Paper Citation Record · LEDGER

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

As of 13 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 13 inbound Pith citation observations for arXiv:2506.08989.

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

pith.paper-citation-record.v1
2506.08989 v1

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:01:24.353008Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:17:38.690339Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T18:17:33.758346Z

Reference resolution

93 of 93 outbound references displayed

verified exact0
verified fuzzy6
unresolved86
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e21e5946-6e2c-4958-aa70-05157d3d6c78 · outbound

This paper cites Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.089154Z

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Observation 21aae386-2ef6-4aa4-8d78-b48c9020da11 · outbound

This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.092784Z

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Observation f7f6efc6-d15b-4409-b085-79fcfb820213 · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.096216Z

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Observation 795cfb9a-3440-4cc7-b00a-dfeb9e47aef8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Training Verifiers to Solve Math Word Problems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.099163Z

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Observation 444bad16-8172-439e-af77-37911851bead · outbound

This paper cites Nearest neighbor pattern classification.IEEE transactions on information theory, 13(1):21–27, 1967.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Nearest neighbor pattern classification.IEEE transactions on information theory, 13(1):21–27, 1967

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.101834Z

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Observation 8494ff6c-dfad-47cd-b313-b7eec9c5ea07 · outbound

This paper cites Process Reinforcement through Implicit Rewards.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Process Reinforcement through Implicit Rewards

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.104449Z

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Observation d618a45c-bbd8-44c1-b0e7-8ceaa4afb208 · outbound

This paper cites Open r1: A fully open reproduction of deepseek-r1, January 2025.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Open r1: A fully open reproduction of deepseek-r1, January 2025

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.107393Z

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Observation 65d781ef-83f7-4f1c-8f7c-0d316c9fd3c2 · outbound

This paper cites The Llama 3 Herd of Models.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning The Llama 3 Herd of Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.110140Z

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Observation 06e02db3-49d4-4303-b2bb-2dae77510a5a · outbound

This paper cites rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.112886Z

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Observation b6a6c548-6f5f-46b1-9fa2-e82483501392 · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.115411Z

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Observation d58dc3c4-d2cf-4252-a6cd-fa0e7567d73e · outbound

This paper cites Olympiad- bench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Olympiad- bench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.117978Z

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Observation 9d429c5a-2a21-4c17-9e9d-333aca6d0183 · outbound

This paper cites Skyworkopenreasonerseries.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Skyworkopenreasonerseries

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.120427Z

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Observation acdea8a8-df57-4221-90d7-adb65cde3e04 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.Sort, 2(4): 0–6, 2021.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Measuring mathematical problem solving with the math dataset.Sort, 2(4): 0–6, 2021

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.122804Z

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Observation 5fdc6bfa-d305-422f-9113-6ae52e74720b · outbound

This paper cites Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.125078Z

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Observation 408a24fd-cfcc-4564-b8ff-ff9c928c58d3 · outbound

This paper cites Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.127813Z

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Observation 81d44e76-1f7a-41b7-a26f-723b456eaa4f · outbound

This paper cites OpenAI o1 System Card.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning OpenAI o1 System Card

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.130388Z

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Observation 9aa4b2e8-32b4-4c68-bc0e-e7d79fd00ed8 · outbound

This paper cites Knowledge- augmented reasoning distillation for small language models in knowledge-intensive tasks.Advances in Neural Information Processing Systems, 36:48573–48602, 2023.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Knowledge- augmented reasoning distillation for small language models in knowledge-intensive tasks.Advances in Neural Information Processing Systems, 36:48573–48602, 2023

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.132956Z

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Observation dffebfb5-adc4-4029-9d9b-9559ba82485f · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Gonzalez, Hao Zhang, and Ion Stoica

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.135196Z

Source-reported events for the cited work

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Observation f6e8813c-4150-4f42-b6e7-46e2507e6ec1 · outbound

This paper cites Solving quantitative reasoning problems with language models.Advances in Neural Information Processing Systems, 35: 3843–3857, 2022.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Solving quantitative reasoning problems with language models.Advances in Neural Information Processing Systems, 35: 3843–3857, 2022

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.137465Z

Source-reported events for the cited work

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Observation f8f00e26-8ce6-46d5-8511-c212abc361c4 · outbound

This paper cites Common 7B Language Models Already Possess Strong Math Capabilities.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Common 7B Language Models Already Possess Strong Math Capabilities

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.139853Z

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Observation f00847c0-fec3-4aee-bc29-da9ab492b095 · outbound

This paper cites From generation to judgment: Opportunities and challenges of llm-as-a-judge.arXiv preprint arXiv:2411.16594, 2024.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning From generation to judgment: Opportunities and challenges of llm-as-a-judge.arXiv preprint arXiv:2411.16594, 2024

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.142570Z

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Observation 67b2ffa4-f2eb-4445-bf66-67a400742f9d · outbound

This paper cites LIMR: Less is More for RL Scaling.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning LIMR: Less is More for RL Scaling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.145061Z

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Observation 2c93907a-1052-42cc-a055-453eef601138 · outbound

This paper cites TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.147834Z

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Observation 0527b2e1-f295-4287-a70d-9bbb64f064f3 · outbound

This paper cites From System 1 to System 2: A Survey of Reasoning Large Language Models.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning From System 1 to System 2: A Survey of Reasoning Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.150655Z

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Observation 0e47cd1a-4d78-45bc-ada1-90e2f1782f55 · outbound

This paper cites Task Oriented In-Domain Data Augmentation.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Task Oriented In-Domain Data Augmentation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.153512Z

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Observation c0173a58-a462-435d-ab26-f430656a5616 · outbound

This paper cites Let’s verify step by step.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Let’s verify step by step

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.156285Z

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Observation 0c1205cd-def1-4f25-bf6d-668cc55db813 · outbound

This paper cites Augmenting math word problems via iterative question composing.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Augmenting math word problems via iterative question composing

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.159002Z

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Observation 5b1eb7ed-159f-4a59-980c-567cb2b38c6b · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Understanding R1-Zero-Like Training: A Critical Perspective

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.161345Z

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Observation 36f27c6a-6278-4eaf-b813-a876df3e527b · outbound

This paper cites SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.164213Z

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Observation 426ff685-7541-4cb4-a2f6-2a7abf44b8c2 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.166865Z

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Observation 0e9c5958-01a1-44c0-8ace-e662bbc76d89 · outbound

This paper cites Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.169433Z

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Observation b1ee18de-6c4a-4f6f-8ec9-ad19fbc7fa63 · outbound

This paper cites ReFT: Reasoning with Reinforced Fine-Tuning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning ReFT: Reasoning with Reinforced Fine-Tuning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.171772Z

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Observation 20c33ad2-872d-43ac-8203-ccf0d3296030 · outbound

This paper cites American mathematics competitions (AMC 10/12).

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning American mathematics competitions (AMC 10/12)

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.174644Z

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Observation f3ea30b0-2db3-41fb-b297-c75c47c18ae7 · outbound

This paper cites American invitational mathematics examination (AIME).

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning American invitational mathematics examination (AIME)

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.176910Z

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Observation 9e2c2ddc-9a31-4f0a-bdc1-83ad9eb5649e · outbound

This paper cites s1: Simple test-time scaling.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning s1: Simple test-time scaling

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.181910Z

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Observation eb1e8ecc-1bb2-448b-9ec6-5a8c2ea6156b · outbound

This paper cites Smoothing Out Hallucinations: Mitigating LLM Hallucination with Smoothed Knowledge Distillation.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Smoothing Out Hallucinations: Mitigating LLM Hallucination with Smoothed Knowledge Distillation

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.184746Z

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Observation 3e828667-bcf3-48a7-ad23-a9bd85c9dcfd · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730– 27744, 2022.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730– 27744, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.187499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54129201-6111-4211-851a-87ceeab991c2 · outbound

This paper cites MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.190807Z

Source-reported events for the cited work

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Observation 544df257-d2cf-496f-a09e-d4f549208a86 · outbound

This paper cites Proximal Policy Optimization Algorithms.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Proximal Policy Optimization Algorithms

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.193880Z

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Observation 8736f22e-dae6-4c9b-8faf-a1c93d6de001 · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.196848Z

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Observation 24662ffb-c264-4631-af2f-7f3314206f60 · outbound

This paper cites Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.199659Z

Source-reported events for the cited work

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Observation f93e7aa4-8f1a-4dd0-8290-698a6f6bfce2 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning HybridFlow: A Flexible and Efficient RLHF Framework

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.202855Z

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Observation f461f536-92b8-46b9-a689-3f5ae74fa4e8 · outbound

This paper cites Efficient Reinforcement Finetuning via Adaptive Curriculum Learning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Efficient Reinforcement Finetuning via Adaptive Curriculum Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.205768Z

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Observation af7c036a-e277-46cf-bd1e-95ab1ad8d0ef · outbound

This paper cites Large language models for data annotation and synthesis: A survey.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Large language models for data annotation and synthesis: A survey

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.156802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3680da20-6462-4d17-83d2-5ab0e4357c1a · outbound

This paper cites Mathscale: Scaling instruction tuning for mathematical reasoning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Mathscale: Scaling instruction tuning for mathematical reasoning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.148509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fbe9324c-2fb3-4fd4-b76d-3acff595b7cf · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.213883Z

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Observation 7e925c12-d9b7-4362-8e23-4fa43bbb41d0 · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.216939Z

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Observation 2e2b9996-07ec-4440-b989-c866a5647eec · outbound

This paper cites Dart-math: Difficulty-aware rejection tuning for mathematical problem-solving.Advances in Neural Information Processing Systems, 37:7821–7846, 2024.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Dart-math: Difficulty-aware rejection tuning for mathematical problem-solving.Advances in Neural Information Processing Systems, 37:7821–7846, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.134887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 84ceaeff-0d18-45aa-8f79-707c113c317c · outbound

This paper cites Openmathinstruct-1: A 1.8 million math instruction tuning dataset.Advances in Neural Information Processing Systems, 37:34737–34774, 2024.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Openmathinstruct-1: A 1.8 million math instruction tuning dataset.Advances in Neural Information Processing Systems, 37:34737–34774, 2024

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.126951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ead05707-8f16-40f7-9349-cb3cef9a9d93 · outbound

This paper cites Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.224905Z

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Observation b30c748d-c604-49f7-9c3c-aa054484011c · outbound

This paper cites Explore the Reasoning Capability of LLMs in the Chess Testbed.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Explore the Reasoning Capability of LLMs in the Chess Testbed

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.227678Z

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Observation 2afe12b7-5507-4f09-9017-3eca11d63e40 · outbound

This paper cites Examining false positives under inference scaling for mathematical reasoning.arXiv preprint arXiv:2502.06217, 2025.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Examining false positives under inference scaling for mathematical reasoning.arXiv preprint arXiv:2502.06217, 2025

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.230830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf457c15-fa3a-4d33-a7ad-bcdc482e83be · outbound

This paper cites Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.233618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3792c869-4ccb-4a8d-b2fb-37e61dfa4142 · outbound

This paper cites Fine-grained human feedback gives better rewards for language model training.Advances in Neural Information Processing Systems, 36:59008–59033, 2023.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Fine-grained human feedback gives better rewards for language model training.Advances in Neural Information Processing Systems, 36:59008–59033, 2023

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.236534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 962e3e5d-9e77-4b1e-aa22-9c407beb8a47 · outbound

This paper cites A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.239657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be76fbae-93bd-43b9-9954-a0c0b08d0d4f · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.242658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76e5be5d-b6b1-4df6-9000-713d118aac47 · outbound

This paper cites Qwen2.5 Technical Report.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Qwen2.5 Technical Report

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.245535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cdadef9-18d5-456d-ab77-de1091d4c497 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.248156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49f89318-4f59-4b71-b1cb-89104f99129c · outbound

This paper cites LIMO: Less is More for Reasoning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning LIMO: Less is More for Reasoning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.250842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9f9b1f8-3f34-4f5c-b985-d526825b24e3 · outbound

This paper cites Demystifying Long Chain-of-Thought Reasoning in LLMs.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Demystifying Long Chain-of-Thought Reasoning in LLMs

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.253700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1649c7b-2163-4771-b4ba-dd88ccf752bb · outbound

This paper cites Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language Models.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.256779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation decbd585-0da8-4383-9b40-8653b184b4ee · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.260331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42b9d5fd-007a-4d0f-8532-9d229f7347a2 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.263254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357d701a-568f-4f66-9ec6-53b779eeae76 · outbound

This paper cites Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.266890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9d31dd3-77a0-4581-918f-ffdecd649ba1 · outbound

This paper cites VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.270146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89a8ed69-2f13-41d2-b7c5-05d6d8c1b80b · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.272905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3a71132-7d0a-4ed9-8b16-0e1a34f67b49 · outbound

This paper cites SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.275765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c633bf1-ae61-4c18-a6d4-4047f6ea3b29 · outbound

This paper cites Rest-mcts*: Llm self-training via process reward guided tree search.Advances in Neural Information Processing Systems, 37:64735–64772, 2024.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Rest-mcts*: Llm self-training via process reward guided tree search.Advances in Neural Information Processing Systems, 37:64735–64772, 2024

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.278944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 228a7f3b-d51f-4453-892b-52afc8a2d0bb · outbound

This paper cites Balancing speciality and versatility: a coarse to fine framework for supervised fine-tuning large language model.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Balancing speciality and versatility: a coarse to fine framework for supervised fine-tuning large language model

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.108731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b8e0183b-dd8c-426c-b887-fb5a31b60961 · outbound

This paper cites Process-based Self-Rewarding Language Models.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Process-based Self-Rewarding Language Models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.284330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aad07c4-6676-4390-ac88-39428790589a · outbound

This paper cites Evaluating the Performance of Large Language Models on GAOKAO Benchmark.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.287403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3777fc28-c445-4af4-a4f2-55d684f645d5 · outbound

This paper cites 1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning 1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.290580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 593556dd-f49d-456d-9bcf-f6e075cae8d2 · outbound

This paper cites Promptcot: Synthesizing olympiad-level problems for mathematical reasoning in large language models.arXiv preprint arXiv:2503.02324, 2025.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Promptcot: Synthesizing olympiad-level problems for mathematical reasoning in large language models.arXiv preprint arXiv:2503.02324, 2025

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.293756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b7f6c82-2274-4773-bfb0-c0f83c69af82 · outbound

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

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Fine-Tuning Language Models from Human Preferences

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.296727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 608a7665-1ac5-4b48-9ee8-a877948827b9 · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning TTRL: Test-Time Reinforcement Learning

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:24.299735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85ac589d-1f86-4088-b7ac-c1ef40899a16 · outbound

This paper cites Let’s think step by step and output the final answer within “∖boxed{}.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Let’s think step by step and output the final answer within “∖boxed{}

Reference 77

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T05:01:25.100791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4acc41aa-0735-45ab-9090-ced5baf37279 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.092909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3893a523-8b05-4b9e-b204-8ab6420d5ab1 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.085821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 906fa85b-88d0-4375-baeb-cf59e85ddbc5 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.078266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 765d8801-9e27-4e21-a3eb-90cc2a0225de · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.071266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac286313-68a0-422e-8629-f9813c2d82fc · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.064054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 488ecaf7-548b-4632-aa20-a3822232e1b7 · outbound

This paper cites ### Output Format : - First , provide your brief outline and planning for the question design.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning ### Output Format : - First , provide your brief outline and planning for the question design

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:01:25.056425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7d10985f-22f1-41e3-89f4-74447f4600e0 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 84

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.048156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cc6fcc66-609d-4c2d-b844-5f0cc2574456 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.039882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9f239392-f56b-4ff8-8874-8024e6abbd73 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.032590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ab9efd30-3f79-4d89-b83c-a3af5ccf71fd · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.025142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9b151e98-c755-4475-86d1-5df25b4d329a · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.016741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1211b350-b2b1-4cc7-9083-ef9bcb61a25e · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.008134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a7b43e2e-2ffb-437d-9b50-cef7c5b7c573 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.999815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72a69c35-1e4e-4365-87e9-1ef6359e27c4 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.991456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation db2a18fe-e500-49f5-a2c1-614161821f13 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.983773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 864def1b-ffd6-49e7-ab28-d8d31f5552df · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 93

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:24.974829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 944059f0-1116-4255-9878-3e7afa29d930 · outbound

This paper cites an unresolved cited work.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:01:25.170896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 6ce4099e-64e1-4d5f-bb86-20d23d32d5b1 · inbound

Libra: Large Chinese-based Safeguard for AI Content cites this paper.

Libra: Large Chinese-based Safeguard for AI Content SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T12:17:38.690339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aada9b5e-40ca-4420-be05-92b822b7db85 · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 193

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:21:48.776855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 33f605ae-eee2-4ce0-8cbf-94d14178471f · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 299

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:24.823728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6776643c-97a0-4199-9eb2-0fd15a3547b6 · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:33.895807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fbca871-fffc-476e-ac85-e9ceb31743d2 · inbound

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning cites this paper.

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-16T16:28:05.689821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 70ec431f-26c0-44d1-a8bf-90c3a40bb5b1 · inbound

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models cites this paper.

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 182

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:40:54.785339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 015fd05d-9846-488c-9baa-c6ea3f247377 · inbound

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments cites this paper.

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 202

Resolution: verified exact; arxiv_id, observed 2026-05-15T01:23:27.233413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation baf5f158-3f8c-4031-9a2e-2ea31bf95a55 · inbound

Confidence-Aware Alignment Makes Reasoning LLMs More Reliable cites this paper.

Confidence-Aware Alignment Makes Reasoning LLMs More Reliable SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:55:53.987663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 16caeec2-af6f-44dd-a223-a6cb3ee161ec · inbound

G-Zero: Self-Play for Open-Ended Generation from Zero Data cites this paper.

G-Zero: Self-Play for Open-Ended Generation from Zero Data SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:11:24.431684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1240ba79-4253-49fc-98b1-5c45025dfec3 · inbound

REVES: REvision and VErification--Augmented Training for Test-Time Scaling cites this paper.

REVES: REvision and VErification--Augmented Training for Test-Time Scaling SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:29:15.126478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9c0575ca-1c65-4e26-a911-8601810c1a2a · inbound

From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier cites this paper.

From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 137

Resolution: verified exact; local_arxiv, observed 2026-07-10T18:17:33.759692Z

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Observation 9211432e-5b7f-4b22-82cc-94924bc16437 · inbound

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation cites this paper.

Spectral Origins of the Self-Correction Blind Spot in Autoregressive Generation SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reference 13

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

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics cites this paper.

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

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