Paper Citation Record · LEDGER

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2210.01241.

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

pith.paper-citation-record.v1
2210.01241 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:55:20.175303Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T00:46:56.861091Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 60163b01-834e-4577-85aa-4a58338630d1 · inbound

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

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 136

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:46:56.863217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 30583c24-e39b-4dfe-aa0d-406303ddb552 · inbound

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models cites this paper.

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 116

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T21:20:59.214159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ed6cbbe-99a6-41cd-ae6a-9d427b1592b3 · inbound

RedRFT: A Light-Weight Benchmark for Reinforcement Fine-Tuning-Based Red Teaming cites this paper.

RedRFT: A Light-Weight Benchmark for Reinforcement Fine-Tuning-Based Red Teaming Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T10:55:20.175303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4315a4d-6138-4a5e-a77a-56c8f4f8748a · inbound

Explicit Preference Optimization: No Need for an Implicit Reward Model cites this paper.

Explicit Preference Optimization: No Need for an Implicit Reward Model Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:40:17.982800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f5f0ec8-367f-4403-92b0-338e21d2aa72 · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 217

Resolution: unresolved; no resolver link, observed 2026-08-06T14:13:07.092046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58995126-1e7c-4486-8e9b-dd9328fd994d · inbound

Red-Teaming Vision-Language-Action Models via Quality Diversity Prompt Generation for Robust Robot Policies cites this paper.

Red-Teaming Vision-Language-Action Models via Quality Diversity Prompt Generation for Robust Robot Policies Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T11:19:57.989893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 62096ec7-e79e-4dbc-a449-9330c3fc8199 · inbound

Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning cites this paper.

Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:05:59.994873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6935e888-670c-40ab-bb41-51594d2b5b4a · inbound

Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception cites this paper.

Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:36:01.718759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0a86a7a-ce88-4642-b809-653e5a94be19 · inbound

Response Time Enhances Alignment with Heterogeneous Preferences cites this paper.

Response Time Enhances Alignment with Heterogeneous Preferences Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:45:59.589927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a17cbd27-48fa-4f76-94d0-784c84a0ef1f · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

Reference 289

Resolution: unresolved; no resolver link, observed 2026-07-11T13:53:36.775836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7aa3f6ec-309c-4f64-95e9-78ba1ad164c0 · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Reference 290

Resolution: unresolved; no resolver link, observed 2026-08-02T08:41:06.439432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.