Paper Citation Record · LEDGER

Bridging Offline and Online Reinforcement Learning for LLMs

As of 22 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 12 inbound Pith citation observations for arXiv:2506.21495.

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

pith.paper-citation-record.v1
2506.21495 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:28:10.266576Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:50:46.549563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:40:08.218379Z

Reference resolution

55 of 55 outbound references displayed

verified exact1
verified fuzzy11
unresolved43
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 344a4cba-33ab-4db7-a4f1-3f43136360d3 · outbound

This paper cites write newline.

Bridging Offline and Online Reinforcement Learning for LLMs write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:04.879326Z

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Observation b4279561-afe0-46a0-89e5-01b5919863f3 · outbound

This paper cites fairseq2, 2023.

Bridging Offline and Online Reinforcement Learning for LLMs fairseq2, 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:12.612372Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b781d302-fe36-4b2f-b531-b915a5c70a9d · outbound

This paper cites Preference learning algorithms do not learn preference rankings.

Bridging Offline and Online Reinforcement Learning for LLMs Preference learning algorithms do not learn preference rankings

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:12.399050Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f37495a5-d296-46c0-b9df-2c80c0b198a9 · outbound

This paper cites Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models.

Bridging Offline and Online Reinforcement Learning for LLMs Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Reference 4

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Observation b7ef05f0-2c6f-407e-8e1f-2280965fa0c9 · outbound

This paper cites Deep reinforcement learning from human preferences.

Bridging Offline and Online Reinforcement Learning for LLMs Deep reinforcement learning from human preferences

Reference 5

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Observation fdc39dda-ea42-4647-896f-4e89e297eccf · outbound

This paper cites The Llama 3 Herd of Models.

Bridging Offline and Online Reinforcement Learning for LLMs The Llama 3 Herd of Models

Reference 6

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Observation f133324e-40d8-4c15-997e-ea96aa6c6069 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:05.412620Z

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Observation 2a3fc58e-c16e-4c0d-b117-3ac588379246 · outbound

This paper cites Athene-70b: Redefining the boundaries of post-training for open models, July 2024 a.

Bridging Offline and Online Reinforcement Learning for LLMs Athene-70b: Redefining the boundaries of post-training for open models, July 2024 a

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:12.160526Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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

This paper cites How to Evaluate Reward Models for RLHF.

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

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Observation cebb86d3-51cf-482d-a85e-7cc9aa5a59fb · outbound

This paper cites Scaling laws for reward model overoptimization.

Bridging Offline and Online Reinforcement Learning for LLMs Scaling laws for reward model overoptimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:05.741024Z

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Observation 2cc140a8-6a72-4d09-a3b9-bf86a18b7246 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:05.871341Z

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Observation 84f5acc2-ba3b-43e3-946b-d31459bd35a3 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs Direct Language Model Alignment from Online AI Feedback

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:05.981374Z

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Observation 587f2705-7c85-4e90-af71-3c6b3ee6d799 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Bridging Offline and Online Reinforcement Learning for LLMs Measuring Mathematical Problem Solving With the MATH Dataset

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.065494Z

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Observation 8bc5fe93-ac70-44e6-944e-71c4a0713743 · outbound

This paper cites ORPO : Monolithic preference optimization without reference model.

Bridging Offline and Online Reinforcement Learning for LLMs ORPO : Monolithic preference optimization without reference model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.143444Z

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Observation 648e4f9b-ba8a-4ae4-ad7c-fd7242c24883 · outbound

This paper cites Lo RA : Low-rank adaptation of large language models.

Bridging Offline and Online Reinforcement Learning for LLMs Lo RA : Low-rank adaptation of large language models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.218419Z

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Observation bb5cea72-367c-44e7-ab17-1f8503bf2a32 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Bridging Offline and Online Reinforcement Learning for LLMs Gonzalez, Hao Zhang, and Ion Stoica

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.322902Z

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Observation 5a1178cc-fecf-4e77-8d95-f8d3fd2ee581 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Bridging Offline and Online Reinforcement Learning for LLMs Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.421583Z

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Observation 53e6dc1b-db68-4490-854b-f79bda263def · outbound

This paper cites Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions.

Bridging Offline and Online Reinforcement Learning for LLMs Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:12.015713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9745ab9e-2f20-445d-8ffa-8f388e7736f2 · outbound

This paper cites From live data to high-quality benchmarks: The arena-hard pipeline, April 2024 b.

Bridging Offline and Online Reinforcement Learning for LLMs From live data to high-quality benchmarks: The arena-hard pipeline, April 2024 b

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:11.809112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 54b4cd45-973e-41ea-a2e1-ba3a182c92cd · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Bridging Offline and Online Reinforcement Learning for LLMs From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:06.760710Z

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Observation 73c2a475-43b2-41d8-a0e4-231a0a7e259a · outbound

This paper cites Self-Alignment with Instruction Backtranslation.

Bridging Offline and Online Reinforcement Learning for LLMs Self-Alignment with Instruction Backtranslation

Reference 21

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Observation bf53e613-46e1-4248-89ae-94c0df82f4d3 · outbound

This paper cites Hashimoto.

Bridging Offline and Online Reinforcement Learning for LLMs Hashimoto

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:11.687633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e8167f2a-9bfc-49f2-aa9c-e62e88efe5ac · outbound

This paper cites Let's Verify Step by Step.

Bridging Offline and Online Reinforcement Learning for LLMs Let's Verify Step by Step

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.062465Z

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Observation d68b4f96-d8a1-4c78-a8f5-74ec1ec203de · outbound

This paper cites Statistical Rejection Sampling Improves Preference Optimization.

Bridging Offline and Online Reinforcement Learning for LLMs Statistical Rejection Sampling Improves Preference Optimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.163268Z

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Observation 627f0544-a507-48b9-8e8d-b5dd31932f45 · outbound

This paper cites Understanding r1-zero-like training: A critical perspective, 2025.

Bridging Offline and Online Reinforcement Learning for LLMs Understanding r1-zero-like training: A critical perspective, 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.276662Z

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Observation 118a8369-2f59-4425-b628-9df5572ca0e0 · outbound

This paper cites Mixtral of experts: A high quality sparse mixture-of-experts.

Bridging Offline and Online Reinforcement Learning for LLMs Mixtral of experts: A high quality sparse mixture-of-experts

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:11.541879Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1af63203-9798-4f1c-948d-469e6525b206 · outbound

This paper cites Ray: A distributed framework for emerging \ AI \ applications.

Bridging Offline and Online Reinforcement Learning for LLMs Ray: A distributed framework for emerging \ AI \ applications

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:11.357146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ceaffc31-60bd-42df-a8c3-a4578692c358 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs Training language models to follow instructions with human feedback

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.577745Z

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Observation d924b7eb-7f25-42fe-836d-3b7a7fe23925 · outbound

This paper cites West-of-N: Synthetic Preferences for Self-Improving Reward Models.

Bridging Offline and Online Reinforcement Learning for LLMs West-of-N: Synthetic Preferences for Self-Improving Reward Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.646010Z

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Observation 6e887785-451e-429b-81b5-183f57a09fcb · outbound

This paper cites Iterative reasoning preference optimization.

Bridging Offline and Online Reinforcement Learning for LLMs Iterative reasoning preference optimization

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.735012Z

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Observation 8524ab45-8871-43d7-9e42-487e27f30440 · outbound

This paper cites Disentangling length from quality in direct preference optimization.

Bridging Offline and Online Reinforcement Learning for LLMs Disentangling length from quality in direct preference optimization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:07.868238Z

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Observation 561a7e33-73f4-4e69-9cfa-a42e91b4fffd · outbound

This paper cites Disentangling Length from Quality in Direct Preference Optimization.

Bridging Offline and Online Reinforcement Learning for LLMs Disentangling Length from Quality in Direct Preference Optimization

Reference 32

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Observation 24110d55-6030-444d-b2d1-75b55ad7a8e0 · outbound

This paper cites Online dpo: Online direct preference optimization with fast-slow chasing, 2024.

Bridging Offline and Online Reinforcement Learning for LLMs Online dpo: Online direct preference optimization with fast-slow chasing, 2024

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:08.036930Z

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Observation 02239330-82da-4ba0-a3d5-42fa36a5edc1 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Bridging Offline and Online Reinforcement Learning for LLMs Direct preference optimization: Your language model is secretly a reward model

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:08.101830Z

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Observation 5b8ade72-fba5-41ec-a837-618165e1337b · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Bridging Offline and Online Reinforcement Learning for LLMs Direct preference optimization: Your language model is secretly a reward model

Reference 35

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Observation eb2362c4-a505-453e-9bfd-7166795d23e6 · outbound

This paper cites Trust region policy optimization.

Bridging Offline and Online Reinforcement Learning for LLMs Trust region policy optimization

Reference 36

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Observation 3120a6ea-4cc8-4632-a8fa-ac9bc2109dc1 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Bridging Offline and Online Reinforcement Learning for LLMs Proximal Policy Optimization Algorithms

Reference 38

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Observation 54604467-07e4-4c24-881d-947e81676d91 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 39

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This paper cites Welcome to the era of experience.

Bridging Offline and Online Reinforcement Learning for LLMs Welcome to the era of experience

Reference 40

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Observation 591e2016-2b65-4747-896a-17aba7f47326 · outbound

This paper cites A long way to go: Investigating length correlations in RLHF.

Bridging Offline and Online Reinforcement Learning for LLMs A long way to go: Investigating length correlations in RLHF

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:11.008634Z

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Observation 346d1015-0e56-44ca-b54d-f209525b007f · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Bridging Offline and Online Reinforcement Learning for LLMs LLaMA: Open and Efficient Foundation Language Models

Reference 42

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Observation ccc5ca8f-c8c3-425d-becb-b12fdd54ce2e · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 43

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Observation 0d1cd526-46cd-488e-87b3-c0ba5b3fd08a · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

Bridging Offline and Online Reinforcement Learning for LLMs Zephyr: Direct Distillation of LM Alignment

Reference 44

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Observation ce183029-a436-4bfc-a777-5425946aa887 · outbound

This paper cites Thinking LLMs: General Instruction Following with Thought Generation.

Bridging Offline and Online Reinforcement Learning for LLMs Thinking LLMs: General Instruction Following with Thought Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.217475Z

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Observation baeaa4fb-5bd9-4b9f-84da-61c5d5ffab84 · outbound

This paper cites Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge.

Bridging Offline and Online Reinforcement Learning for LLMs Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.310079Z

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Observation aadb1a06-6ba7-44f1-8ad0-d2b140535341 · outbound

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

Bridging Offline and Online Reinforcement Learning for LLMs Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.397544Z

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Observation a00e9344-8a24-475a-b719-bad7539cd25c · outbound

This paper cites Gibbs sampling from human feedback: A provable kl-constrained framework for rlhf.

Bridging Offline and Online Reinforcement Learning for LLMs Gibbs sampling from human feedback: A provable kl-constrained framework for rlhf

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:28:10.850501Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d8e1c05-82c5-420f-9591-4dd36d84a8f6 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

Bridging Offline and Online Reinforcement Learning for LLMs WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.578482Z

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Observation ab9dd718-b78d-491d-9789-0004f8b42a36 · outbound

This paper cites Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss.

Bridging Offline and Online Reinforcement Learning for LLMs Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.691354Z

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Observation 6a88cb36-aac5-4a67-8291-9c4fc629a398 · outbound

This paper cites Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study.

Bridging Offline and Online Reinforcement Learning for LLMs Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.790974Z

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Observation 757a19e2-111d-4b8c-b2d4-47fbf950d92b · outbound

This paper cites BPO : Staying close to the behavior LLM creates better online LLM alignment.

Bridging Offline and Online Reinforcement Learning for LLMs BPO : Staying close to the behavior LLM creates better online LLM alignment

Reference 52

Resolution: verified exact; doi, observed 2026-08-06T22:28:10.442692Z

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Observation 41c10192-46cd-49c6-aadf-e0e4536b6240 · outbound

This paper cites Self-Rewarding Language Models.

Bridging Offline and Online Reinforcement Learning for LLMs Self-Rewarding Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:09.980703Z

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Observation e89d6539-c0bf-45ad-b512-df53c68879fa · outbound

This paper cites WildChat: 1M ChatGPT Interaction Logs in the Wild.

Bridging Offline and Online Reinforcement Learning for LLMs WildChat: 1M ChatGPT Interaction Logs in the Wild

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:10.083842Z

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Observation 23af5f03-b49c-4648-8428-f8d344d54282 · outbound

This paper cites Lima: Less is more for alignment.

Bridging Offline and Online Reinforcement Learning for LLMs Lima: Less is more for alignment

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:10.181387Z

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Observation c4852346-3bd9-40a7-a77f-56969f60f120 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Bridging Offline and Online Reinforcement Learning for LLMs Fine-Tuning Language Models from Human Preferences

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T22:28:10.266576Z

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Pith citing papers

Observation 3ab7ef80-1dbb-46a4-821c-b519340abb04 · inbound

Task-Dependent Evaluation of LLM Output Homogenization: A Taxonomy-Guided Framework cites this paper.

Task-Dependent Evaluation of LLM Output Homogenization: A Taxonomy-Guided Framework Bridging Offline and Online Reinforcement Learning for LLMs

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:36:24.983666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d3c3b757-9212-422a-b8f0-97949b079396 · inbound

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation cites this paper.

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation Bridging Offline and Online Reinforcement Learning for LLMs

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T09:50:46.549563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202772d5-4b27-4529-a7b7-41fb2b972c45 · inbound

Safety Alignment of LMs via Non-cooperative Games cites this paper.

Safety Alignment of LMs via Non-cooperative Games Bridging Offline and Online Reinforcement Learning for LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:21.679930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 089ad325-e523-45ab-a2c4-a1e5469647d6 · inbound

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning cites this paper.

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning Bridging Offline and Online Reinforcement Learning for LLMs

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:56:15.425803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7465628b-7cca-4c32-8f66-7c8684b401f7 · inbound

Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO cites this paper.

Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO Bridging Offline and Online Reinforcement Learning for LLMs

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:02:50.010858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b7230ccc-d595-499e-98fc-4d0eb1787025 · inbound

Multi$^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments cites this paper.

Multi$^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments Bridging Offline and Online Reinforcement Learning for LLMs

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:46:27.027263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 507f7013-5128-4117-8a77-4d64895355cc · inbound

Multi$^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments cites this paper.

Multi$^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments Bridging Offline and Online Reinforcement Learning for LLMs

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-02T12:30:46.217716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc445246-eaec-4226-b5fc-f4fefe4861de · inbound

Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces cites this paper.

Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces Bridging Offline and Online Reinforcement Learning for LLMs

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:46:48.927436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7ee3a065-8118-4b92-9708-1f8e7d080591 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Bridging Offline and Online Reinforcement Learning for LLMs

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:40.509771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7e0c52fc-5ece-4b58-9779-38d28c66da07 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data Bridging Offline and Online Reinforcement Learning for LLMs

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:40:08.219887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f177b23e-6f8c-4e22-b30a-ef7b1335dae5 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data Bridging Offline and Online Reinforcement Learning for LLMs

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:19:51.287491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9cbe79a4-8756-444d-a1b3-b98c5f4f1484 · inbound

LeVo 2: Stable and Melodious Song Generation via Hierarchical Representation Modeling and Progressive Post-Training cites this paper.

LeVo 2: Stable and Melodious Song Generation via Hierarchical Representation Modeling and Progressive Post-Training Bridging Offline and Online Reinforcement Learning for LLMs

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:15:47.555967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.