Paper Citation Record · LEDGER

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2509.03537.

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

pith.paper-citation-record.v1
2509.03537 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:17:13.821920Z

measured 18 of 18 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 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

18 of 18 outbound references displayed

verified exact0
verified fuzzy3
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a7a71da-eeb0-4562-b917-d3a509c04373 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Evaluating Large Language Models Trained on Code

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.732880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8e3db9b-6914-4760-826b-fecc9e6486ec · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.738630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b73d0ffa-457b-4b1d-85c5-b595229fe28f · outbound

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

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.743935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbe70dc4-8e78-4d4e-88a8-b072a15b3a7e · outbound

This paper cites StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.749999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8753fe9-fef7-4f22-9d23-1e4dc5afc420 · outbound

This paper cites Competitive Programming with Large Reasoning Models.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Competitive Programming with Large Reasoning Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.755616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397166e6-a4a4-44d1-8f37-0ffa783c02d6 · outbound

This paper cites an unresolved cited work.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:17:14.122287Z

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 16e4a717-7845-47c8-b931-7bb989f39dba · outbound

This paper cites Language Models Can Teach Themselves to Program Better.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Language Models Can Teach Themselves to Program Better

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.766596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f12c963a-9083-4579-8128-fc2233fb8adc · outbound

This paper cites Qwen2.5-Coder Technical Report.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Qwen2.5-Coder Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.771367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e56cf67-6e4d-4b7c-92ac-30340b4a9d38 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.776157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 944c58a2-a88b-4d2a-9dbe-d3b2c24a94d1 · outbound

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

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Understanding R1-Zero-Like Training: A Critical Perspective

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.781115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf84de14-32ec-4fa4-bdbf-4020e10daa64 · outbound

This paper cites CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.786271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5759bce-d896-4232-b2df-88f3d6ad35f4 · outbound

This paper cites Qwen2.5 Technical Report.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Qwen2.5 Technical Report

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.791467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cf570fe-e19a-413a-98c7-b137748981b8 · outbound

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

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.797081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 826bf715-dc69-4193-92a9-815a966ded12 · outbound

This paper cites Execution-based Code Generation using Deep Reinforcement Learning.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Execution-based Code Generation using Deep Reinforcement Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.801965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44eb70b4-099c-4dfc-a3ce-bf381b2e2cd2 · outbound

This paper cites Sutton and Andrew G.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Sutton and Andrew G

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:14.107674Z

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 4337c025-72a6-4375-9146-b13ac84b2cc5 · outbound

This paper cites Reinforcement Learning Enhanced LLMs: A Survey.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Reinforcement Learning Enhanced LLMs: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.811953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e33c6417-4a03-41ba-be60-dfa7156370dc · outbound

This paper cites the word is a subset of the puzzle’s characters).

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models the word is a subset of the puzzle’s characters)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:14.093333Z

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 3ece2b84-8724-4fa4-a6b2-6345d1d91dd0 · outbound

This paper cites includes the first character of the puzzle and contains all the characters from the puzzle.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models includes the first character of the puzzle and contains all the characters from the puzzle

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:17:14.077781Z

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.

Pith citing papers

No inbound Pith citation observations are available.