Paper Citation Record · LEDGER

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

As of 18 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 4 inbound Pith citation observations for arXiv:2508.12680.

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

pith.paper-citation-record.v1
2508.12680 v1

Coverage vector

measured 100 of 113 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:24:08.529010Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T17:09:33.968186Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:06:10.238711Z

Reference resolution

100 of 113 outbound references displayed

verified exact1
verified fuzzy3
unresolved96
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cfd5f7f5-cedb-4235-b24c-3b2b79e6a404 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

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Observation ce8eff9e-56fc-4499-ad9d-9ffb88505115 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Training Verifiers to Solve Math Word Problems

Reference 2

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Observation 6aa7cf1a-2207-493e-b21f-e67f780a5272 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Measuring mathematical problem solving with the math dataset

Reference 3

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Observation 4a2cf671-3e03-4208-86e5-e1bf28c41528 · outbound

This paper cites SWE-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, 2024.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation SWE-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, 2024

Reference 4

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Observation 5aea5da8-1175-4b5c-a206-e8dae25642b7 · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale, 2025.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Dapo: An open-source llm reinforcement learning system at scale, 2025

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.047280Z

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Observation c00739b9-2aff-4843-bf97-9b9bc98461f3 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.052248Z

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Observation 464d6984-42b7-43e7-980b-ed5dd2d088d2 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.057500Z

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Observation ade186c9-82a5-49a8-be9f-a10ccce1f593 · outbound

This paper cites Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective

Reference 8

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Observation fe4eab4d-e348-4dd7-85bd-740000ab12f2 · outbound

This paper cites Qwen2.5-VL Technical Report.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Qwen2.5-VL Technical Report

Reference 9

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Observation ff11dbdd-89e4-4039-b08e-30fd1a15485f · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.075537Z

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Observation b335f2bc-d348-4448-9e50-7861a3efc2c7 · outbound

This paper cites Visual instruction tuning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Visual instruction tuning

Reference 11

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Observation 58da3d48-c780-4ecd-ab43-50f69b2a6eb4 · outbound

This paper cites Visual-RFT: Visual Reinforcement Fine-Tuning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Visual-RFT: Visual Reinforcement Fine-Tuning

Reference 12

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Observation bbcb08f5-158d-40db-98bc-4747335ee78a · outbound

This paper cites Vlm-r1: A stable and generalizable r1-style large vision-language model, 2025.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Vlm-r1: A stable and generalizable r1-style large vision-language model, 2025

Reference 13

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Observation 3bde4210-ac89-43db-a1de-bf6ee3940371 · outbound

This paper cites Lmm-r1: Empowering 3b lmms with strong reasoning abilities through two-stage rule-based rl, 2025.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Lmm-r1: Empowering 3b lmms with strong reasoning abilities through two-stage rule-based rl, 2025

Reference 14

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Observation 7622440a-edb0-41fd-b314-135e30cbaa0c · outbound

This paper cites Virgo: A Preliminary Exploration on Reproducing o1-like MLLM.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Virgo: A Preliminary Exploration on Reproducing o1-like MLLM

Reference 16

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Observation 112b9614-e7a1-4a83-8c93-a72286806a15 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization

Reference 17

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Observation e23391ff-c8d4-463f-a79c-78f2522cadd0 · outbound

This paper cites Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning

Reference 18

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Observation 6e8cb2c6-8893-4d19-ae6a-e7dba4b1234a · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.121024Z

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Observation 642c9b11-9ea2-4095-8624-faaa2e2aafde · outbound

This paper cites SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.125709Z

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Observation 90239c86-c51a-4bc9-a116-367c475a62c1 · outbound

This paper cites VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Reference 21

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Observation 0544f2a6-a603-43a8-804b-37d51e1ee67e · outbound

This paper cites Kimi-VL Technical Report.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Kimi-VL Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.135546Z

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Observation 2af91df2-18d5-4b30-88f3-717e80af052b · outbound

This paper cites Improve vision language model chain-of-thought reasoning, 2024.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Improve vision language model chain-of-thought reasoning, 2024

Reference 23

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Observation 643b81b0-db47-446e-84f0-a9d29287b31c · outbound

This paper cites Llava-cot: Let vision language models reason step-by-step, 2025.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Llava-cot: Let vision language models reason step-by-step, 2025

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.145289Z

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Observation d2394a16-e466-42f0-a81e-1ad9d082294d · outbound

This paper cites Spatialvlm: Endowing vision-language models with spatial reasoning capabilities.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Spatialvlm: Endowing vision-language models with spatial reasoning capabilities

Reference 25

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Observation d2cec0f4-2c7c-45ac-8c25-2662a84eb841 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language Models

Reference 26

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Observation da7e05ac-18da-4499-9480-2d1f810a8482 · outbound

This paper cites MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning

Reference 27

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Observation 17e8a213-d68d-4a21-b5bd-71b06b1fe91a · outbound

This paper cites LESS: Selecting Influential Data for Targeted Instruction Tuning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation LESS: Selecting Influential Data for Targeted Instruction Tuning

Reference 28

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Observation 183598ef-8a3e-482c-8f50-d146f36bd236 · outbound

This paper cites Estimating Training Data Influence by Tracing Gradient Descent.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Estimating Training Data Influence by Tracing Gradient Descent

Reference 29

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Observation fb1a6e3f-3679-4b9f-a601-dedf248447a8 · outbound

This paper cites GPT-4o System Card.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation GPT-4o System Card

Reference 30

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Observation 606f5ab8-6bd8-415b-aa7a-9850ede75773 · outbound

This paper cites LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.180238Z

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Observation 6251beb0-6008-4404-8d7a-7d8c47d1a376 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 32

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Observation a7eb8a0b-c7b5-4ad2-950d-304f8a234132 · outbound

This paper cites Qvq: To see the world with wisdom, December 2024.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Qvq: To see the world with wisdom, December 2024

Reference 33

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Observation 68b71451-4a7a-4856-86ba-b191f7adc41a · outbound

This paper cites OpenAI o1 System Card.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation OpenAI o1 System Card

Reference 34

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Observation f24ef1ec-9434-4f03-a185-96858763d27b · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 35

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Observation 88f412a1-b5a5-45f7-a2bf-78a6b741fa94 · outbound

This paper cites an unresolved cited work.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Unresolved cited work

Reference 36

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Observation 5d4b8d6e-260a-49aa-9a78-6e1471136246 · outbound

This paper cites R1-v: Reinforcing super gen- eralization ability in vision-language models with less than $3.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation R1-v: Reinforcing super gen- eralization ability in vision-language models with less than $3

Reference 37

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Observation a3c2899c-091c-4675-aa56-5eb2bec22a5b · outbound

This paper cites SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Reference 38

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Observation fbd8b0af-21e1-4a8c-9841-09f1b4e70411 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 39

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Observation cc2396e8-cd50-45ba-8cd9-3706eac66bb3 · outbound

This paper cites Lima: Less is more for alignment.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Lima: Less is more for alignment

Reference 40

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Observation f35c73f3-39d1-45fb-807c-6ba3f365470f · outbound

This paper cites Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning

Reference 41

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Observation 12946d17-c9d3-47d6-b083-e47acee5baef · outbound

This paper cites LLM-Assisted Code Cleaning For Training Accurate Code Generators.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation LLM-Assisted Code Cleaning For Training Accurate Code Generators

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.236832Z

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Observation c6e8cc79-7e3c-4088-a071-b849fad1b69e · outbound

This paper cites What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.242672Z

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Observation c73c9da2-a9c0-46e3-a726-cbb2d4663d9a · outbound

This paper cites Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models

Reference 44

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Observation 0cb1384e-8139-4298-8508-cca5bcef0348 · outbound

This paper cites OctoPack: Instruction Tuning Code Large Language Models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation OctoPack: Instruction Tuning Code Large Language Models

Reference 45

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Observation 30a91729-8420-44bf-8e9b-39f6759bcbb0 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Lora: Low-rank adaptation of large language models

Reference 46

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Observation acb0228c-59ed-4336-bbd5-7f6fc4c76ada · outbound

This paper cites Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts

Reference 47

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Observation d4d2e983-fcd9-4d5b-808c-e86268208079 · outbound

This paper cites Mmmu: A massive multi-discipline multi- modal understanding and reasoning benchmark for expert agi.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Mmmu: A massive multi-discipline multi- modal understanding and reasoning benchmark for expert agi

Reference 48

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Observation 46cf7362-e5d1-46a6-bb99-4f1ba45e377c · outbound

This paper cites MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark

Reference 49

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Observation c5f39aea-717f-4e37-9215-6e84e5962235 · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 50

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Observation 75c08491-55e3-47da-af83-9fb8f069cbc3 · outbound

This paper cites LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts

Reference 51

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Observation b9656623-4767-4186-94f5-b2ae1fea1b86 · outbound

This paper cites Chartqa: A benchmark for question answering about charts with visual and logical reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Chartqa: A benchmark for question answering about charts with visual and logical reasoning

Reference 52

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Observation 697d2f21-c6f5-45bb-b7ca-7fd28bfbefa6 · outbound

This paper cites Measuring multimodal mathematical reasoning with math-vision dataset.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Measuring multimodal mathematical reasoning with math-vision dataset

Reference 53

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Observation 065bef9b-408c-473e-ac24-3904ed4f939e · outbound

This paper cites Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? In European Conference on Computer Vision, pages 169–186.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? In European Conference on Computer Vision, pages 169–186

Reference 54

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Source-reported events for the cited work

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Observation 16a605b8-022a-4945-9fd4-0bc8dbb33625 · outbound

This paper cites OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.302455Z

Source-reported events for the cited work

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Observation 659a2e93-4df8-4d7d-9d13-5bcad45354f1 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.307694Z

Source-reported events for the cited work

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Observation ab350932-1d83-4672-a1b2-6435f145c084 · outbound

This paper cites DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.313024Z

Source-reported events for the cited work

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Observation 2a673b41-5ccf-4fb4-8a99-b9d678df3c72 · outbound

This paper cites Charxiv: Charting gaps in realistic chart understanding in multimodal llms.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Charxiv: Charting gaps in realistic chart understanding in multimodal llms

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.318268Z

Source-reported events for the cited work

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Observation bd9394ee-27c1-4d83-ad73-20f2d6ae886d · outbound

This paper cites ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.322949Z

Source-reported events for the cited work

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Observation 72bfa829-d95b-4eb4-abd1-7d58dce836d3 · outbound

This paper cites A dataset of clinically generated visual questions and answers about radiology images.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation A dataset of clinically generated visual questions and answers about radiology images

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.327988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f841676b-ba39-40c1-b25e-5ffa31b25379 · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.332746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a3f783a-95aa-4417-97e9-298d15cbc6f2 · outbound

This paper cites Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.337699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff7cb12c-657c-4e22-8879-62ac8b89aca1 · outbound

This paper cites MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.342648Z

Source-reported events for the cited work

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Observation 72f64ce5-8e37-4f3a-b84e-f3d780d1ae00 · outbound

This paper cites Ovis: Structural Embedding Alignment for Multimodal Large Language Model.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.347677Z

Source-reported events for the cited work

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Observation da29709f-a27e-4bc2-b702-7e3df9903af3 · outbound

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

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.352870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34ae2762-e1ed-41ae-8ea5-71819f1e94ae · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation LLaVA-OneVision: Easy Visual Task Transfer

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.357697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f10e8a88-ecf0-443e-9358-9d7289054b12 · outbound

This paper cites Llava-next: Improved reasoning, ocr, and world knowledge, January 2024.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Llava-next: Improved reasoning, ocr, and world knowledge, January 2024

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.362835Z

Source-reported events for the cited work

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Observation 65c6103f-3e1b-40b1-8d0f-fd6070afde1c · outbound

This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.368349Z

Source-reported events for the cited work

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Observation 0e724969-432f-4218-8cb3-d931bb78a8dd · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.373195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6bf0777-e8da-4546-96d7-41539bd2234a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Proximal Policy Optimization Algorithms

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.378185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 376bacae-793c-42dd-9047-57ab352cf7a8 · outbound

This paper cites FigureQA: An Annotated Figure Dataset for Visual Reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation FigureQA: An Annotated Figure Dataset for Visual Reasoning

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.382930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63c1af2b-ad80-420f-97f4-2035f9b86daa · outbound

This paper cites Dvqa: Understanding data visualizations via question answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Dvqa: Understanding data visualizations via question answering

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.387919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ed0157a-9167-4bc7-b5e0-d26bd703336f · outbound

This paper cites Plotqa: Reasoning over scientific plots.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Plotqa: Reasoning over scientific plots

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.392660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96109899-f9ff-431b-b58f-a0ed11b218ed · outbound

This paper cites Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.397621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48732e57-7c6b-425b-8266-7a93b8ea40f1 · outbound

This paper cites MapQA: A Dataset for Question Answering on Choropleth Maps.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation MapQA: A Dataset for Question Answering on Choropleth Maps

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.402852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ae55cf7-6324-4e57-b2c2-2e1e7fa2bfe2 · outbound

This paper cites ChartBench: A Benchmark for Complex Visual Reasoning in Charts.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation ChartBench: A Benchmark for Complex Visual Reasoning in Charts

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.407822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23c48653-37e2-4852-b360-82b30dbae3e2 · outbound

This paper cites Unichart: A universal vision-language pretrained model for chart comprehension and reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Unichart: A universal vision-language pretrained model for chart comprehension and reasoning

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.412542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6132d4de-611d-43a2-9dc3-0ffc6e463a72 · outbound

This paper cites Docvqa: A dataset for vqa on document images.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Docvqa: A dataset for vqa on document images

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.417054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30ce4f23-7c12-45e3-b24e-577d02c4cd73 · outbound

This paper cites Harnessing Webpage UIs for Text-Rich Visual Understanding.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Harnessing Webpage UIs for Text-Rich Visual Understanding

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.422038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9418bd85-c530-41be-aeeb-1d4b5681b22b · outbound

This paper cites Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.427313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 769eb7e2-f057-4600-a319-7c77768b5187 · outbound

This paper cites An augmented benchmark dataset for geometric question answering through dual parallel text encoding.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation An augmented benchmark dataset for geometric question answering through dual parallel text encoding

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.432638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d08d20f2-47c6-4c1f-a5ad-588660b69e8b · outbound

This paper cites UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.437400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning.

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

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.442245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84cebb8a-e84c-4ded-942a-a9e0dab82fb6 · outbound

This paper cites Solving geometry problems: Combining text and diagram interpretation.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Solving geometry problems: Combining text and diagram interpretation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.447210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69d8adda-2460-48f0-be5b-5764e70775e3 · outbound

This paper cites CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.452090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ae9e6f8-e958-4a16-bd67-35a411a8f7fa · outbound

This paper cites IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.457298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3229e0cd-4c93-42b0-a050-a02eba852c68 · outbound

This paper cites A Corpus for Reasoning About Natural Language Grounded in Photographs.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation A Corpus for Reasoning About Natural Language Grounded in Photographs

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.462326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e6016ae-9dd9-47a4-b9a8-4917f9ef2ff6 · outbound

This paper cites Image Retrieval from Contextual Descriptions.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Image Retrieval from Contextual Descriptions

Reference 88

Resolution: verified exact; local_arxiv, observed 2026-08-15T17:24:08.770841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6a872cae-9d7c-4986-9b99-f5f33a6cec46 · outbound

This paper cites Lawrence Zitnick, and Devi Parikh.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Lawrence Zitnick, and Devi Parikh

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.472416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb282081-0b1c-42d3-8e7d-198b15c2a976 · outbound

This paper cites Super-clevr: A virtual benchmark to diagnose domain robustness in visual reasoning.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Super-clevr: A virtual benchmark to diagnose domain robustness in visual reasoning

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:24:10.024942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation de48a35c-7bd1-4689-8db8-a768aece6e2e · outbound

This paper cites A diagram is worth a dozen images.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation A diagram is worth a dozen images

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.481966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d15722cf-d116-4081-a0d7-a43e7e8b4b34 · outbound

This paper cites Are you smarter than a sixth grader? textbook question answering for multimodal machine comprehension.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Are you smarter than a sixth grader? textbook question answering for multimodal machine comprehension

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:24:09.996101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cd6f8cb2-0f48-4a38-a74d-5288742c67d2 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.490975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab713047-994d-4443-8b21-b87b0005d038 · outbound

This paper cites Vizwiz grand challenge: Answering visual questions from blind people.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Vizwiz grand challenge: Answering visual questions from blind people

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.495486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfe0133e-91c3-4c81-85a7-0729729d3aa8 · outbound

This paper cites Towards vqa models that can read.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Towards vqa models that can read

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.500513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b17bf1cf-2bfd-4532-bedf-bc28197e34dd · outbound

This paper cites A-okvqa: A benchmark for visual question answering using world knowledge.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation A-okvqa: A benchmark for visual question answering using world knowledge

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.505250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e24b1632-9004-4fb0-b05f-7da7199d71b8 · outbound

This paper cites Ok-vqa: A visual question answering benchmark requiring external knowledge.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Ok-vqa: A visual question answering benchmark requiring external knowledge

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.510153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15866e9d-4e44-40d8-9ab7-a6b5d64790b7 · outbound

This paper cites PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.514831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d26467e-9283-4c20-9eb0-d4c876cad2fb · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.519580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f701a439-9b26-42c4-9d6f-f0b003162a47 · outbound

This paper cites Chart-r1: Chain-of-thought supervision and reinforcement for advanced chart reasoner.

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation Chart-r1: Chain-of-thought supervision and reinforcement for advanced chart reasoner

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-15T17:24:08.524451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76ea1cc2-7929-4419-bcf2-0c36ff67336e · outbound

This paper cites You are a QUESTION-TYPE classifier (do NOT answer the question itself).

Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation You are a QUESTION-TYPE classifier (do **NOT** answer the question itself)

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:24:09.922336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 6bf98c01-7ddf-4da9-888a-95077f7dad34 · inbound

OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks cites this paper.

OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:30:58.744656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27a7c529-19a8-4113-909d-20fb608e0500 · inbound

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model cites this paper.

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:46:03.296681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f3d80314-5b0f-4b0b-bdf7-8e8705610c62 · inbound

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution cites this paper.

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:06:10.242064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f4626655-0973-4564-9de3-00cec701f71f · inbound

Pest-Thinker: Learning to Think and Reason like Entomologists via Reinforcement Learning cites this paper.

Pest-Thinker: Learning to Think and Reason like Entomologists via Reinforcement Learning Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:09.398205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.