-f0ec-4732-9240-220720a77ba0 · outbound

This paper cites Large Language Models Can Self-Improve.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Large Language Models Can Self-Improve

Reference 17

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Observation 5bb3867a-9e85-4ccd-9a0b-dd040d95acce · outbound

This paper cites Mistral 7B.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Mistral 7B

Reference 18

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Observation fb1df4bc-5fd6-47c1-9bbb-0fdf51c42bb1 · outbound

This paper cites LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression.

Direct Advantage Regression: Aligning LLMs with Online AI Reward LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.332928Z

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Observation 49d30676-1d5e-4e45-9221-f88207877ce6 · outbound

This paper cites Buy 4 REINFORCE samples, get a baseline for free!, 2019.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Buy 4 REINFORCE samples, get a baseline for free!, 2019

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:00:35.911831Z

Source-reported events for the cited work

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Observation 7db09f20-10ba-4ae2-95c2-932de7832e3b · outbound

This paper cites H., Gonzalez, J.

Direct Advantage Regression: Aligning LLMs with Online AI Reward H., Gonzalez, J

Reference 21

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Observation 5713cc60-a032-40f9-9ee1-9c7fb09b7853 · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

Direct Advantage Regression: Aligning LLMs with Online AI Reward RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.355051Z

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Observation 119025eb-6581-4f30-876e-c57e1f9bbfa5 · outbound

This paper cites Long-context LLMs Struggle with Long In-context Learning.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Long-context LLMs Struggle with Long In-context Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.363013Z

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Observation 0260710d-1281-41b8-94ff-f9cfb170da8d · outbound

This paper cites Self-Alignment with Instruction Backtranslation.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Self-Alignment with Instruction Backtranslation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.370186Z

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Observation 655e60ba-9d44-4f89-93ce-da6d3994aeb9 · outbound

This paper cites GPT-4 Technical Report.

Direct Advantage Regression: Aligning LLMs with Online AI Reward GPT-4 Technical Report

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.376535Z

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Observation 2823e698-7e03-4f77-ab70-9a1cd46d21df · outbound

This paper cites Training language models to follow instructions with human feedback.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Training language models to follow instructions with human feedback

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.383490Z

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Observation beaa816a-bc9f-4c5b-9e67-e5969ca58a1c · outbound

This paper cites Iterative Reasoning Preference Optimization.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Iterative Reasoning Preference Optimization

Reference 27

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Observation 567618af-c880-49f7-8ed0-53554abed509 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.396199Z

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Observation 566be659-2760-4af5-aca0-72c8a17bb822 · outbound

This paper cites and Schaal, S.

Direct Advantage Regression: Aligning LLMs with Online AI Reward and Schaal, S

Reference 29

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Observation 7d34b619-f8f7-451f-83af-f53ae90e55a7 · outbound

This paper cites Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing

Reference 30

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Observation 2dbdcd2e-4fe1-4134-8f3a-a9a247fe76f6 · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Improving language understanding by generative pre-training

Reference 31

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Observation 2451e565-9a03-44d8-a62f-5a9877d51b31 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T12:00:34.423837Z

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Observation bd5f79f4-7d37-4d7b-a39b-23b9227ab623 · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Stable-baselines3: Reliable reinforcement learning implementations

Reference 33

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Observation 80c2df79-a520-471c-99a7-e48dcffd2c15 · outbound

This paper cites Trust Region Policy Optimization.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Trust Region Policy Optimization

Reference 34

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Observation 187f42c2-3341-4438-8a03-2b8e6a2d0b79 · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Proximal Policy Optimization Algorithms

Reference 35

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Adafactor: Adaptive Learning Rates with Sublinear Memory Cost

Reference 36

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Observation e3f413ea-612b-4baa-b9c8-235f2c723be3 · outbound

This paper cites Learning to summarize from human feedback.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Learning to summarize from human feedback

Reference 37

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Direct Advantage Regression: Aligning LLMs with Online AI Reward S., Barto, A

Reference 38

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Observation 3bfda666-2dd3-41a5-b7b1-ab9c1a87c596 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Gemma 2: Improving Open Language Models at a Practical Size

Reference 39

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This paper cites Attention Is All You Need.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Attention Is All You Need

Reference 40

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Observation c903f103-4cda-4f66-967b-b0d7a5ae870d · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Trl: Transformer reinforcement learning

Reference 41

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This paper cites Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models.

Direct Advantage Regression: Aligning LLMs with Online AI Reward Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models

Reference 42

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 43

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Critic Regularized Regression

Reference 44

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Observation 851b486b-a22a-46a7-a95b-1d03bfab8819 · outbound

This paper cites HelpSteer2-Preference: Complementing Ratings with Preferences.

Direct Advantage Regression: Aligning LLMs with Online AI Reward HelpSteer2-Preference: Complementing Ratings with Preferences

Reference 45

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint

Reference 46

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 47

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Qwen2 technical report, 2024 a

Reference 48

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Observation f89034d2-5489-42bd-b99b-6761bad044ed · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs

Reference 49

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Self-Rewarding Language Models

Reference 50

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Direct Advantage Regression: Aligning LLMs with Online AI Reward SLiC-HF: Sequence Likelihood Calibration with Human Feedback

Reference 51

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 52

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Direct Advantage Regression: Aligning LLMs with Online AI Reward Fine-Tuning Language Models from Human Preferences

Reference 53

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Observation 8711beae-a82d-419a-a3f5-a8e0c68b3288 · outbound

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Direct Advantage Regression: Aligning LLMs with Online AI Reward write newline

Reference 54

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Pith citing papers

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