Paper Citation Record · LEDGER

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2608.01522.

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

pith.paper-citation-record.v1
2608.01522 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:08:27.089569Z

measured 42 of 42 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

42 of 42 outbound references displayed

verified exact9
verified fuzzy1
unresolved31
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5d36def0-842b-44e7-89fa-021b73d2c339 · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:08:31.189095Z

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 afe4e132-1f59-4f87-9e9f-f59c16195e15 · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:08:30.979532Z

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

Observation 1e7ee572-2531-4076-b210-b57198a62915 · outbound

This paper cites Y.; Kim, H.; Nam, J.; and Kwak, D.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Y.; Kim, H.; Nam, J.; and Kwak, D

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:22.378877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98747308-700e-46db-9866-9d4b7a981365 · outbound

This paper cites Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:30.212990Z

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 c41ccfc0-7b53-4ac3-a3fe-e2c36127ebb5 · outbound

This paper cites C.-Y.; Peng, B.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics C.-Y.; Peng, B

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:22.565249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc4eca74-4853-4e5e-8f89-a58db3cf9f7f · outbound

This paper cites Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problems.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problems

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T00:08:29.917633Z

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 1fa5ee7b-aefd-43c2-89c4-52b3cfbf1c16 · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:22.747287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 160a72b3-4192-4973-ae14-c95c8f7e1222 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Training Verifiers to Solve Math Word Problems

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:22.802880Z

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Unavailable: canonical work link unavailable.

Observation 55f961c5-37da-4973-99c5-03b2d44e0b40 · outbound

This paper cites The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:22.965289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1502b380-af18-4e3d-9000-b7db58bad258 · outbound

This paper cites Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.124533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a4e408d-a9d4-41b7-b629-1601260c0875 · outbound

This paper cites FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.220982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 082e6d06-398f-4600-a127-18d04123a176 · outbound

This paper cites LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.331668Z

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Unavailable: canonical work link unavailable.

Observation a3818433-6bd3-4e9d-aff3-867595dfc4a3 · outbound

This paper cites Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:29.591004Z

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 7049221d-c652-4120-a28e-84b764880ac5 · outbound

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

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Measuring Mathematical Problem Solving With the MATH Dataset

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.557233Z

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Unavailable: canonical work link unavailable.

Observation 3a7b2a6b-419b-48d8-aa18-77e82cc17200 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics LoRA: Low-Rank Adaptation of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.659512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05fe3a9a-a991-4487-a9e3-ad615971040d · outbound

This paper cites R-Zero: Self-Evolving Reasoning LLM from Zero Data.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics R-Zero: Self-Evolving Reasoning LLM from Zero Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.821560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e6e7eef-9e77-48a0-95ed-d94b47422642 · outbound

This paper cites On the Emergence of Implicit Curriculum in RLVR Learning Dynamics.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics On the Emergence of Implicit Curriculum in RLVR Learning Dynamics

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:23.894377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f797a26b-738a-413f-8c77-b79072c75b0c · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:08:30.777702Z

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 a7e01ae2-2f1f-4c8f-8d6c-d0031bf62ec9 · outbound

This paper cites ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:24.264070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4f66b6-5fac-44b2-a9b5-52f9c7f926fc · outbound

This paper cites Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:29.296261Z

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 77a1f805-2869-48e1-83ad-23c326f45a3a · outbound

This paper cites Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:29.061480Z

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 59f5f96d-954b-43de-9c55-70257781ffc8 · outbound

This paper cites N.; Guo, Z.; and Chen, W.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics N.; Guo, Z.; and Chen, W

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:24.590955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 320d73ca-b445-4c57-8b2c-a322c9e2aee3 · outbound

This paper cites SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:24.739824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18e1d785-71a1-4d60-b579-091137d6ce39 · outbound

This paper cites Let's Verify Step by Step.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Let's Verify Step by Step

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:24.826627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7145b4ce-6d8a-451c-8d7e-236ebea1f53f · outbound

This paper cites Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Self-Improvement Can Self-Regress: The Rise-and-Collapse Failure Mode of LLM Self-Training

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:24.971238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9d067c6-2a3f-4cfe-8a25-8dd9f3e40c9c · outbound

This paper cites Augmenting Math Word Problems via Iterative Question Composing.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Augmenting Math Word Problems via Iterative Question Composing

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:25.129155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dcbe759-1785-4b01-93f2-7865b7afdc9f · outbound

This paper cites ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:25.365379Z

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Unavailable: canonical work link unavailable.

Observation fdb61e68-0c05-42de-8a15-7b65e0b3a022 · outbound

This paper cites Learning from Synthetic Data without Model Collapse in Iterative Instruction Tuning.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Learning from Synthetic Data without Model Collapse in Iterative Instruction Tuning

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:28.703155Z

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 166b9f55-4cde-4a6a-8ee7-af3499ee993d · outbound

This paper cites Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:25.757170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf24a7a1-9fe9-4d55-b960-91b809835627 · outbound

This paper cites Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:25.854976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09c6067f-041f-45f9-a358-ea66f29aade2 · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 31

Resolution: verified exact; raw_fallback, observed 2026-08-06T00:08:28.385709Z

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 ec615c0f-6570-4048-a053-5c49094d6aee · outbound

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

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.039213Z

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Unavailable: canonical work link unavailable.

Observation bbfb2bf7-b513-4dd5-95d9-9632d261dd80 · outbound

This paper cites Efficient Reinforcement Finetuning via Adaptive Curriculum Learning.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Efficient Reinforcement Finetuning via Adaptive Curriculum Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.113912Z

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Observation 3b8e3f2b-e8fc-4857-9463-42f308cc2a1e · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 34

Resolution: verified exact; raw_fallback, observed 2026-08-06T00:08:28.065753Z

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 a97687d4-99e0-4e60-99e2-6eb33bf6ffa1 · outbound

This paper cites A.; Di Giacomo, D.; Bond \'a r, I.; Engdahl, E.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics A.; Di Giacomo, D.; Bond \'a r, I.; Engdahl, E

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:08:30.549639Z

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 7ce4ed75-9699-482f-b0e8-cd77a78d8fa4 · outbound

This paper cites Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.436283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c73a7ed3-e9d1-4db3-996e-c6cf06bdff0d · outbound

This paper cites PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.563300Z

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Unavailable: canonical work link unavailable.

Observation 869d2bb8-4850-4f5e-96ae-a51523cbb232 · outbound

This paper cites CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.676385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad48a7e9-6041-45fb-ae39-a29a3bab8f2a · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.742198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28c8611c-8363-424b-b700-09269d6beb1b · outbound

This paper cites an unresolved cited work.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Unresolved cited work

Reference 40

Resolution: verified exact; raw_fallback, observed 2026-08-06T00:08:27.704155Z

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 d1ab7a5a-a1da-479a-92d6-25e1ca92c2bb · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T00:08:26.939816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ad2b193-5d0c-4c5f-87ab-d942a94c7a89 · outbound

This paper cites D$^2$Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning.

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics D$^2$Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:08:27.354804Z

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

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