Paper Citation Record · LEDGER

Natural Language Reinforcement Learning

As of 16 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 7 inbound Pith citation observations for arXiv:2411.14251.

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

pith.paper-citation-record.v1
2411.14251 v3

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:26:45.325950Z

measured 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:27:23.283216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:16:44.965693Z

Reference resolution

89 of 89 outbound references displayed

verified exact1
verified fuzzy25
unresolved63
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a368fc41-0a9e-44b2-a09d-f5b4429e93fc · outbound

This paper cites LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models.

Natural Language Reinforcement Learning LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.935259Z

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Observation edbff655-b780-4f2c-acc6-4781cb896451 · outbound

This paper cites PaLM 2 Technical Report.

Natural Language Reinforcement Learning PaLM 2 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.940575Z

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Observation 8e6354cf-3945-4821-9e95-e221f3b5d51b · outbound

This paper cites Barreto, W.

Natural Language Reinforcement Learning Barreto, W

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.945172Z

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Observation cd3505fa-6d02-425b-b25f-5ec9ffe43bc7 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.949269Z

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Observation 82eedd35-baa7-4241-ae48-ae7c2f7ffc24 · outbound

This paper cites Bellman, R.

Natural Language Reinforcement Learning Bellman, R

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.953506Z

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Observation 027d1516-beae-4a97-b028-10aad4e27b5d · outbound

This paper cites Brown, B.

Natural Language Reinforcement Learning Brown, B

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.957770Z

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Observation b898905b-6b13-42b8-b6bb-57be078bb2a6 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Natural Language Reinforcement Learning Evaluating Large Language Models Trained on Code

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.962409Z

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Observation 968957f6-3aeb-4a60-91c8-f50ddcfe376b · outbound

This paper cites LLF-Bench: Benchmark for Interactive Learning from Language Feedback.

Natural Language Reinforcement Learning LLF-Bench: Benchmark for Interactive Learning from Language Feedback

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.966685Z

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Observation 215f34e5-cb78-4abd-bae6-8d664bfbc452 · outbound

This paper cites Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs.

Natural Language Reinforcement Learning Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.971047Z

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Observation e0d72d1f-5f2b-4c08-9ed6-c2e6c6c1f16b · outbound

This paper cites Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning.

Natural Language Reinforcement Learning Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.975500Z

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Observation e30ebab1-2d78-405c-95ac-2df10dac9828 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Natural Language Reinforcement Learning Training Verifiers to Solve Math Word Problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.979752Z

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Observation 6eec9846-cdb4-4846-97f4-fa977e383a24 · outbound

This paper cites State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding.

Natural Language Reinforcement Learning State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:26:45.777439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 68263461-c87b-4c98-a219-73e774b388ce · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.988684Z

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Observation 90799239-f6f4-44ef-aa2b-5760d2e0ee17 · outbound

This paper cites The Llama 3 Herd of Models.

Natural Language Reinforcement Learning The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.992608Z

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Observation 340b0613-f11d-4dde-bd22-1ef2c30e3f63 · outbound

This paper cites ChessGPT: Bridging Policy Learning and Language Modeling.

Natural Language Reinforcement Learning ChessGPT: Bridging Policy Learning and Language Modeling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:44.996629Z

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Observation cf78593d-89e2-49b2-a804-19c8160fc570 · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

Natural Language Reinforcement Learning Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.000653Z

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Observation 022ddc83-bea1-4f4b-98cf-1d39cb98a159 · outbound

This paper cites LLM-based NLG Evaluation: Current Status and Challenges.

Natural Language Reinforcement Learning LLM-based NLG Evaluation: Current Status and Challenges

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.005039Z

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Observation ed42830a-4390-451e-b83b-c2c48bb67aa9 · outbound

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

Natural Language Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.009187Z

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Observation 21297ea2-61f3-4a41-92c8-9f173e7a7b85 · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Natural Language Reinforcement Learning Reasoning with Language Model is Planning with World Model

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.013350Z

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Observation c8c35a29-850e-4ef6-a3ba-6711af4651e6 · outbound

This paper cites Hayes and J.

Natural Language Reinforcement Learning Hayes and J

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.017508Z

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Observation f79122b0-303a-4c7a-adfa-0994a33a1e7f · outbound

This paper cites OpenAI o1 System Card.

Natural Language Reinforcement Learning OpenAI o1 System Card

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.021348Z

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Observation 5623c0bb-efbc-4590-9539-14819357dfe2 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.025502Z

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Observation e39943cb-360e-4690-9ee5-1b85c31dd478 · outbound

This paper cites TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks.

Natural Language Reinforcement Learning TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.029330Z

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Observation 50e91fdc-b438-433e-9c09-a0b23aa0b2c3 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

Natural Language Reinforcement Learning Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 24

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Observation a2a2e805-cc57-485e-8a56-0d3276fd2a5f · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.037941Z

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Observation 090d6e21-77de-4093-9ceb-52a911f540c7 · outbound

This paper cites Kocsis and C.

Natural Language Reinforcement Learning Kocsis and C

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.041894Z

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Observation baea8e53-557f-4d0a-a45d-660c4bede6b9 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 27

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Observation 15555ad6-9319-414c-af79-3b621ccafb93 · outbound

This paper cites OpenSpiel: A Framework for Reinforcement Learning in Games.

Natural Language Reinforcement Learning OpenSpiel: A Framework for Reinforcement Learning in Games

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.049600Z

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Observation 0ef26c8b-17ad-43a0-a63c-bc4178e0e717 · outbound

This paper cites Generative Judge for Evaluating Alignment.

Natural Language Reinforcement Learning Generative Judge for Evaluating Alignment

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.053988Z

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Observation 32b09d38-f9ab-467a-b377-a323a2b11b45 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Natural Language Reinforcement Learning Understanding R1-Zero-Like Training: A Critical Perspective

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.058370Z

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Observation 3c3292ec-4609-4c37-a898-c828cc6d0528 · outbound

This paper cites Generative Reward Models.

Natural Language Reinforcement Learning Generative Reward Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.062487Z

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Observation 5c7a0cc6-029a-497c-99b0-9b0581e26e10 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 32

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Observation 3edd602c-77a4-4631-892a-97efadcdf350 · outbound

This paper cites GPT-4 Technical Report.

Natural Language Reinforcement Learning GPT-4 Technical Report

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.070775Z

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Observation 74c14bfd-11a0-404a-a664-d71479fa398f · outbound

This paper cites Ouyang, J.

Natural Language Reinforcement Learning Ouyang, J

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.074842Z

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Observation 46cb65de-18f8-4efb-a797-9dad6c1706b0 · outbound

This paper cites Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents.

Natural Language Reinforcement Learning Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents

Reference 35

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Observation fd94541d-a95b-4d81-ac3a-83ac8faae2d8 · outbound

This paper cites Saffidine, N.

Natural Language Reinforcement Learning Saffidine, N

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.340851Z

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Observation efdae428-298b-40be-a3cc-7eb771a76251 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Natural Language Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 37

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Observation 26cac532-b3c5-415e-9b01-039864b7dbe5 · outbound

This paper cites Rethinking Reflection in Pre-Training.

Natural Language Reinforcement Learning Rethinking Reflection in Pre-Training

Reference 38

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Observation 2a937d47-c854-4991-98d6-34686234fe20 · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Natural Language Reinforcement Learning Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 39

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Observation c71c5c5e-437b-45dd-ae5a-f7301efda2d9 · outbound

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Natural Language Reinforcement Learning Silver and R

Reference 40

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Observation b181ebfa-afc3-498d-8ae2-8c55cfc9d7a7 · outbound

This paper cites Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations.

Natural Language Reinforcement Learning Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations

Reference 41

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Observation 40e41c35-8a1f-44ab-b114-adeb6c0703c4 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 42

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Observation 516ac680-a738-4587-8af6-7fa5091b44e9 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 43

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Observation 433e3daf-fa10-40c6-969b-efde65600741 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 44

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Observation fd17f4e5-b3c1-44ec-9148-8e5ad73b8e39 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Natural Language Reinforcement Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 45

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Observation b80ef602-fd7d-4a90-bcaa-9466c20ee407 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Natural Language Reinforcement Learning Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 46

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Observation 9fe5d0bf-c40b-462d-a63d-2e5ab29e633f · outbound

This paper cites PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization.

Natural Language Reinforcement Learning PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Reference 47

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Observation fc44de71-934f-4cc1-a34b-022d6a17a79e · outbound

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Natural Language Reinforcement Learning RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 48

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Observation c163c745-5944-48c7-a55b-e3608bae8c10 · outbound

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Natural Language Reinforcement Learning Emergent Abilities of Large Language Models

Reference 49

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Natural Language Reinforcement Learning Unresolved cited work

Reference 50

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Observation 09b81976-abb5-40cd-9058-8b833ba79809 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 51

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Natural Language Reinforcement Learning Large Language Models for Generative Information Extraction: A Survey

Reference 52

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Natural Language Reinforcement Learning Large Language Models as Optimizers

Reference 53

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Observation 69d78044-50c8-4cac-b9c0-aa02ce107df7 · outbound

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Natural Language Reinforcement Learning ReAct: Synergizing Reasoning and Acting in Language Models

Reference 54

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Observation 275d478a-7246-49b5-a490-64807a15e1a4 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Natural Language Reinforcement Learning Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 55

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Observation c955fc7f-bdb2-4801-bee7-dd28cff0eafc · outbound

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Natural Language Reinforcement Learning TextGrad: Automatic "Differentiation" via Text

Reference 56

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Observation 1385d4df-1b9d-4dd4-9239-1ba1dda1cbca · outbound

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Natural Language Reinforcement Learning Generative Verifiers: Reward Modeling as Next-Token Prediction

Reference 57

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Observation 83a6326b-e7e6-42c3-ab74-7a1d3a5f38bc · outbound

This paper cites Benchmarking Large Language Models for News Summarization.

Natural Language Reinforcement Learning Benchmarking Large Language Models for News Summarization

Reference 58

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Observation 3161a2f7-e05a-433b-b13d-28948673740d · outbound

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Natural Language Reinforcement Learning Policy Improvement using Language Feedback Models

Reference 59

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Observation 315e4d54-7606-40cf-9c90-2262fe82b012 · outbound

This paper cites Use <white> or <black> to represent the winning side.

Natural Language Reinforcement Learning Use <white> or <black> to represent the winning side

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.223330Z

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Observation 73decc35-f457-4762-b451-80870bd6cc29 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 64

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Observation 77302053-7a92-47b6-8402-ea19c56002fb · outbound

This paper cites Advantage: <white> Overall, White has a slight advantage in this position, with multiple ways to break through Black’s lines and gain a significant advantage.

Natural Language Reinforcement Learning **Advantage:** <white> Overall, White has a slight advantage in this position, with multiple ways to break through Black’s lines and gain a significant advantage

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.197407Z

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Observation 6742d035-c1cd-4feb-a4c2-ed68866ed586 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:26:46.184618Z

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Observation 49b80d2d-ecb4-4a07-bb18-ccd3349b0257 · outbound

This paper cites Advantage: <white> Overall, White has a slight advantage in this position, with multiple ways to break through Black’s lines and gain a significant advantage.

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.172127Z

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Observation c49dc1fc-d99e-4de9-988b-aa5338f9d038 · outbound

This paper cites This move has the goal of preparing to defend and possibly create a barrier against Black’s pieces.

Natural Language Reinforcement Learning This move has the goal of preparing to defend and possibly create a barrier against Black’s pieces

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.159468Z

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Observation 0cedb6ca-ddaa-4013-9e28-ef5290690248 · outbound

This paper cites This move aims to create more space and put pressure on Black’s pieces, which will make it harder for them to maneuver.

Natural Language Reinforcement Learning This move aims to create more space and put pressure on Black’s pieces, which will make it harder for them to maneuver

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.146899Z

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Observation cb177108-f87d-4e0d-91b4-08ae93c7ec17 · outbound

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Natural Language Reinforcement Learning Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:26:46.134238Z

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Observation f23cfb63-092e-479d-a9ec-f4bde217cc0b · outbound

This paper cites final_evaluation.

Natural Language Reinforcement Learning final_evaluation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.121483Z

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Observation f5bbee96-1118-454a-b70d-e1b3cfc39820 · outbound

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Natural Language Reinforcement Learning "" EVAL_USER_PROMPT =

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.108186Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fcba6d14-aea2-49bb-bd2f-1c12f89e5eb0 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:26:46.262116Z

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Observation 6922645e-48b9-4b95-9df2-3ef9a5369764 · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:26:46.249725Z

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Observation 11b82be6-f8ee-4836-b06d-18703db65bca · outbound

This paper cites an unresolved cited work.

Natural Language Reinforcement Learning Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:26:46.236565Z

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Observation 08198664-f4ef-4fab-83a8-6cc9d48fb95c · outbound

This paper cites "" TD_USER_PROMPT =.

Natural Language Reinforcement Learning "" TD_USER_PROMPT =

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.095362Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 768c5c5a-a3a9-4aa7-b0a7-aa2b90aa875e · outbound

This paper cites The conclusion supports the paper’s contributions and scope.

Natural Language Reinforcement Learning The conclusion supports the paper’s contributions and scope

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.082659Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d9b6f142-05d6-4266-9eee-cf085f843313 · outbound

This paper cites Limitations.

Natural Language Reinforcement Learning Limitations

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.069435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9a5f5e7b-22c5-4a7e-b387-a17dc885f5bd · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include theoretical results.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not include theoretical results

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.057280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 800b0abe-8c36-4fa3-a400-a44c47e56794 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not include experiments

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.044107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 96587e05-3452-41c3-95d1-28ad959637d0 · outbound

This paper cites Guidelines: • The answer NA means that paper does not include experiments requiring code.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that paper does not include experiments requiring code

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.031338Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 49a75a41-5a31-4439-bd1f-82f37f7bcd4c · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not include experiments

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.018065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 01f27543-9ee9-4199-9b2c-bd3a2ee81389 · outbound

This paper cites Due to high computational burdens, the paper does not include error bars for all of our experiments, but the paper contains every detail necessary for experiment reproduction.

Natural Language Reinforcement Learning Due to high computational burdens, the paper does not include error bars for all of our experiments, but the paper contains every detail necessary for experiment reproduction

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:46.004196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f61acb50-017a-4a4d-8e66-fda4bd71858f · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not include experiments

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.990850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d4448829-c2b1-488c-b45d-4f4ec9d08db4 · outbound

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Natural Language Reinforcement Learning Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.976256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 334c8107-35b1-4106-9487-7a823278ab2c · outbound

This paper cites Guidelines: • The answer NA means that there is no societal impact of the work performed.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that there is no societal impact of the work performed

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.962991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 53c71d70-a38e-40d7-b635-d8b8cb40d1ba · outbound

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Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper poses no such risks

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.949541Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a5cc73ca-7410-4d9b-826a-cff21d26a8a3 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not use existing assets

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.935765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 86107130-3554-4d29-b039-416562879423 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not release new assets.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not release new assets

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.922556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3db7b08e-9894-421d-8a8f-8004f128d4d9 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-12T15:26:45.317297Z

Source-reported events for the cited work

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Observation e202afd8-c6e8-4284-b00f-ca07ba2aae17 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Natural Language Reinforcement Learning Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.900941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 775af9aa-6b5e-4ce4-95e1-46dec77421c2 · outbound

This paper cites Answer: [Yes] Justification: The paper is about foundational research on LLM and has described the usage of LLMs.

Natural Language Reinforcement Learning Answer: [Yes] Justification: The paper is about foundational research on LLM and has described the usage of LLMs

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:26:45.887647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation 4a8ea224-44d9-4c42-bbe4-61d127990c06 · inbound

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks cites this paper.

A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworks Natural Language Reinforcement Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T19:27:23.283216Z

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Unavailable: canonical work link unavailable.

Observation 1d0bc4b8-304c-47b1-b80c-88712380399e · inbound

elsciRL: Integrating Language Solutions into Reinforcement Learning Problem Settings cites this paper.

elsciRL: Integrating Language Solutions into Reinforcement Learning Problem Settings Natural Language Reinforcement Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:17:51.412053Z

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Unavailable: canonical work link unavailable.

Observation 6c032603-e570-4a06-8d29-73791bff4a0d · inbound

LLM Economist: Large Population Models and Mechanism Design in Multi-Agent Generative Simulacra cites this paper.

LLM Economist: Large Population Models and Mechanism Design in Multi-Agent Generative Simulacra Natural Language Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T15:28:42.368027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a793711b-2543-4159-9e11-a314f0d7daa6 · inbound

Learning from Language Feedback via Variational Policy Distillation cites this paper.

Learning from Language Feedback via Variational Policy Distillation Natural Language Reinforcement Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:39:00.368600Z

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Observation 62af02a2-3793-4ca9-9930-1bf60acf34a8 · inbound

When Clients Stop Following: A Cognitive Conceptualization Diagram-driven Framework for Strategic Counseling cites this paper.

When Clients Stop Following: A Cognitive Conceptualization Diagram-driven Framework for Strategic Counseling Natural Language Reinforcement Learning

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:16:44.967417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0a90098d-cd39-4f92-a217-89194b133d30 · inbound

Instruction-Conditioned Exploration for Reinforcement Learning with Self-Distillation to an Unconditioned Policy cites this paper.

Instruction-Conditioned Exploration for Reinforcement Learning with Self-Distillation to an Unconditioned Policy Natural Language Reinforcement Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T15:25:49.260514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9be8e652-2fb8-4dc0-ad9b-9062167e5bbf · inbound

Instruction-Conditioned Exploration for Reinforcement Learning with Self-Distillation to an Unconditioned Policy cites this paper.

Instruction-Conditioned Exploration for Reinforcement Learning with Self-Distillation to an Unconditioned Policy Natural Language Reinforcement Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:15.885559Z

Source-reported events for the cited work

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