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Paper Citation Record · LEDGER

GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 38 inbound Pith citation observations for arXiv:2105.14517.

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

pith.paper-citation-record.v1
2105.14517 v3

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measured 0 of 0 reference resolution

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measured 38 of 38 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 38 of 38 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:32:45.014068Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-02T22:47:26.028530Z

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Outbound references

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Pith citing papers

Observation 758540ab-a712-4367-bf67-383ddfccdda3 · inbound

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset cites this paper.

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 1

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arxiv_id, observed 2026-05-17T20:45:37.815378Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-17T20:45:37.750536Z digest=sha256:c6f39ee0d5a26ff56630c71069fee1c17755c13a232ffaefc6d17d48fb0203b0

Observation 1cf6766e-ec04-45d5-bad1-58fb844eb521 · inbound

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? cites this paper.

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 10

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arxiv_id, observed 2026-05-17T01:29:30.154946Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-17T01:29:30.032408Z digest=sha256:4ed694f5bd83f1e5dbc356e3595c92291a6b107bd0a60503903e3be0a0ee6c5a

Observation f649d6c8-798b-4b68-9905-0aa7f810d6f1 · inbound

We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? cites this paper.

We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 32

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source=pdf_text observed=2026-05-16T21:55:40.808698Z digest=sha256:24eeeb7bfcf3af2015b0c3d45509c8795a631acfffc4c5e2544e7b72dd03f4ad

Observation 93606d2e-aff9-4192-83a7-6235d9996db4 · inbound

MiniCPM-V: A GPT-4V Level MLLM on Your Phone cites this paper.

MiniCPM-V: A GPT-4V Level MLLM on Your Phone GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 19

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arxiv_id, observed 2026-05-10T21:07:31.981369Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T21:07:31.387726Z digest=sha256:a4936c65e1c84da66f34f98c35fd5b38271b65b6cde6568b27b8a57ce75ab714

Observation 124d11dd-a760-42da-9c6c-962a50518033 · inbound

ElectroVizQA: How well do Multi-modal LLMs perform in Electronics Visual Question Answering? cites this paper.

ElectroVizQA: How well do Multi-modal LLMs perform in Electronics Visual Question Answering? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 8

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source=arxiv_source observed=2026-08-12T10:59:47.456187Z digest=sha256:b59d74b57e97a21ba532f61a40f168d9b9c930c3d0e4bf775199df424056c835

Observation e5390b79-acb0-4daa-88f6-9b4d0cae83c2 · inbound

Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring cites this paper.

Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 6

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source=pdf_text observed=2026-08-12T04:59:44.998859Z digest=sha256:d4e3d974b1c4739dcf24a150dbbafead0293564c7e3af987a9132a5612ff4574

Observation f7d72d06-6794-413b-8a99-ece4719930a9 · inbound

AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information? cites this paper.

AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 9

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source=pdf_text observed=2026-08-11T23:19:11.446829Z digest=sha256:715a6a1018a615bb7bb971f945416ed1de087ad8a95af97a03557d09ea11e2f7

Observation e306dab6-f352-4493-b748-47771ba98683 · inbound

Chimera: Improving Generalist Model with Domain-Specific Experts cites this paper.

Chimera: Improving Generalist Model with Domain-Specific Experts GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 9

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source=pdf_text observed=2026-08-11T20:13:47.494443Z digest=sha256:849eb70e7291551595189658acec9acda1da1343e8f044b238d3f67f6b13dc5f

Observation 062308c0-b4b0-44de-9902-75f3c5f169df · inbound

Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning cites this paper.

Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 11

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source=pdf_text observed=2026-08-11T17:25:59.570536Z digest=sha256:f20a93ea647a1f3243d64efb097c95777702e1075421e1bc6040a8944af5738a

Observation 91801d1a-5dd6-4d6c-a5ee-027a0dcff59e · inbound

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search cites this paper.

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 1998

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source=pdf_text observed=2026-08-11T04:53:11.750387Z digest=sha256:637ef06b0a604af4be421bf1ebdfc77a7da02ed728a6496a27cb469b317e81db

Observation 58d9216f-3ca5-4af6-ab93-28c88c5dddb8 · inbound

Slow Perception: Let's Perceive Geometric Figures Step-by-step cites this paper.

Slow Perception: Let's Perceive Geometric Figures Step-by-step GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 6

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source=pdf_text observed=2026-08-10T23:21:42.560958Z digest=sha256:cc750fdf8978314813f3f10569293faaffff52db6d1230fabfddd85bc6ced1c2

Observation 17a34dd4-4b78-46a3-80d9-3d5dd6202e27 · inbound

Visual question answering: from early developments to recent advances -- a survey cites this paper.

Visual question answering: from early developments to recent advances -- a survey GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 185

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source=arxiv_source observed=2026-08-10T21:46:28.949210Z digest=sha256:1700348114320bfb2379fde28f1b26ca23d196a7be2312f60495932739530e83

Observation cdde7c84-f3c4-4329-b3e6-6edbebb405ed · inbound

RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? cites this paper.

RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 18

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source=pdf_text observed=2026-08-10T18:30:56.557012Z digest=sha256:a7deeecc046e815885c27ab69ee355277b874566e0e3dbcd760c9caeb6c43ae5

Observation 4371e3e0-06ad-4ccc-aa02-a9927339681a · inbound

InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model cites this paper.

InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 12

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source=arxiv_source observed=2026-08-10T17:18:40.008109Z digest=sha256:c4d3733f76297cf423a2b8690628072e5e4e44c7c980ca9d3d7469b8971af0e9

Observation 2c239a0b-3c6a-4e05-9ba8-de94667fed2e · inbound

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models cites this paper.

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 10

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source=arxiv_source observed=2026-08-10T15:40:39.594235Z digest=sha256:f10599fc3db326bb897a0bb476dbd0e6176c3ab44b6937ffe38ce190af904ed7

Observation f5760f9b-228f-4499-bd29-3133d095f342 · inbound

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models cites this paper.

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 8

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source=arxiv_source observed=2026-08-09T19:27:46.589939Z digest=sha256:c5803117ce1a742fd2733eb547850b7c72e50802678afb2fb51882d53f5f1173

Observation edecfd91-e333-4d89-8e3a-823e99214da9 · inbound

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems cites this paper.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 8

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arxiv_id, observed 2026-05-22T22:57:13.333835Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T22:55:34.238427Z digest=sha256:1063085d424985f4d283e27e7e48ea3f73a95bec0d78e325ac0fbf88d9c70cc2

Observation df6a3f08-498f-4318-a006-20b6057a0396 · inbound

OpenVLThinker: Complex Vision-Language Reasoning via Iterative SFT-RL Cycles cites this paper.

OpenVLThinker: Complex Vision-Language Reasoning via Iterative SFT-RL Cycles GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 7

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arxiv_id, observed 2026-05-19T06:59:03.355958Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T06:59:03.112252Z digest=sha256:2128a17aa057634613de78d37edf52252cdc452e73ba8b9ff55a457d6dd31cd4

Observation 1477183b-63ca-4856-ae9c-d131bec0fa6a · inbound

GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning cites this paper.

GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 6

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source=pdf_text observed=2026-08-16T12:32:45.014068Z digest=sha256:015adb3304ae55376269ab6e352a21b591caf88e1baadb610a15df504180b60f

Observation c5b95091-4d9e-489c-8fea-111549d0a0ea · inbound

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark cites this paper.

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 23

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source=pdf_text observed=2026-08-16T11:46:40.402359Z digest=sha256:8cc4f3e63aa75bf931d69ecb42a5de3542981d4483940af3f4205eab2c7b3cd7

Observation 415db557-b096-48c8-ae49-f1f428093b02 · inbound

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models cites this paper.

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 45

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source=arxiv_source observed=2026-08-15T23:21:12.044445Z digest=sha256:0d762f7fceebf1ff1a494d901703ff37dc91538e9f62e7148f320f8a1837923e

Observation 8abcfdfa-96fa-48c4-89b6-bf3aaa5080ed · inbound

CellVerse: Do Large Language Models Really Understand Cell Biology? cites this paper.

CellVerse: Do Large Language Models Really Understand Cell Biology? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 13

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source=pdf_text observed=2026-08-15T23:00:37.955390Z digest=sha256:60b1e818680b340544b48f37bf876980234c8e94dd66052a18f440a2dbb06e75

Observation bee95ecf-2051-43e9-851f-db014439399a · inbound

NAN: A Training-Free Solution to Coefficient Estimation in Model Merging cites this paper.

NAN: A Training-Free Solution to Coefficient Estimation in Model Merging GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 4

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source=arxiv_source observed=2026-08-07T15:08:45.539141Z digest=sha256:5f063d771e90c6616a3bef10ba8d0ae8c276d967d9dda4cf6df18102e5a76e61

Observation e9b48f86-27bc-43ae-b295-ebe6533bc78d · inbound

LaViDa: A Large Diffusion Language Model for Multimodal Understanding cites this paper.

LaViDa: A Large Diffusion Language Model for Multimodal Understanding GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 13

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source=pdf_text observed=2026-08-07T14:59:33.345230Z digest=sha256:0a366d04e0adda3748f241fc10e13f1014360b87db49b8203d2584f4e4385cf0

Observation 3c66b4bf-0e7e-434e-b2d1-9df26c205382 · inbound

Can Visual Encoder Learn to See Arrows? cites this paper.

Can Visual Encoder Learn to See Arrows? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 4

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source=pdf_text observed=2026-08-07T14:07:17.952748Z digest=sha256:a02e8c54da81aab49cdf7105c2b7f84ce4b0a72e70726b059441cf311613b930

Observation eebbef18-5422-4da1-bb9e-31a4d2dd1f0f · inbound

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? cites this paper.

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 20

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source=pdf_text observed=2026-08-07T13:05:25.722333Z digest=sha256:60b6cad26f51c99b3c39e0dd9fa936f772f9168933c1e6c3d531e5a80e59aedf

Observation e4615098-7cfd-4dfc-abb7-03ccc8f23df0 · inbound

Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models cites this paper.

Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 7

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source=pdf_text observed=2026-08-07T12:37:43.332355Z digest=sha256:0d37f526153de6a4c14a9c41fa2ab4b9dbab6f49ce046cca1045f74c5f416773

Observation c9cf355f-0040-4426-9d0d-eb9c92452fac · inbound

Towards Geometry Problem Solving in the Large Model Era: A Survey cites this paper.

Towards Geometry Problem Solving in the Large Model Era: A Survey GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 2022

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source=pdf_text observed=2026-08-07T11:22:40.721234Z digest=sha256:45941a4901372d4cc790a27eadd786c5e53e98cd409a7231b044624dd2382d90

Observation 3077b91e-77dd-4bd3-8cfc-551ee1005f5f · inbound

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning cites this paper.

MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 5

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source=pdf_text observed=2026-08-07T10:28:46.943541Z digest=sha256:0254a7bef41200d1af7496e49725d18f657a757c9104b11933f87b44071afb4f

Observation d672599f-5a5c-4dac-9f7b-d879ef2f558f · inbound

Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach cites this paper.

Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 5

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source=arxiv_source observed=2026-08-16T11:24:32.995932Z digest=sha256:85a1e4b6d3ac2ab4a12ab0a1c2e9ac7f77f04905fd04b7ac625323b00fb1fd5b

Observation 47d9affc-1ceb-4e3c-8935-9b05f859fd14 · inbound

EasyARC: Evaluating Vision Language Models on True Visual Reasoning cites this paper.

EasyARC: Evaluating Vision Language Models on True Visual Reasoning GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 3

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source=pdf_text observed=2026-08-07T04:06:40.262475Z digest=sha256:9ff4ebad3763a00272af0213760d0ead0d88a33a5490a1e662d802a5c16f14d7

Observation 19b30b09-1918-4e97-9c92-8b68e719fc18 · inbound

MAGE: Multimodal Alignment and Generation Enhancement via Bridging Visual and Semantic Spaces cites this paper.

MAGE: Multimodal Alignment and Generation Enhancement via Bridging Visual and Semantic Spaces GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 7

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source=pdf_text observed=2026-08-06T12:31:26.032238Z digest=sha256:27be3fb1c07c6ccf3f89b196ee09f9ea076884a28e9d0508f6b532913fa609ee

Observation 20c4912d-1cd7-4772-9f91-4e218d516716 · inbound

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines cites this paper.

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 6

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arxiv_id, observed 2026-05-19T00:41:56.071851Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T00:38:43.897231Z digest=sha256:0307e5fde4f8ec8efb7902acb62e9e073de1c3a19419a65ea42af9d63c8d7d88

Observation 3b5cebb5-9ff0-4f8d-88d3-4b0a296a8cf4 · inbound

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation cites this paper.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 83

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Unavailable: canonical work link unavailable.

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GeoAnalystBench: A GeoAI benchmark for assessing large language models for spatial analysis workflow and code generation cites this paper.

GeoAnalystBench: A GeoAI benchmark for assessing large language models for spatial analysis workflow and code generation GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 5

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LaRe: Latent Refocusing for Multimodal Reasoning cites this paper.

LaRe: Latent Refocusing for Multimodal Reasoning GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 96

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Observation 57f8c1da-9723-4db5-b579-3f07bfbe335f · inbound

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery cites this paper.

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 35

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Observation 3f4fdbb5-71a6-4a74-a01a-7c25f9b0c483 · inbound

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery cites this paper.

Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 35

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