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Paper Citation Record · LEDGER

DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 inbound Pith citation observations for arXiv:2411.00836.

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

pith.paper-citation-record.v1
2411.00836 v2

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measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 41 of 41 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:26:07.809728Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:48:56.041994Z

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Outbound references

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Pith citing papers

Observation 4794ee11-da2e-46c1-84dc-2d3eaaa2a716 · inbound

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

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:26:07.809728Z digest=sha256:1ff357882d5ff29025e14e53837abb18d55747b80ef1506cc0ee5cec35cc7b41

Observation c2dd2c26-2ff9-4d2e-9eea-9e2b62982ada · inbound

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization cites this paper.

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 41

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arxiv_id, observed 2026-05-16T00:19:20.565097Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T00:19:20.462455Z digest=sha256:82be50e095ec9e0e868480bdff740446499acfc2360a9d7e8e315bea55246686

Observation 54d46fca-135d-447d-8e2c-1e722cc02ab6 · inbound

R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization cites this paper.

R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 57

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arxiv_id, observed 2026-05-16T15:04:22.722652Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T15:04:22.690503Z digest=sha256:46d9642592b11429fae8562802f244dd2740b27f5673d1ede3df611d42225ef4

Observation cae3aea9-046d-48a6-b246-c7d7fac5a7dd · inbound

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models cites this paper.

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 156

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arxiv_id, observed 2026-05-10T13:41:08.033152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T13:41:07.991012Z digest=sha256:f43116c38573090629112cd7a52b6888910e60e1f3e54f4f3921d19ccb2d508d

Observation c1496f25-d005-4f09-80d0-1a64808b027e · inbound

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning cites this paper.

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 31

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arxiv_id, observed 2026-05-11T14:42:56.825358Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T14:42:56.565621Z digest=sha256:1ad2b7f322b6839169d487abb9284e02b37358dad04d92565951e5cd770cdbf8

Observation 5ae7bb7b-10ed-462e-908c-fd816a7b30b4 · inbound

TimeCausality: Evaluating the Causal Ability in Time Dimension for Vision Language Models cites this paper.

TimeCausality: Evaluating the Causal Ability in Time Dimension for Vision Language Models DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 59

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source=arxiv_source observed=2026-08-07T15:21:08.559862Z digest=sha256:6ff0f9eca41e95fffa7aa0c387b684ffbf57c336d2405c9836c5544f1a1edef4

Observation 1b61006d-4166-4d49-ad64-4c018a689bad · inbound

MiMo-VL Technical Report cites this paper.

MiMo-VL Technical Report DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 77

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source=arxiv_source observed=2026-08-07T11:04:14.304184Z digest=sha256:68209f17c3d7f6a686af83fdf55e48b674c91603c482d327d9be6db8b2365f6d

Observation a5bc9403-a0d6-4efd-b92f-bc0e7a252ec1 · inbound

WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning cites this paper.

WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 86

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source=pdf_text observed=2026-08-07T05:27:05.225253Z digest=sha256:68d9ff370b786d27cae7a55d3f65ca6c82c29b801e24f8a51e6c9663d8f70bff

Observation 68b418f4-f233-4f31-b187-9a27584609bf · inbound

MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI cites this paper.

MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 51

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source=pdf_text observed=2026-08-06T21:41:41.103071Z digest=sha256:e3639ea3e45ddf2cf9bd462917fea010c15e4f3ec9f93060aff371172d635f26

Observation b7f21d7b-1304-4d8e-aa23-099a7a46970d · inbound

GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning cites this paper.

GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 74

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arxiv_id, observed 2026-05-11T04:48:27.265524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T04:48:26.355351Z digest=sha256:d4baf3e7d3c05851d08801dbbfcc7c1a130d7d4c346de4f0647f7b1fef01bf0e

Observation 9da45d34-702a-41cc-9fa9-a0241d60580d · inbound

Kwai Keye-VL Technical Report cites this paper.

Kwai Keye-VL Technical Report DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 48

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source=pdf_text observed=2026-08-06T20:45:10.546613Z digest=sha256:89f5a115f140128ffe546155aa80b27e275690ec09558d17498971cca1f6f788

Observation e509b6e9-ec44-41bd-865e-d1e0d170bfc1 · inbound

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset cites this paper.

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 40

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source=pdf_text observed=2026-08-06T20:15:52.701699Z digest=sha256:474fc943784672647d2efd6f375e4d892f85cde50fbea911f894e7d8bd139cff

Observation 78c0a6e1-1605-47cb-86ed-90f98db30e62 · inbound

Position: Reasoning After Perception Means Reasoning Without Vision cites this paper.

Position: Reasoning After Perception Means Reasoning Without Vision DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 58

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no resolver link, observed 2026-08-06T15:26:02.359760Z

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source=arxiv_source observed=2026-08-06T15:26:02.359760Z digest=sha256:f32e47d282ba56493eec5c0c46afbf4a72de4bcab9bfc7d438abd69c5853bc7e

Observation 25648867-0a60-4698-8cd4-62272875f645 · inbound

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning cites this paper.

GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 56

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no resolver link, observed 2026-08-06T00:59:54.936904Z

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source=arxiv_source observed=2026-08-06T00:59:54.936904Z digest=sha256:9fcb12bdaa20418b9f85cecf37cfdb955456a4235279b69998839dc583c8d823

Observation 803706d1-06d3-4b48-8f87-64fdea209998 · inbound

MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models cites this paper.

MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 70

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no resolver link, observed 2026-08-05T23:03:10.178730Z

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source=arxiv_source observed=2026-08-05T23:03:10.178730Z digest=sha256:0cce66d5a746c36c289dc7b197320bec4223f8cf9cce7dc8f87cc0fc38bedef7

Observation 6b2461dd-f50c-4b0b-b157-80895269b884 · inbound

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency cites this paper.

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 190

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arxiv_id, observed 2026-05-10T11:58:59.011849Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T11:58:58.660564Z digest=sha256:b8ea34f31d16e306fd882bb969b1359e811eba6aa0a5280b255a487f66990da3

Observation 9e06aefb-62f4-4a2c-a405-f24a37aebcb5 · inbound

R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning cites this paper.

R-4B: Incentivizing General-Purpose Auto-Thinking Capability in MLLMs via Bi-Mode Annealing and Reinforce Learning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 40

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no resolver link, observed 2026-08-05T14:42:21.125850Z

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source=arxiv_source observed=2026-08-05T14:42:21.125850Z digest=sha256:375fa30f9e39d31925e9d7cc91b090027b61b66c208f35c90090b69f4445a17a

Observation 2a76cfdb-d8cb-4be2-b25b-a98ce65010b4 · inbound

Kwai Keye-VL 1.5 Technical Report cites this paper.

Kwai Keye-VL 1.5 Technical Report DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 43

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no resolver link, observed 2026-08-05T12:28:31.683925Z

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source=pdf_text observed=2026-08-05T12:28:31.683925Z digest=sha256:8ced412e2c6308ac4f57e81df5de3e8ca3142edb54dd338ff2a262cd1d88b97d

Observation 1ff0b8d2-eeb1-4d9b-8ca6-3d5e54c15a04 · inbound

Can Vision-Language Models Solve Visual Math Equations? cites this paper.

Can Vision-Language Models Solve Visual Math Equations? DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 14

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no resolver link, observed 2026-08-04T19:53:10.732656Z

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source=arxiv_source observed=2026-08-04T19:53:10.732656Z digest=sha256:3ccc3f9bce4946686eb623b547f5616a4bd09a6004e025aaab76e7e35c85b5dc

Observation bb89482a-18be-46e9-b761-04106fad767e · inbound

Boosting Reasoning in Large Multimodal Models via Activation Replay cites this paper.

Boosting Reasoning in Large Multimodal Models via Activation Replay DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 68

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arxiv_id, observed 2026-05-17T05:09:04.048673Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T05:05:48.682057Z digest=sha256:ad67c78642b618eadd6fa3393fd7c6626470e032249866ca31a91675a814febb

Observation 3abf123a-2591-4894-920f-4ff320b2353d · inbound

Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization cites this paper.

Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 17

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arxiv_id, observed 2026-05-16T16:08:04.410716Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T16:06:52.052810Z digest=sha256:8a0f8c918ff2e5ea8869d340fea0c6efc3cefd7470553c3d80ff9bbc9c66aaa5

Observation 6ff6ff25-35b0-498f-9c44-152740a151c8 · inbound

ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch cites this paper.

ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 52

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arxiv_id, observed 2026-05-16T13:12:54.723766Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T13:12:01.889341Z digest=sha256:038dbe9668ee0ca7ea416157ddecfe2ced5f48ec64f87bb98ce8ea3da7ad6b18

Observation d81264c5-2706-49e1-bb91-813a388323b3 · inbound

CodePercept: Code-Grounded Visual STEM Perception for MLLMs cites this paper.

CodePercept: Code-Grounded Visual STEM Perception for MLLMs DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 64

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no resolver link, observed 2026-07-14T23:22:13.847876Z

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source=pdf_text observed=2026-07-14T23:22:13.847876Z digest=sha256:3ab9ef3ea0cd2df3af70233caac140120c479a4020870b9fcc60ac8698a0971c

Observation 583be613-923c-472f-96ff-0a2bc5223d62 · inbound

Seed1.8 Model Card: Towards Generalized Real-World Agency cites this paper.

Seed1.8 Model Card: Towards Generalized Real-World Agency DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 98

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arxiv_id, observed 2026-05-15T07:45:14.496421Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T07:44:02.827006Z digest=sha256:fb157767203f99f05df4c87cf4e30aaceee75dab24562e9a40c9fcbd7659ba1c

Observation 367a7780-a059-4402-9a3c-a76e46315220 · inbound

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models cites this paper.

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 58

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arxiv_id, observed 2026-05-11T00:20:53.738571Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T18:35:21.514502Z digest=sha256:6b9b5d63a6d266432e70a0ede1f5a1360fd10db64c7c84e1d7280efb8a385cb1

Observation 7b7096a6-de08-413d-9bd5-22762d1f2f95 · inbound

Why and When Visual Token Pruning Fails? A Study on Relevant Visual Information Shift in MLLMs Decoding cites this paper.

Why and When Visual Token Pruning Fails? A Study on Relevant Visual Information Shift in MLLMs Decoding DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 55

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arxiv_id, observed 2026-05-11T11:31:01.518013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T14:50:37.022338Z digest=sha256:d75fc30b5a9d4f52e5ebe9857d2823d400c2dc25929675f751b0d5362faa9773

Observation a5a5f8eb-ce0c-4d76-8b63-65250ae29914 · inbound

ReaLB: Real-Time Load Balancing for Multimodal MoE Inference cites this paper.

ReaLB: Real-Time Load Balancing for Multimodal MoE Inference DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 2

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arxiv_id, observed 2026-05-12T08:01:29.079542Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T01:23:42.529129Z digest=sha256:2db3ca8339aab825141c96a17576a2eb8bb9ff0595ce1f6122473a5904774492

Observation 574323eb-0efb-4a20-8e7b-e5dc35346274 · inbound

Segment-Aligned Policy Optimization for Multi-Modal Reasoning cites this paper.

Segment-Aligned Policy Optimization for Multi-Modal Reasoning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 22

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arxiv_id, observed 2026-05-11T16:51:07.917445Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T14:44:31.160543Z digest=sha256:c34ec8175eaa59c29f92d5f4ecfef69fb8e49a0f258f0b1ad4df72595a25cb67

Observation e8a2003e-ca14-4039-aa51-13d48769aa30 · inbound

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe cites this paper.

Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 54

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arxiv_id, observed 2026-05-11T23:26:16.356487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T17:00:49.448352Z digest=sha256:f0f3a36e76d004061bac704adb26c3d8522851539413782dfca56362295d2469

Observation 94f731f4-8d62-4817-aa77-2f3d071c6fc5 · inbound

CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization cites this paper.

CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 29

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arxiv_id, observed 2026-05-20T07:28:06.725569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T07:25:34.637803Z digest=sha256:88c6a1d1d3edaf8e0dd6b44cf49b9714264cb9ec8e645dfec208b8cd44ceb0ae

Observation 77cdde0a-33d9-4c61-8880-9092fa519084 · inbound

Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning cites this paper.

Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 55

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arxiv_id, observed 2026-05-20T06:18:05.215516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T06:16:47.650748Z digest=sha256:26c33d56eef2918798baf2e35936269c5a6e0e58b8e14c5286fac5bc99de10ef

Observation 62ba18d2-50e4-444a-b080-abbb816179e0 · inbound

TRON: Targeted Rule-Verifiable Online Environments for Visual Reasoning RL cites this paper.

TRON: Targeted Rule-Verifiable Online Environments for Visual Reasoning RL DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 50

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arxiv_id, observed 2026-07-01T22:56:19.945174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T14:55:07.045625Z digest=sha256:7d2c8b7f929360a7bb80d4614bce98ef4bb72654bfcd2814f89a0190f135a6d7

Observation bcdf8a07-284a-487e-8e7d-6cbf472d189b · inbound

Sci-Rho: A Multilingual Visually-Grounded Symbolic Benchmark for STEM Problems cites this paper.

Sci-Rho: A Multilingual Visually-Grounded Symbolic Benchmark for STEM Problems DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 80

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verified exact
arxiv_id, observed 2026-07-02T20:47:22.863324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T20:11:02.445626Z digest=sha256:4bf0669ec5f1e2f22b9de72b3ba7ab3e8e865e4addab3c7c1e0be341ca3a4ad5

Observation 7e73f050-7a90-42da-aa3d-e2d49f48d2ae · inbound

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning cites this paper.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 120

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verified exact
arxiv_id, observed 2026-07-02T21:37:25.272238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T19:36:57.231932Z digest=sha256:a48f06e5fabc322cd9b99e377e502dfdadb583d587030c899b6bbb159a9beaac

Observation 2eac8e13-ee06-4d26-acba-29fdfa65db91 · inbound

Kwai Keye-VL-2.0 Technical Report cites this paper.

Kwai Keye-VL-2.0 Technical Report DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 113

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metadata mismatch
arxiv_id, observed 2026-07-03T04:27:37.126894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T13:53:10.352603Z digest=sha256:f30a233822344960cb977ca7cb58dc6106fbbda3bd0dde25cb4a8d8f2fc82222

Observation 735cf272-874d-4908-b4d9-26409cdabd90 · inbound

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

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 133

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verified exact
arxiv_id, observed 2026-07-03T20:48:56.043493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T01:08:52.981296Z digest=sha256:75661b1a6cd61d25e3198312ee54f5dbcfc5b0c01378442381c6f0e18b8920ec

Observation 203aa784-5ef5-4555-9b26-f50f1b9fd1b7 · inbound

TuringViT: Making SOTA Vision Transformers Accessible to All cites this paper.

TuringViT: Making SOTA Vision Transformers Accessible to All DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 68

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verified exact
arxiv_id, observed 2026-06-29T15:03:32.172756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T05:32:26.746776Z digest=sha256:c1fd1c2295f95b58fdaf25dc9f555bc775b82b160d7f5722ac1ffaa72ef06511

Observation 0d3444e8-d223-4509-9899-5de7a94a8763 · inbound

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity cites this paper.

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 150

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verified exact
arxiv_id, observed 2026-07-02T19:07:17.456810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-02T18:57:46.841456Z digest=sha256:60f548aeb600c42cf5b42ca0dda3441bffacaf9a1bdd53cbf786bffdf4431c7a

Observation ee54c62c-eef4-4ccd-ac6c-f89ced35fad5 · inbound

Model Guides You How to Draw: Adaptive Visual Gating for Unified Multimodal Reasoning cites this paper.

Model Guides You How to Draw: Adaptive Visual Gating for Unified Multimodal Reasoning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 43

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unresolved
no resolver link, observed 2026-07-14T01:07:06.861298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T01:07:06.861298Z digest=sha256:caffcda1755042ea845504442f931490c0f6363815244a09a358622ac7d5c3b9

Observation a6346352-c820-4d72-88fc-7d33e3b9970a · inbound

What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs cites this paper.

What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 34

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unresolved
no resolver link, observed 2026-08-04T02:46:49.739428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T02:46:49.739428Z digest=sha256:8f445405eadc7c11bead92470ccc16720c0f17e91a7fa08b29ad56ef297d879e

Observation d9ba0465-73f0-47d9-a34b-4f562c052503 · inbound

MIDAL: A Dataset of Math Image Descriptions for Accessible Learning cites this paper.

MIDAL: A Dataset of Math Image Descriptions for Accessible Learning DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T00:49:46.500785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:49:46.500785Z digest=sha256:180e9c7752a3f0a1c5ab7ac5e2b883e97c25107482132f14cc09636972253238