Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-13T10:07:53.748795Z
Paper Citation Record · LEDGER
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
As of 7 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 98 inbound Pith citation observations for arXiv:2309.12284.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:28:35.100407Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
85 of 85 outbound references displayed
- verified exact34
- verified fuzzy25
- unresolved25
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
28
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 9b5516cd-0ceb-4a1e-8a4b-ea78295743f4 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b2a8f102-e69d-48b9-a3e9-75e754996539 · outbound
This paper cites PaLM 2 Technical Report.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models PaLM 2 Technical Report
Reference 2
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 600a086b-8139-48b5-afba-78b8f8032c2f · outbound
This paper cites Azerbayev, H.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Azerbayev, H
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e6274441-00b0-476a-aef2-18d997bcf154 · outbound
This paper cites Baichuan 2.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Baichuan 2
Reference 4
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d0a87732-4891-45ab-aa20-704b30dbab48 · outbound
This paper cites A is B” Fail to Learn “B is A.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models A is B” Fail to Learn “B is A
Reference 5
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6c73a10c-b19d-4f42-89b6-bbb1b2d90002 · outbound
This paper cites Submodularity In Machine Learning and Artificial Intelligence.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Submodularity In Machine Learning and Artificial Intelligence
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.794000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 19c3fa35-21f4-4537-9247-737f87d5b788 · outbound
This paper cites Brown, B.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Brown, B
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ed5ea7e5-b033-4bab-a875-b2100c4b73a4 · outbound
This paper cites Evaluating Large Language Models Trained on Code.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Evaluating Large Language Models Trained on Code
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.869141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 18d824d7-da72-4cb1-9ace-f724755f3d6f · outbound
This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.877670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7b75bf82-c5f9-4b14-a2f3-8f4a0f5fae15 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4e7710f4-227f-487b-af04-5198c4ee1b5c · outbound
This paper cites Chiang, Z.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Chiang, Z
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0e073b85-2ae3-42aa-b1ef-974681aefb17 · outbound
This paper cites PaLM: Scaling Language Modeling with Pathways.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models PaLM: Scaling Language Modeling with Pathways
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.828673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6af93e4a-93a1-445d-8ef5-c5993371eca4 · outbound
This paper cites Training Verifiers to Solve Math Word Problems.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Training Verifiers to Solve Math Word Problems
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.831736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 12365b19-259d-4775-b583-f59c0af182f2 · outbound
This paper cites Evaluating Language Models for Mathematics through Interactions.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Evaluating Language Models for Mathematics through Interactions
Reference 14
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bd7c1123-24c5-455a-aa74-d069b83df4f8 · outbound
This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models QLoRA: Efficient Finetuning of Quantized LLMs
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.860343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 614b027a-ea03-47a1-8c8d-d14843b11f3b · outbound
This paper cites Devlin, M.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Devlin, M
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation aa35f7cf-f02b-4e84-a9fe-0dfbe89c995e · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 17
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f639bcf9-cb45-47ec-9cad-4a87e273fce0 · outbound
This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T07:36:55.300854Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7be5d00c-78e1-4417-9ecc-0604ee4a08ab · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3e7b4c3f-b48e-4011-8d84-5f41d1df87d3 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 40158dd1-7a4b-45c7-95ec-723e75d6ef76 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 21
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 01fc296e-b4f6-44e0-bdb6-5772e8976add · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation af20ed75-96ae-4772-9ba5-a520768890a8 · outbound
This paper cites Hendrycks, C.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Hendrycks, C
Reference 23
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 473cb540-bf52-4abd-b00a-76b3311d7993 · outbound
This paper cites Distilling the Knowledge in a Neural Network.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Distilling the Knowledge in a Neural Network
Reference 24
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 49b9cf86-f815-42ff-b06b-aec00fad2eb3 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d664de70-e3aa-47be-95b9-2ab98fccbf0e · outbound
This paper cites Hsieh, C.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Hsieh, C
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8a4913a3-6ac8-468b-8220-cf50e257df7e · outbound
This paper cites Large Language Models Can Self-Improve.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Large Language Models Can Self-Improve
Reference 27
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 90ccabe4-0827-48db-843d-c7b220f4abf9 · outbound
This paper cites Imani, L.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Imani, L
Reference 28
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 264286c5-8e63-44f2-85c5-e06b084de26f · outbound
This paper cites InternLM: A Multilingual Language Model with Progressively Enhanced Capabilities.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models InternLM: A Multilingual Language Model with Progressively Enhanced Capabilities
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 992a3921-ad37-460a-8a64-5b880a650afb · outbound
This paper cites Mistral 7B.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Mistral 7B
Reference 30
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c167e540-09ec-4c59-bac3-b6edcdbe38cc · outbound
This paper cites BYOM: Building Your Own Multi-Task Model For Free.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models BYOM: Building Your Own Multi-Task Model For Free
Reference 31
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bd0017ea-fd92-400f-8036-3fc941bf68cd · outbound
This paper cites Forward-Backward Reasoning in Large Language Models for Mathematical Verification.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Forward-Backward Reasoning in Large Language Models for Mathematical Verification
Reference 32
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cd32a8ba-80aa-4d63-8ca3-011b88b995ff · outbound
This paper cites Jiang, Y.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Jiang, Y
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3222649a-acc9-4f31-b306-b6d8d933f2d4 · outbound
This paper cites Generalization in anti-causal learning.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Generalization in anti-causal learning
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ed413fb0-fa84-49d0-9ada-8c2ea9870e59 · outbound
This paper cites Lewkowycz, A.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Lewkowycz, A
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5e116516-d824-4f75-926e-111b81300fd1 · outbound
This paper cites StarCoder: may the source be with you!.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models StarCoder: may the source be with you!
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.806668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 935c42e5-59a6-4ab1-ab5a-7fabe229d4f1 · outbound
This paper cites Explanations from Large Language Models Make Small Reasoners Better.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Explanations from Large Language Models Make Small Reasoners Better
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.819418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c1692f5c-b109-41c5-92c8-78d6cff6cb1f · outbound
This paper cites DeepInception: Hypnotize Large Language Model to Be Jailbreaker.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models DeepInception: Hypnotize Large Language Model to Be Jailbreaker
Reference 38
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 23e50c2b-bede-475d-8bdc-bc296487a670 · outbound
This paper cites Lightman, V.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Lightman, V
Reference 39
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 73193517-b8a4-44d3-86d4-98ee48c1bd01 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 40
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 615a6a42-b8e0-461f-b908-ad07a8c3093e · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cedaf0e7-8209-4190-b948-8e2bbcbadc02 · outbound
This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.852306Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e758f181-367d-467b-a8ee-ddc556a0ce31 · outbound
This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T04:00:08.752459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a9157e86-a6ac-47df-8a00-5fb33fc1a567 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 44
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b98793db-6c06-48d9-aa23-9a61269ab1a8 · outbound
This paper cites Magister, J.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Magister, J
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.960893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2cabdda0-928c-42f8-8775-028b8a8be8ec · outbound
This paper cites When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.863501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 86ce4c1b-8b7f-4e96-b847-30defc39be9b · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-05-13T10:07:53.962546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation df5a854b-b475-44fa-bfe7-e6ace830fe5a · outbound
This paper cites Mirzadeh, M.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Mirzadeh, M
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.964399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f15bb286-27dd-4b84-8428-535c38f16142 · outbound
This paper cites Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs
Reference 49
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 231fe091-56a2-479f-b37c-d36b1e884f90 · outbound
This paper cites Platypus: Quick, Cheap, and Powerful Refinement of LLMs.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Platypus: Quick, Cheap, and Powerful Refinement of LLMs
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.881022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation eb99afa5-b6a9-48cc-85e0-6b54b12cc1c3 · outbound
This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T17:03:10.517825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 701a21ce-fef7-423e-9d69-2b6693d9d4e4 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 52
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 914544dd-46b1-46e1-9403-4882fc930317 · outbound
This paper cites GPT-3.5-Turbo.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models GPT-3.5-Turbo
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.969366Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 15aa0e07-ac2a-4cc1-8162-ec015340ccd6 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 54
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1aa722dc-10c1-4a37-9425-2ebd04da228f · outbound
This paper cites Ouyang, J.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Ouyang, J
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.972706Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 573a94d8-a89d-4b72-9948-74dfd6da9594 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 56
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b5e85227-85c0-4d74-9ef7-966d83885397 · outbound
This paper cites The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only
Reference 57
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 317aa13a-dfcd-446f-b0e8-605cfc22b67e · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 58
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7012c8fe-393e-44e2-9bec-dd519de6a49e · outbound
This paper cites Radford, J.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Radford, J
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.885778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3de790c8-b874-4233-bec8-398ffbef2e53 · outbound
This paper cites Raffel, N.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Raffel, N
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.888171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7b3e5844-4c2e-442b-be9c-a51a1152ccdf · outbound
This paper cites Code Llama: Open Foundation Models for Code.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Code Llama: Open Foundation Models for Code
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.810357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a289e46e-4007-40b0-8ae8-cb15c670e065 · outbound
This paper cites Proximal Policy Optimization Algorithms.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Proximal Policy Optimization Algorithms
Reference 62
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.815459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ebb044f7-5cda-414f-8f89-0cb78f941dab · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 63
- Resolution
- unresolved
- raw_fallback, observed 2026-05-13T10:07:53.890213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2abd50e7-85bf-411e-b8a8-e83acaa224b0 · outbound
This paper cites Shridhar, A.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Shridhar, A
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.892213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7f806829-9776-4315-9332-00c544519377 · outbound
This paper cites A Survey of Reasoning with Foundation Models.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models A Survey of Reasoning with Foundation Models
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.825483Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8ca7f434-3d95-40dc-875f-5f52a7dac22f · outbound
This paper cites Talmor, J.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Talmor, J
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.894257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dadd1940-8ad9-4a7b-b333-2788dd2248bb · outbound
This paper cites Taori, I.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Taori, I
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.896164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 604f1641-563f-44c2-a86c-26fa62204f92 · outbound
This paper cites Galactica: A Large Language Model for Science.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Galactica: A Large Language Model for Science
Reference 68
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.834848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 811ca10f-e44a-4a57-b2ab-f2203d227049 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models LLaMA: Open and Efficient Foundation Language Models
Reference 69
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.837474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5bd00b37-7b8c-412f-92d1-a7f130b07410 · outbound
This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 70
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T10:07:53.840131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 21b40ced-45c8-49a8-afd4-265206464d40 · outbound
This paper cites Wang and A.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Wang and A
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.898099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c313013d-4410-4ccf-98b7-131ae7229763 · outbound
This paper cites Making Large Language Models Better Reasoners with Alignment.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Making Large Language Models Better Reasoners with Alignment
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.846541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 85b85026-1180-401e-b453-cebdd2a380ac · outbound
This paper cites Dataset Distillation.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Dataset Distillation
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T23:53:20.506326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ce1bc534-a2d3-4e32-b5b9-0b6be8104f15 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 74
- Resolution
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- raw_fallback, observed 2026-05-13T10:07:53.899920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 696ea7d7-dfd2-44a6-bb71-534ea58f9cda · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 75
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e354e926-89db-4687-a9c9-481fe4aca7fb · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 76
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 144676fc-cd2c-47a1-914f-2c5a9b87bb6d · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 77
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1fd926bc-5f7c-4cbe-8987-9f9013475e52 · outbound
This paper cites Xiong, Z.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Xiong, Z
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T10:07:53.907746Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f438b39c-7a7d-4c5c-af6b-45aca5aa9f5a · outbound
This paper cites Scaling Relationship on Learning Mathematical Reasoning with Large Language Models.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T00:22:11.212173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 82cd76fd-f6a5-4b6d-a877-8f352d58f4a2 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 80
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e24fe130-d775-406b-a5ea-88c22b462b63 · outbound
This paper cites GLM-130B: An Open Bilingual Pre-trained Model.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models GLM-130B: An Open Bilingual Pre-trained Model
Reference 81
- Resolution
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- arxiv_id, observed 2026-05-14T17:41:34.452877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2a97f1a0-58e8-46b5-9e4a-ce36d01af29c · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 82
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6b8b815c-9bc1-4c23-a56f-3b3c34f40f99 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 83
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ccc4ea19-55d7-416a-97b3-c43efc7792dc · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 84
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 95bfa1f2-cd52-4e4a-9a7c-15b1f5d138f7 · outbound
This paper cites an unresolved cited work.
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models Unresolved cited work
Reference 85
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
Observation f8b7c087-a5d5-46ed-8f25-de745c73d67d · inbound
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MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 67
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2ff305ce-43c3-4e3b-a3dd-136b288bdc65 · inbound
Llemma: An Open Language Model For Mathematics cites this paper.
Llemma: An Open Language Model For Mathematics MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 200
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 327ed800-460c-40b8-a6d8-06533fcc7d63 · inbound
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations cites this paper.
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 91
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation da2bce1b-20cd-426d-a3ee-32d2e51863b2 · inbound
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism cites this paper.
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 87
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e3432349-9f7e-424a-8f02-120244180c1d · inbound
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models cites this paper.
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 56
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 199aa8db-4689-4756-ba46-a7906474a728 · inbound
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites cites this paper.
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 132
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 71829804-8eb5-4b3b-9223-07cee86e6432 · inbound
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model cites this paper.
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 76
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation de5c3b54-c989-4ab8-ac8f-dda1be073b83 · inbound
Improve Mathematical Reasoning in Language Models by Automated Process Supervision cites this paper.
Improve Mathematical Reasoning in Language Models by Automated Process Supervision MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 25
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 859f9129-73d9-43d8-84d4-4772f4109909 · inbound
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs cites this paper.
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 32
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d65a5ea4-362f-4056-8f6e-888cf512b8f6 · inbound
Scaling Synthetic Data Creation with 1,000,000,000 Personas cites this paper.
Scaling Synthetic Data Creation with 1,000,000,000 Personas MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 27
- Resolution
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- local_arxiv, observed 2026-05-16T00:03:55.800476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 668c80a0-6ad9-4535-ad92-e947a1915c42 · inbound
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output cites this paper.
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 162
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a9c7edb4-2ee7-4b63-88f8-815946a23316 · inbound
Training and Evaluating Language Models with Template-based Data Generation cites this paper.
Training and Evaluating Language Models with Template-based Data Generation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 11
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6ffbdba2-f8f5-4b44-a803-cd3d99ae2582 · inbound
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling cites this paper.
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 282
- Resolution
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- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f49278d1-d160-465f-97c1-04d1f90fe18a · inbound
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding cites this paper.
DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 103
- Resolution
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- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fe1bf6d8-eacf-4c53-8dae-2ad67378b17e · inbound
Efficient Reasoning with Hidden Thinking cites this paper.
Efficient Reasoning with Hidden Thinking MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 26
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 329f4f5c-63ae-48d7-a321-bae7b65940ed · inbound
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model cites this paper.
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 248
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 35a2abee-78fb-45e7-b177-5b7609e5fdff · inbound
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.
Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 237
- Resolution
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- local_arxiv, observed 2026-05-23T04:32:33.194629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 190fb115-a65f-44ad-9b90-9af36f5d438c · inbound
FoNE: Precise Single-Token Number Embeddings via Fourier Features cites this paper.
FoNE: Precise Single-Token Number Embeddings via Fourier Features MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T03:12:28.740708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 19aa3187-45cf-4a28-b167-4aaf3cf33b53 · inbound
MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation cites this paper.
MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T10:52:15.101879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fc0b14a4-7b7e-4494-a92b-c81758895e40 · inbound
Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models cites this paper.
Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 21
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f47f458-6a09-4c7a-af59-185ffdbe48e0 · inbound
PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models cites this paper.
PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 33
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7455639d-3a6d-4ee7-8b6f-1bbbd092c814 · inbound
Data Diversification Methods In Alignment Enhance Math Performance In LLMs cites this paper.
Data Diversification Methods In Alignment Enhance Math Performance In LLMs MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 47
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ea6cf13-6a27-4958-be72-b60ebcf40fba · inbound
Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? cites this paper.
Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 47
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 203a912c-06cb-4a22-a508-fbea9047bb0b · inbound
BlueLM-2.5-3B Technical Report cites this paper.
BlueLM-2.5-3B Technical Report MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 66
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c760db8a-a1f2-4bc5-bc80-e5d7ee1535db · inbound
Multi-Actor Generative Artificial Intelligence as a Game Engine cites this paper.
Multi-Actor Generative Artificial Intelligence as a Game Engine MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 22
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb7676ad-1e54-48f8-9211-27e788a050bd · inbound
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix cites this paper.
Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 38
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33c867b7-c587-4172-a55b-d3a85925e403 · inbound
Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models cites this paper.
Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 83
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 443b2f42-9b08-4ab9-9e70-1fa93b354cf9 · inbound
Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training cites this paper.
Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 48
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7ba80e46-2301-41e1-bb67-fc584efc11cc · inbound
League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models cites this paper.
League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 48
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f7f87a91-8e66-4a32-a3f1-9f900acf6e11 · inbound
InternBootcamp Technical Report: Boosting LLM Reasoning with Verifiable Task Scaling cites this paper.
InternBootcamp Technical Report: Boosting LLM Reasoning with Verifiable Task Scaling MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 55
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T22:34:23.984357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2c62a03b-ada0-4784-9116-5c54e452a17d · inbound
RTTC: Reward-Guided Collaborative Test-Time Compute cites this paper.
RTTC: Reward-Guided Collaborative Test-Time Compute MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02d5e798-ba01-4390-9b71-5a4b14975710 · inbound
Fin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models cites this paper.
Fin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 27
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T22:41:53.038801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ab0aef57-d224-447b-a6f4-6b16c43a11a5 · inbound
Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness cites this paper.
Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 20
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff376a3a-b949-4ec1-a0a2-3df40d6fd30d · inbound
Mitigating Catastrophic Forgetting in Large Language Models with Forgetting-aware Pruning cites this paper.
Mitigating Catastrophic Forgetting in Large Language Models with Forgetting-aware Pruning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 37
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 95449c0e-42c4-4fa4-88cb-cd9e41843a3c · inbound
BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning cites this paper.
BoHA: Blockwise Hadamard Product Adaptation for Parameter-Efficient Fine-Tuning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T13:51:26.005222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fc2263e9-1162-4226-9374-bdcde78e5f40 · inbound
Understanding the Ability of LLMs to Handle Character-Level Perturbation cites this paper.
Understanding the Ability of LLMs to Handle Character-Level Perturbation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 854bce9b-1cbb-49b8-b7c7-89af84ebd1e1 · inbound
HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs cites this paper.
HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 3
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d23a962-8a37-4b7c-a1a9-462679af17bd · inbound
Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning cites this paper.
Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T22:43:37.937417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3925c8d7-0178-4be7-8d1c-2687db53aacf · inbound
Hard Negative Sample-Augmented DPO Post-Training for Small Language Models cites this paper.
Hard Negative Sample-Augmented DPO Post-Training for Small Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T21:58:35.704197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f5263d87-9829-4f62-8d96-3742f0f410ec · inbound
NVIDIA Nemotron 3: Efficient and Open Intelligence cites this paper.
NVIDIA Nemotron 3: Efficient and Open Intelligence MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 174
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 53147291-666e-4dcb-813a-efbcc4a5f533 · inbound
Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.
Unifying Learning Dynamics and Generalization in Transformers Scaling Law MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 59
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f796b6cc-370a-44bb-b192-68665ea90df1 · inbound
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models cites this paper.
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 27
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f22ce01-46fe-482d-9749-82dbdc7fe598 · inbound
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 258
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7155811c-4818-41e2-a2e4-f976c7d326f2 · inbound
Vision-aligned Latent Reasoning for Multi-modal Large Language Model cites this paper.
Vision-aligned Latent Reasoning for Multi-modal Large Language Model MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3132e48e-c34e-49b0-94bd-673564d26aef · inbound
Multi-Token Prediction via Self-Distillation cites this paper.
Multi-Token Prediction via Self-Distillation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T06:47:28.317574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6489fe45-2fee-419b-ab7a-58ca6bf22d65 · inbound
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 35
- Resolution
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- local_arxiv, observed 2026-05-21T13:44:11.387380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ed337479-3dd2-4505-9de1-f447ec5fd921 · inbound
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 35
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58d1207b-b7a4-4014-8ce7-037eecd9ee4b · inbound
Model soups need only one ingredient cites this paper.
Model soups need only one ingredient MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 20
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1359f7b3-643c-4fb3-857c-af0cdd140d64 · inbound
Weight Decay Improves Language Model Plasticity cites this paper.
Weight Decay Improves Language Model Plasticity MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 27
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 856d3786-7708-46a3-83cc-13953ef9e013 · inbound
A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search cites this paper.
A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 38
- Resolution
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- no resolver link, observed 2026-08-03T09:45:45.383707Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aecf69e4-28d1-4e6a-9c77-84e8126e8ae4 · inbound
Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation cites this paper.
Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 24
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 231460e8-7272-4774-9ecd-e7815e9ebc42 · inbound
Sensitivity-Positional Co-Localization in GQA Transformers cites this paper.
Sensitivity-Positional Co-Localization in GQA Transformers MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 15
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dcfa3496-d404-433a-984d-9a363d268ef3 · inbound
Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation cites this paper.
Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 17
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e1cfa49a-56bb-4d14-b9a5-8bc2bc2d0b03 · inbound
HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models cites this paper.
HintMR: Eliciting Stronger Mathematical Reasoning in Small Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8b7fbc11-44cd-45f8-b907-7933eff2c0b0 · inbound
TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.
TLoRA: Task-aware Low Rank Adaptation of Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 76
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 76648abb-bfc9-479e-80ef-95841fc52c1d · inbound
Rethinking Wireless Communications through Formal Mathematical AI Reasoning cites this paper.
Rethinking Wireless Communications through Formal Mathematical AI Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation edcffe1b-49f5-45da-9a0f-15afe9c07b0d · inbound
Post-Optimization Adaptive Rank Allocation for LoRA cites this paper.
Post-Optimization Adaptive Rank Allocation for LoRA MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6c4a8568-c94b-4028-9892-98e71cfd7413 · inbound
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting cites this paper.
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 19
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fcea2bf9-6121-401e-8ab6-96ca8f04e0b0 · inbound
Compress Then Adapt? No, Do It Together via Task-aware Union of Subspaces cites this paper.
Compress Then Adapt? No, Do It Together via Task-aware Union of Subspaces MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 49
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bda9fc62-3624-4288-afbc-fade165f9cce · inbound
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training cites this paper.
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 438db7d0-dc20-437b-bae5-ba1902898125 · inbound
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training cites this paper.
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a683d2b9-af54-4ed7-965c-a21712bc7e1a · inbound
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training cites this paper.
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T23:45:07.560013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 98b5b407-f33f-47f6-8c58-93a479dc6124 · inbound
You Snooze, You Lose: Automatic Safety Alignment Restoration through Neural Weight Translation cites this paper.
You Snooze, You Lose: Automatic Safety Alignment Restoration through Neural Weight Translation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 143
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d3d5bb8c-4047-459c-a3ea-0b39b7b2996e · inbound
Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing cites this paper.
Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e6f7b949-6b15-4af6-acd9-3f4864d8c9d6 · inbound
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation aa135b7d-0100-4ef1-afdb-290f6b5e1085 · inbound
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 01696423-e06e-4da9-a6af-c12f5335307a · inbound
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.
Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 5
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T22:39:10.594590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f9e4fb2e-0950-4211-b854-5b50d1359a24 · inbound
Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less cites this paper.
Optimizer-Model Consistency: Full Finetuning with the Same Optimizer as Pretraining Forgets Less MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0b86f74d-d96c-400e-a623-ca3696abe74f · inbound
NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.
NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 32
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9bceca25-203e-4324-8ba3-aa2ce661afc1 · inbound
Generating Leakage-Free Benchmarks for Robust RAG Evaluation cites this paper.
Generating Leakage-Free Benchmarks for Robust RAG Evaluation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation de46a5c0-f3ad-44d4-a14f-53268f204cbe · inbound
Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation cites this paper.
Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T10:07:53.977132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 45229171-d927-4238-b537-6da084e2ea6f · inbound
LoCO: Low-rank Compositional Rotation Fine-tuning cites this paper.
LoCO: Low-rank Compositional Rotation Fine-tuning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 51
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:53:42.624097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation be133cc4-9ae9-4616-9827-6b91b1203b78 · inbound
Strategic Over-Parameterization for Generalizable Low-Rank Adaptation cites this paper.
Strategic Over-Parameterization for Generalizable Low-Rank Adaptation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T20:13:44.011536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 50eefc58-44f2-4f05-aa45-01e797412e0a · inbound
Self-Supervised On-Policy Distillation for Reasoning Language Models cites this paper.
Self-Supervised On-Policy Distillation for Reasoning Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 72
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T14:43:22.245111Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 764b1470-688e-4500-aeb2-3480a03a15cf · inbound
Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning cites this paper.
Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T05:59:41.151064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c8e29f48-df1d-4f68-8b60-40175d456b88 · inbound
FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning cites this paper.
FuRA: Full-Rank Parameter-Efficient Fine-Tuning with Spectral Preconditioning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 51
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T05:40:23.862219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bc00dc7a-48e2-47cf-9fe2-c8bca6586211 · inbound
Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis cites this paper.
Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 4
- Resolution
- malformed identifier
- local_arxiv, observed 2026-06-29T22:13:59.343734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0202c38d-1491-45c9-8f5f-7b983f47a96d · inbound
Transformers Provably Learn to Internalize Chain-of-Thought cites this paper.
Transformers Provably Learn to Internalize Chain-of-Thought MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T14:33:30.605507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 21f0ba61-fcf2-4370-a689-044654b7424e · inbound
Tailoring the Curriculum: Student-Centered Reasoning Distillation via Dynamic Data-Model Compatibility cites this paper.
Tailoring the Curriculum: Student-Centered Reasoning Distillation via Dynamic Data-Model Compatibility MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T08:03:14.663338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation adfc3eb6-2746-460a-b1fd-6ecd3f6d3254 · inbound
FedSmoothLoRA: Toward Smoother and Faster Convergence in Federated Low-Rank Adaptation cites this paper.
FedSmoothLoRA: Toward Smoother and Faster Convergence in Federated Low-Rank Adaptation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T08:13:15.255471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d58a7fab-7ff5-4bec-b62d-0eafddd34a6f · inbound
Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization cites this paper.
Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T08:43:15.280478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7b68a28e-f841-4b83-84bc-72a355a1242d · inbound
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts cites this paper.
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 52
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T21:16:14.408979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 431f8ed2-81c7-4e09-8b72-681d5538cb81 · inbound
Test-Time Training for Zero-Resource Dense Retrieval Reranking cites this paper.
Test-Time Training for Zero-Resource Dense Retrieval Reranking MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 25
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T21:36:14.728621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f99f0ac3-ed1d-4c05-a98b-83c5f5820e43 · inbound
SafeSteer: Localized On-Policy Distillation for Efficient Safety Alignment cites this paper.
SafeSteer: Localized On-Policy Distillation for Efficient Safety Alignment MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 93
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T23:06:20.958496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e81eeeaa-3318-40e9-a9d5-af111e315d9c · inbound
RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning cites this paper.
RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-27T22:31:21.127351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 11e160e5-0b9d-4e17-91f0-7de883bba3f5 · inbound
HARP: Efficient Data Selection for Finetuning Large Language Models cites this paper.
HARP: Efficient Data Selection for Finetuning Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 37
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T16:17:09.386612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 076dbd29-b118-4aa1-a9e3-bb3127778516 · inbound
CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning cites this paper.
CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 97
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T10:25:41.594552Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 271709c8-6f57-4f09-a498-2d993678b5a2 · inbound
Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization cites this paper.
Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 55
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T16:17:08.555743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2331335f-3480-4e22-8dc4-3dc510d2f5eb · inbound
EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning cites this paper.
EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T17:28:44.011356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 67ecf999-b31c-40ea-8469-d057a6d04b51 · inbound
CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation cites this paper.
CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T09:43:36.303603Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63cfae02-205a-4c00-9bb2-b87f5ac3acc7 · inbound
Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.
Multi-Turn On-Policy Distillation with Prefix Replay MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 196
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T13:53:36.775836Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c4e5118-1651-412f-a1e7-b0fbbd0d4d4c · inbound
Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.
Multi-Turn On-Policy Distillation with Prefix Replay MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 197
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T08:40:55.260416Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c17149ee-5b6b-4ec3-ab29-7cea4b5909da · inbound
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:51:03.291898Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2859c2c-da61-4cee-9b3a-5ac8500ab965 · inbound
Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models cites this paper.
Structured Synthetic Reasoning Data for Arithmetic Fine-Tuning of Small Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T13:26:29.579525Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b95bd498-13fe-499c-a1c0-3e9ddb67583b · inbound
The Blessing of Dimensionality: How Near-Orthogonality in High-Dimensional Spaces Explains Temporal Portability cites this paper.
The Blessing of Dimensionality: How Near-Orthogonality in High-Dimensional Spaces Explains Temporal Portability MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T10:18:19.974749Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b3f5f4b-6a30-43a8-9330-80c39ef3c116 · inbound
FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts cites this paper.
FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:39:41.609569Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f10cd801-8c47-4813-b616-a332b5c404d4 · inbound
\k{appa}-LoRA: Condition Numbers Reveal Which LoRA Matrices Worth Updating cites this paper.
\k{appa}-LoRA: Condition Numbers Reveal Which LoRA Matrices Worth Updating MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T04:37:44.974876Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad48a7e9-6041-45fb-ae39-a29a3bab8f2a · 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 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.