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Paper Citation Record · LEDGER

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving

As of 4 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2512.10739.

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

pith.paper-citation-record.v1
2512.10739 v3

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:40:30.140719Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

67 of 67 outbound references displayed

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Outbound references

Observation 7b201fa7-2edf-4822-bc7c-96f7908bcbc1 · outbound

This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 1

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source=pdf_text observed=2026-08-04T06:40:23.260343Z digest=sha256:2d5cea2c512fdc0c8824a4b0892f08cb9649cebd68ce0da1335e926a661ff7c4

Observation 4e30123f-1e0f-461c-bef2-97d05a189f2a · outbound

This paper cites Intern-s1: A scientific multimodal foundation model.arXiv preprint arXiv:2508.15763, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Intern-s1: A scientific multimodal foundation model.arXiv preprint arXiv:2508.15763, 2025

Reference 2

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source=pdf_text observed=2026-08-04T06:40:23.379329Z digest=sha256:2c3faef436457314928ca7e0ba61c56ded5d34a9e63845391afe53be8c410eea

Observation efbee071-935c-4cbe-b658-be0b4f3f058e · outbound

This paper cites MathArena: Evaluating LLMs on Uncontaminated Math Competitions.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving MathArena: Evaluating LLMs on Uncontaminated Math Competitions

Reference 3

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Observation 29799628-afe5-4a3d-9348-6e5c57770324 · outbound

This paper cites Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving

Reference 4

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source=pdf_text observed=2026-08-04T06:40:23.612497Z digest=sha256:6e1f0ee84d9798204c21ef50339359f138f3069231798762b564dd3850cc515a

Observation 979f597f-44f8-4126-aa3c-bf3e5dacc73e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Evaluating Large Language Models Trained on Code

Reference 5

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source=pdf_text observed=2026-08-04T06:40:23.752322Z digest=sha256:17aec3af3c80639d74693336f0a78919a19da0aaeb73f003faf036f6b6120a9e

Observation 24574ada-0b90-40c2-8cac-349d5496bbd8 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 6

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source=pdf_text observed=2026-08-04T06:40:23.898599Z digest=sha256:0f7973fe9d149ec221510457f731a90bce518b04879448c75f0d2f9dd825f810

Observation 73278f5f-43d5-42d5-bd87-3427e81b5fd7 · outbound

This paper cites Advanced version of gemini with deep think officially achieves gold-medal standard at the international mathematical olympiad, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Advanced version of gemini with deep think officially achieves gold-medal standard at the international mathematical olympiad, 2025

Reference 7

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source=pdf_text observed=2026-08-04T06:40:24.041814Z digest=sha256:6306f19449e95ef03882f0d18be87072d0cf5d83090393ca061105648e61ecb2

Observation 835dc669-3e1f-4893-9f4f-15008906d575 · outbound

This paper cites ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving

Reference 8

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source=pdf_text observed=2026-08-04T06:40:24.157889Z digest=sha256:62c85d8517a1d71747f82b30eea00cf8e8822ea67142e4cd45abb366df460a7f

Observation 1583c6ec-1618-4414-a522-ef5c0234287a · outbound

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

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 9

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source=pdf_text observed=2026-08-04T06:40:24.287198Z digest=sha256:81137611a0b1092ed578663043287b2469e9bcaa1d1c022f3a1ae921837a0541

Observation 729f308b-1a61-4b24-b3f5-584588604f3b · outbound

This paper cites Hmmt february problem archive.https://www.hmmt.org/ www/tournaments/testing.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Hmmt february problem archive.https://www.hmmt.org/ www/tournaments/testing

Reference 10

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source=pdf_text observed=2026-08-04T06:40:24.340920Z digest=sha256:b8e086c36dc184007f467038ddf66b402353921c9c01a852f87a6849f9b1e7e8

Observation 2cfff7d0-c4fc-4186-9736-e6af98a8b8f0 · outbound

This paper cites MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations

Reference 11

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source=pdf_text observed=2026-08-04T06:40:24.420480Z digest=sha256:9c1d2f09fe965550b391a6083e84d06f53788fd413857ed0b4bfe97f08e2a781

Observation b2792294-7191-4a69-bfe7-1eb41359ea78 · outbound

This paper cites Gemini 2.5 pro capable of winning gold at imo 2025.arXiv preprint arXiv:2507.15855, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Gemini 2.5 pro capable of winning gold at imo 2025.arXiv preprint arXiv:2507.15855, 2025

Reference 12

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source=pdf_text observed=2026-08-04T06:40:24.484225Z digest=sha256:84be56775d59d4966440178e4256f6df282e54bed0081355d81a3cbcf03f886f

Observation ae9d5220-c9a0-4ad3-9512-a51abf8654d2 · outbound

This paper cites A survey of frontiers in llm reasoning: Inference scaling, learning to reason, and agentic systems.Trans.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving A survey of frontiers in llm reasoning: Inference scaling, learning to reason, and agentic systems.Trans

Reference 13

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source=pdf_text observed=2026-08-04T06:40:24.537173Z digest=sha256:697e57eac03afae0337afec36458f0c7669a4a1cae0e76c96ce4322aea717e0b

Observation 2ebcdcce-ecc9-4caa-a902-5544966723a6 · outbound

This paper cites Prover-Verifier Games improve legibility of LLM outputs.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Prover-Verifier Games improve legibility of LLM outputs

Reference 14

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source=pdf_text observed=2026-08-04T06:40:24.619908Z digest=sha256:44b08e5fe723a2acbc32c8d3c69ec89089e288171b0e6d58a7a068941f18a8d9

Observation 93227744-8493-4868-8185-a193fa6cf660 · outbound

This paper cites WebThinker: Empowering Large Reasoning Models with Deep Research Capability.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Reference 15

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Observation d543d618-6245-4541-a094-87a016794b19 · outbound

This paper cites ToRL: Scaling Tool-Integrated RL.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving ToRL: Scaling Tool-Integrated RL

Reference 16

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source=pdf_text observed=2026-08-04T06:40:24.762093Z digest=sha256:283f7f2ee1a067069ffa3fdcb84ad071414220fb276d8f66f41a03b7f4b49d56

Observation f1165099-4e1e-472f-b650-fef726a1aa97 · outbound

This paper cites Compassverifier: A unified and robust verifier for llms evaluation and outcome reward.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Compassverifier: A unified and robust verifier for llms evaluation and outcome reward

Reference 17

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Observation da937472-cdc1-490a-beb9-4b79cd4fbc57 · outbound

This paper cites Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning

Reference 18

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Observation aa1c584d-1889-43a7-90f1-4d6295cc8023 · outbound

This paper cites Agent rl scaling law: Agent rl with spontaneous code execution for mathematical problem solving,.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Agent rl scaling law: Agent rl with spontaneous code execution for mathematical problem solving,

Reference 19

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source=pdf_text observed=2026-08-04T06:40:24.943221Z digest=sha256:59bda0d3732a0b37eb30bb2d815d3f441273d9d3200450eeacacb8bc45327770

Observation fe2d36aa-692b-4d64-ad4f-0bf512bc21cf · outbound

This paper cites American invitational mathematics examination (aime) problems and solutions.https://maa.org/student-programs/amc/.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving American invitational mathematics examination (aime) problems and solutions.https://maa.org/student-programs/amc/

Reference 20

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source=pdf_text observed=2026-08-04T06:40:25.140202Z digest=sha256:ed6bda050b7325d4c1990c975c2d19adc7e8560efe094298c4e01d754832e115

Observation d053c4c5-5559-4bd8-850b-48cec6049235 · outbound

This paper cites Malt: Improving reasoning with multi-agent llm training.ArXiv, abs/2412.01928, 2024.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Malt: Improving reasoning with multi-agent llm training.ArXiv, abs/2412.01928, 2024

Reference 21

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Observation 9a4a0a4a-c032-4bc5-95e3-127d9a40499e · outbound

This paper cites s1: Simple test-time scaling.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving s1: Simple test-time scaling

Reference 22

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Observation 475e95e1-0d9c-436a-a578-77bf2bb3f67e · outbound

This paper cites Introducing openai o3 and o4-mini, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Introducing openai o3 and o4-mini, 2025

Reference 23

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Observation 10b45ed2-0b4f-4e54-8e93-e826ab1495af · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving gpt-oss-120b & gpt-oss-20b Model Card

Reference 24

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Observation 7dd3c732-b590-4a79-94e9-a8e8d06217cb · outbound

This paper cites Openai imo 2025 proofs, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Openai imo 2025 proofs, 2025

Reference 25

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source=pdf_text observed=2026-08-04T06:40:25.529637Z digest=sha256:75387e99229b2005b615bc6b3d3d8e8aa2dd7447c788d81e66d9197aa8bfc46e

Observation 3f1be116-8a29-4246-9df0-8330539a4fd0 · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-04T06:40:25.589280Z digest=sha256:a1c0acb7ab5f4d3073c45ad093cabdc621ada1bd8d21a0afecb972b370116fd8

Observation 4c4f4155-107f-4702-bed7-c21e665bb296 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 27

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source=pdf_text observed=2026-08-04T06:40:25.685252Z digest=sha256:d8b2d85ec7bf4abb5b4b95c2d734a91e400a147a83577f7533018a5462c3ba53

Observation 03de0ad8-bd7c-4deb-9eb4-a8e79f32dea3 · outbound

This paper cites rStar2-Agent: Agentic Reasoning Technical Report.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving rStar2-Agent: Agentic Reasoning Technical Report

Reference 28

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source=pdf_text observed=2026-08-04T06:40:25.785903Z digest=sha256:2c6d52f0cc40d6628313e1af76bc28af9da6a378d376aa14eb90f03ee04826e7

Observation e3f43e40-60a2-41cd-b675-8500ca787fd4 · outbound

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

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 29

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source=pdf_text observed=2026-08-04T06:40:25.875766Z digest=sha256:5785bf601b40813317f322637d43840cf7dcff68593e56497ff130e734aab1df

Observation 00be9321-a837-47be-bf23-06498554a1b7 · outbound

This paper cites Satori-r1: Incentivizing multimodal reasoning with spatial grounding and verifiable rewards.arXiv preprint arXiv:2505.19094, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Satori-r1: Incentivizing multimodal reasoning with spatial grounding and verifiable rewards.arXiv preprint arXiv:2505.19094, 2025

Reference 30

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source=pdf_text observed=2026-08-04T06:40:26.033608Z digest=sha256:0412c2518c66ebcc2d9bf1ba2265f53e3426594f977f5b42236d7aa540b69531

Observation e0ffad19-3c3c-4541-8f1f-17837f6a4a8e · outbound

This paper cites A survey of reasoning with foundation models: Concepts, methodologies, and outlook.ACM Computing Surveys, 57(11):1–43, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving A survey of reasoning with foundation models: Concepts, methodologies, and outlook.ACM Computing Surveys, 57(11):1–43, 2025

Reference 31

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Observation bd427e85-4ef1-4d32-891b-17ab59710af9 · outbound

This paper cites Plan-and- solve prompting: Improving zero-shot chain-of-thought reasoning by large language models.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Plan-and- solve prompting: Improving zero-shot chain-of-thought reasoning by large language models

Reference 32

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source=pdf_text observed=2026-08-04T06:40:26.267470Z digest=sha256:f79e44b9b8146a48d627d2dadca7cbe01518ec62a15ae1ba4b5cd91c6133e479

Observation 4884c081-abb6-484b-97b8-4ca30140d06d · outbound

This paper cites A Survey on Large Language Models for Mathematical Reasoning.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving A Survey on Large Language Models for Mathematical Reasoning

Reference 33

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Observation f707769d-30a2-4b07-897c-127aaf196d40 · outbound

This paper cites OPV: Outcome-based process verifier for efficient long chain-of-thought verification.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving OPV: Outcome-based process verifier for efficient long chain-of-thought verification

Reference 34

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source=pdf_text observed=2026-08-04T06:40:26.470372Z digest=sha256:8ffa1d2fba5e5720d1ad06cc5df22c0975181b10880e41b3b6415092af9263b0

Observation 182acec9-b37b-482a-a6a6-03e50247561d · outbound

This paper cites Grok 4, 2025.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Grok 4, 2025

Reference 35

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source=pdf_text observed=2026-08-04T06:40:26.616335Z digest=sha256:5eb1592b32eb4dfce92eaebf78b8da357bcdda7e53a6da449c10ca76c483e47a

Observation ffdce025-c348-45d2-87ba-e02f69d451e8 · outbound

This paper cites Qwen3 Technical Report.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Qwen3 Technical Report

Reference 36

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source=pdf_text observed=2026-08-04T06:40:26.760868Z digest=sha256:e9fe3f1683595304d1cbeff83522313f8cc502af380681ad0e0e6a44a3b34ded

Observation 741bd985-9344-4848-9c55-1d873f5a24ec · outbound

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

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 37

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source=pdf_text observed=2026-08-04T06:40:26.993380Z digest=sha256:ceab4a91740b9e205f6d4e10ddac2935fbc5abed481a1d8dc8f0b4068213b837

Observation 955d0567-4898-445d-a39e-c52286bacebd · outbound

This paper cites Reinforce LLM Reasoning through Multi-Agent Reflection.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Reinforce LLM Reasoning through Multi-Agent Reflection

Reference 38

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source=pdf_text observed=2026-08-04T06:40:27.178080Z digest=sha256:e3edcf320334c72b646811db96b4da6cb6205fc2aaf0d4de2402be0ef95b1239

Observation 5762b5d4-e3ab-44c7-949a-91706f00eabc · outbound

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

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 39

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source=pdf_text observed=2026-08-04T06:40:27.371206Z digest=sha256:0e26c14b6b089403c789858ff8b76cf69b2a8f72768c6cc3e874058dcf4d4067

Observation ca0b9613-7d1b-4a01-86e6-6041655acc47 · outbound

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

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Reference 40

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source=pdf_text observed=2026-08-04T06:40:27.544092Z digest=sha256:68d7f0ccca539ae998a66e64803e05f44754210cbf5a94bea0af1d4b173e5df6

Observation 55537287-1e32-4ea5-97b8-a6533ee96552 · outbound

This paper cites ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Reference 41

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source=pdf_text observed=2026-08-04T06:40:27.771393Z digest=sha256:9b8c20a29bf2d5e797af9a0c49d64aad4862272937d15df0bfbd0d61ebc6a911

Observation d047db71-af55-4f75-9d6a-289ac171181e · outbound

This paper cites ARTIST: Improving the Generation of Text-rich Images with Disentangled Diffusion Models and Large Language Models.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving ARTIST: Improving the Generation of Text-rich Images with Disentangled Diffusion Models and Large Language Models

Reference 42

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T06:40:27.940805Z digest=sha256:ab161b76b9ae5484fe03e2489839c6e863152eeaf21710b02add88129dd8f925

Observation 8f8665b6-ba14-4e32-bf36-4f742ab48380 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Automatic Chain of Thought Prompting in Large Language Models

Reference 43

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no resolver link, observed 2026-08-04T06:40:28.151683Z

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source=pdf_text observed=2026-08-04T06:40:28.151683Z digest=sha256:e01ca2c887cd58ee8f9c537056465ee8142f209c8239537da27abd5e824325b1

Observation 49fcb739-e383-416b-be90-8b35cff3e367 · outbound

This paper cites ProcessBench: Identifying Process Errors in Mathematical Reasoning.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving ProcessBench: Identifying Process Errors in Mathematical Reasoning

Reference 44

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T06:40:28.275289Z digest=sha256:ae3d21fa4b41a865253679254fce7c3bf988cd138beb43c2f301e8bd5dd64318

Observation 4e9bcd08-b089-48c3-8c6d-c1f9be82ef9f · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 45

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source=pdf_text observed=2026-08-04T06:40:28.349094Z digest=sha256:df766548a0174f7d1adbfca5e302b3c33cc919a05d42a3184c34fad753797544

Observation 2e3f882a-6262-46a8-8af9-8937dd02f28a · outbound

This paper cites Solving Formal Math Problems by Decomposition and Iterative Reflection.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Solving Formal Math Problems by Decomposition and Iterative Reflection

Reference 46

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source=pdf_text observed=2026-08-04T06:40:28.465639Z digest=sha256:0f3535f593114d2feac67194041f0c5fc37600f33894991aa151073b41162c82

Observation 1e32ba23-e977-4d6d-861d-4a76e99e4246 · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving TTRL: Test-Time Reinforcement Learning

Reference 47

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no resolver link, observed 2026-08-04T06:40:28.581624Z

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source=pdf_text observed=2026-08-04T06:40:28.581624Z digest=sha256:0b0dd0a7a2455e746b84ad6d69af41d14d19406bf27e9619c1f36b2a7f04e542

Observation 9d94b487-8f8e-44e6-8fe8-f3171af6113b · outbound

This paper cites The scientific ideas, methodology, analyses, and conclusions were entirely developed by the authors, while the LLMs assisted only in improving clarity and readability of the text.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving The scientific ideas, methodology, analyses, and conclusions were entirely developed by the authors, while the LLMs assisted only in improving clarity and readability of the text

Reference 50

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source=pdf_text observed=2026-08-04T06:40:28.699011Z digest=sha256:2dc5990ffe382e5f15fc7a2aeb52b131851c57de3205d603a63223b7704920e8

Observation aba29485-3414-42eb-b095-8d676f0eee38 · outbound

This paper cites * The final answer is secondary to the correctness of the derivation.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving * The final answer is secondary to the correctness of the derivation

Reference 51

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source=pdf_text observed=2026-08-04T06:40:28.856946Z digest=sha256:965da6962f2e694d33629c2c12ecbafca187774e379ec0adbe62871124b9c8c9

Observation c2e5f316-f9ae-4477-9ad1-67ef353dd8f7 · outbound

This paper cites * If you cannot provide a complete solution, you must provide any significant ˓→partial results that you can prove with full rigor.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving * If you cannot provide a complete solution, you must provide any significant ˓→partial results that you can prove with full rigor

Reference 52

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T06:40:28.911587Z digest=sha256:e85951628d90885b636a8e4498f365ae412a1848e7cf1d71020f4bd9a81c9236

Observation 2c441329-c712-4fdf-a2ab-122500e0be93 · outbound

This paper cites I have found a complete ˓→solution. The answer is.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving I have found a complete ˓→solution. The answer is

Reference 53

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source=pdf_text observed=2026-08-04T06:40:28.981973Z digest=sha256:5458f513656b85a6f9af3c7915eedb4f0912825cd0fe8e04bbf09152d7414dce

Observation 21cf8029-2865-44e1-99e9-06e352a4db53 · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 54

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source=pdf_text observed=2026-08-04T06:40:29.036476Z digest=sha256:e31c4958e57e02b782513eee485b164ac9f5cbd342536e88863a0fbc3ec5f03c

Observation 0327cfc5-087b-4c27-b6e8-03e36f0179c5 · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-04T06:40:29.108465Z digest=sha256:f64b3aa4e60b3082caa5691c88baf1549d24762171edd5422bed5a6dd5c181fc

Observation fc01cb61-3b3a-4d6c-9874-01db9a423a62 · outbound

This paper cites **Your output must adhere to the following principles and format:** #### **A.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving **Your output must adhere to the following principles and format:** #### **A

Reference 56

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source=pdf_text observed=2026-08-04T06:40:29.167770Z digest=sha256:2e422eae5512d1f7487fcc159d2af11aa659ce7196670710c91a5825133f7800

Observation 58a4399b-03cb-45fe-bd37-aeebf37aa015 · outbound

This paper cites Do not include lemmas from the ‘Provided Lemmas‘ if the model ˓→utilises them.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Do not include lemmas from the ‘Provided Lemmas‘ if the model ˓→utilises them

Reference 57

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source=pdf_text observed=2026-08-04T06:40:29.210199Z digest=sha256:4e2a0a49eda2d226784cefb5506e43239616d174a3c2b911bb82eb042f70ca91

Observation 167a5099-19e9-44c8-a8b0-57467b6751c5 · outbound

This paper cites #### **B.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving #### **B

Reference 58

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source=pdf_text observed=2026-08-04T06:40:29.283839Z digest=sha256:36f57a72e97925c5718a17a1a7e3aaa928334b183fe40b2c1f50861690557e9f

Observation 76dd74b7-a8cb-49b0-abd4-61bce7dc90e4 · outbound

This paper cites The number of ‘<lemma>...</lemma>‘ environments must match the ˓→number of lemmas extracted in this round.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving The number of ‘<lemma>...</lemma>‘ environments must match the ˓→number of lemmas extracted in this round

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:29.338359Z digest=sha256:28568ad61b693294816678081a6f5f6158f52e6ba7deaf1f31252bb8acd8f50b

Observation 234b8392-8a1d-4c6c-84b3-471cc6309105 · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 60

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source=pdf_text observed=2026-08-04T06:40:29.414236Z digest=sha256:0b97e588555de10420ed7cefb35fc0a527be8c08d230498f6ba5e83c9a0ae9d3

Observation 90e99fdb-137e-414b-b7ff-7434b1c24b8d · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 61

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no resolver link, observed 2026-08-04T06:40:29.424855Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:29.424855Z digest=sha256:4bba83856a019e7b4ffc5fc663758645cbc83884692e262a22df0b65fd45d38d

Observation 4782ea6f-c436-4a6c-9bb3-bdd4f595c82c · outbound

This paper cites - A key part of your evaluation is to verify that any use of a lemma from the Provided ˓→Lemmas library is correctly applied and that its preconditions are satisfied.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving - A key part of your evaluation is to verify that any use of a lemma from the Provided ˓→Lemmas library is correctly applied and that its preconditions are satisfied

Reference 62

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:29.558196Z digest=sha256:5e910570676391636d3fc43d93674b89fdb1bba247cdb8b1e31e65d1a2d57dda

Observation 86ec3dbb-a847-4be4-8be6-d1cb00e8079a · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 63

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no resolver link, observed 2026-08-04T06:40:29.721995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:29.721995Z digest=sha256:f979eb5206baa48f1e6d4e83735f495850d2606299b071830979a3885504a731

Observation 0853bf74-cb15-434a-b4ad-b93c5f1bf5ff · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:29.870236Z digest=sha256:54f98db0b8f5e5442edf3a286ac29b70622e97aabb4b860e82b5209fa001bad4

Observation 342af898-8b81-49fd-b8f0-3f3c45e78d86 · outbound

This paper cites I have not found a complete solution.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving I have not found a complete solution

Reference 65

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no resolver link, observed 2026-08-04T06:40:30.004970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:30.004970Z digest=sha256:21f23a3e9240be6c3e49613ba922b55f3773c00a9b9d8d0de0e45ebf08469f14

Observation 40df3174-8bab-4666-bd82-5a12c079db0e · outbound

This paper cites Isosceles-Free Sets Three points form an isosceles triangle if and only if one of them is equidistant from the other two.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Isosceles-Free Sets Three points form an isosceles triangle if and only if one of them is equidistant from the other two

Reference 66

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no resolver link, observed 2026-08-04T06:40:30.086888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:30.086888Z digest=sha256:bc201f357311641f86dba786bd38d1e4f3dcd125146b3e8898278a8db75c2a8e

Observation 9496281c-b160-4740-aba9-22e202588db8 · outbound

This paper cites Hence,(0,1)/∈𝒯.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Hence,(0,1)/∈𝒯

Reference 67

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no resolver link, observed 2026-08-04T06:40:30.140719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:30.140719Z digest=sha256:005d286f901a01f9de1b47de11d3f91503ff332b9c93dc478368da624a8bea1c

Observation 63a6d8fd-2927-4f0d-81c1-0c5092177c9d · outbound

This paper cites an unresolved cited work.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Unresolved cited work

Reference 2023

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no resolver link, observed 2026-08-04T06:40:24.228569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:24.228569Z digest=sha256:c7825b3008779cb859ff069c4b44e19adcc45a0a06576eafcf5537615ee991cb

Observation 7dcb72e0-1c50-4f99-8526-881157608874 · outbound

This paper cites Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving.

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving

Reference 2025

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no resolver link, observed 2026-08-04T06:40:25.051327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:40:25.051327Z digest=sha256:c9c9c985e62dc30ee986296d09cd85189799aab7cd2cac06cef21f6cdd463695

Pith citing papers

No inbound Pith citation observations are available.