MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective | Paper Citation Record

Observation f6c7de02-b8f7-4689-8b48-9fcb1a5c0988 · outbound

This paper cites Phi-3 technical report: A highly capable language model locally on your phone, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Phi-3 technical report: A highly capable language model locally on your phone, 2024

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This paper cites Lawrence Zitnick, Dhruv Batra, and Devi Parikh.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Lawrence Zitnick, Dhruv Batra, and Devi Parikh

Reference 2

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Observation 6b13b67a-2826-4d42-a277-939c243e4e08 · outbound

This paper cites Pixtral 12b, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Pixtral 12b, 2024

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Observation 88503e0e-eb56-4065-834c-333684f824a2 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Flamingo: a visual language model for few-shot learning

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Observation 620f42f1-e921-4387-b5af-0bea0aa64520 · outbound

This paper cites Unicom: Universal and compact representation learning for image re- trieval, 2023.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unicom: Universal and compact representation learning for image re- trieval, 2023

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Observation 392d676f-d717-43b3-a963-6a4e784f0ad4 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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Observation 5a3cb3c3-c7b5-4b63-8759-2e2c9483f6ca · outbound

This paper cites Benchmarking foundation models with language- model-as-an-examiner.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Benchmarking foundation models with language- model-as-an-examiner

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Observation 3a569c53-eca4-41cc-aed1-e0e13b528f6a · outbound

This paper cites AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?

Reference 8

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Observation 34af97cc-c653-4fc4-9f3e-53580ba164c6 · outbound

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

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Are We on the Right Way for Evaluating Large Vision-Language Models?

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Observation 4d426660-b006-4629-9d50-508e9e74dc1b · outbound

This paper cites InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

Reference 10

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Observation 01337695-0e8e-4add-bfb0-1d19d00479f6 · outbound

This paper cites How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites

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Observation e25963b0-5c21-4047-95e0-4209caa29209 · outbound

This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

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Observation 89cf1586-6f20-4a4f-a2c2-8eafcca0e571 · outbound

This paper cites Opencompass: A universal evaluation platform for foundation models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Opencompass: A universal evaluation platform for foundation models

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Observation 1761d266-6cdf-430a-90a2-27df1ace2ead · outbound

This paper cites Molmo and pixmo: Open weights and open data for state-of-the-art vision-language models, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Molmo and pixmo: Open weights and open data for state-of-the-art vision-language models, 2024

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Observation d8c43b71-31f3-4880-a221-e0fbd37bd55e · outbound

This paper cites Vlmevalkit: An open- source toolkit for evaluating large multi-modality models,.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Vlmevalkit: An open- source toolkit for evaluating large multi-modality models,

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Observation 1b4b3530-0bfb-4f77-ae21-051394a1d927 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Scaling recti- fied flow transformers for high-resolution image synthesis

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Observation e2144318-a87c-4cf8-af47-a01a5c975885 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

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Observation 043b6139-149a-47eb-acba-cb8576dc294f · outbound

This paper cites Ocrbench v2: An improved benchmark for evaluating large multimodal models on visual text localization and reasoning, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Ocrbench v2: An improved benchmark for evaluating large multimodal models on visual text localization and reasoning, 2024

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This paper cites Smith, Wei-Chiu Ma, and Ranjay Krishna.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Smith, Wei-Chiu Ma, and Ranjay Krishna

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This paper cites Lumina-t2x: Transforming text into any modality, resolution, and dura- tion via flow-based large diffusion transformers, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Lumina-t2x: Transforming text into any modality, resolution, and dura- tion via flow-based large diffusion transformers, 2024

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Observation c5ece020-f293-4eae-85a2-43dcce0cec50 · outbound

This paper cites Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance

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Observation c78fc9af-9c35-49fb-9379-e274a6031276 · outbound

This paper cites Chatglm: A family of large language models from glm-130b to glm-4 all tools, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Chatglm: A family of large language models from glm-130b to glm-4 all tools, 2024

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Observation 24d9c418-a3c1-4770-8901-12ff2e6cc96d · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Making the v in vqa matter: Elevating the role of image understanding in visual question answer- ing

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Observation e87e963a-4527-4e4c-807f-9faec4e66514 · outbound

This paper cites Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024

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Observation c52fba38-7d99-4a5c-a8d5-d72edc5df881 · outbound

This paper cites Denoising dif- fusion probabilistic models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Denoising dif- fusion probabilistic models

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Observation 65865f0e-ac7c-437a-ad06-8ba98191d52c · outbound

This paper cites Cogvlm2: Visual language models for image and video understanding, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Cogvlm2: Visual language models for image and video understanding, 2024

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Observation 928cb6f8-4a69-42c3-beb4-245f80d879fc · outbound

This paper cites Chatgpt for shaping the future of 9 dentistry: the potential of multi-modal large language model.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Chatgpt for shaping the future of 9 dentistry: the potential of multi-modal large language model

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Observation b98100ee-c7ff-44be-b245-1c10baff7f79 · outbound

This paper cites Genmac: Compositional text-to-video generation with multi-agent collaboration, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Genmac: Compositional text-to-video generation with multi-agent collaboration, 2024

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Observation 998299a5-2518-461b-bb68-19aa7336bed3 · outbound

This paper cites Mini-monkey: Alleviating the semantic saw- tooth effect for lightweight mllms via complementary image pyramid, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mini-monkey: Alleviating the semantic saw- tooth effect for lightweight mllms via complementary image pyramid, 2024

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This paper cites Hudson and Christopher D.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Hudson and Christopher D

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This paper cites Ku, Qian Liu, and Wenhu Chen.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Ku, Qian Liu, and Wenhu Chen

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Chatgpt for good? on opportuni- ties and challenges of large language models for education

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Reflective decoding network for image captioning

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

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Observation d4e2799c-b6c2-4394-915b-400f3e2f62d7 · outbound

This paper cites Building and better understanding vision- language models: insights and future directions., 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Building and better understanding vision- language models: insights and future directions., 2024

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Observation b745b877-e7ee-44cc-9cd5-20d6df8ef4ca · outbound

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective What matters when building vision-language models?,

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Llava-onevision: Easy visual task transfer, 2024

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective AutoBencher: Towards Declarative Benchmark Construction

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Llm-grounded video diffusion models, 2024

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Observation 894a6aa1-2230-4cdf-a99e-f594e9c768f1 · outbound

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Vila: On pre-training for visual language models, 2023

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Observation 97984e33-8afc-4b0f-b019-ec6c0f30fff3 · outbound

This paper cites Microsoft coco: Common objects in context.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Microsoft coco: Common objects in context

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Observation d8f55a43-6f18-48cd-87bc-5e13ab9587a1 · outbound

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Improved baselines with visual instruction tuning

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Observation efbb7fb3-2d82-47db-beac-e355f76519c8 · outbound

This paper cites Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Llava-next: Im- proved reasoning, ocr, and world knowledge, 2024

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Observation 6ec08b7a-98d7-4311-a264-2f5311eaa607 · outbound

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MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Tempcom- pass: Do video llms really understand videos?, 2024

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Observation 72df9ccf-b402-4686-831d-2b7fa24dd0f9 · outbound

This paper cites Ocrbench: On the hidden mystery of ocr in large multimodal models, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Ocrbench: On the hidden mystery of ocr in large multimodal models, 2024

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This paper cites Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pages 216–233.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pages 216–233

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.872275Z

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Observation de84a044-9868-4e8b-85c4-d245ff68e623 · outbound

This paper cites Mmdu: A multi-turn multi-image dia- log understanding benchmark and instruction-tuning dataset for lvlms, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mmdu: A multi-turn multi-image dia- log understanding benchmark and instruction-tuning dataset for lvlms, 2024

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Observation 6b2a2f7e-e0dc-4e9b-830f-9fc7de4a394c · outbound

This paper cites Mmalaya2.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mmalaya2

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.839643Z

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Observation 19f4c7ed-d0e8-4f7f-a8f7-e97484ad952e · outbound

This paper cites Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.822483Z

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Observation 1fefffe4-841f-4476-ad1b-aab72a973087 · outbound

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

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Ovis: Structural Embedding Alignment for Multimodal Large Language Model

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Observation dad6b72c-ab48-4ee2-b150-6c4992ebac98 · outbound

This paper cites Mmlongbench-doc: Bench- marking long-context document understanding with visual- izations, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mmlongbench-doc: Bench- marking long-context document understanding with visual- izations, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.806687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 99adf939-6ebf-4b71-abd2-739a3ea8e914 · outbound

This paper cites The llama 3 herd of models, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective The llama 3 herd of models, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.791517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dc7f92d1-c0ea-4920-86d2-78b33d333f96 · outbound

This paper cites Gpt-4o system card, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Gpt-4o system card, 2024

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.775496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f6c63cb7-7aef-443b-a138-e5014b289879 · outbound

This paper cites GPT-4 Technical Report.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective GPT-4 Technical Report

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.625018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eec231ab-3931-4a8f-8ee7-b49b1d93bb09 · outbound

This paper cites Omnidocbench: Benchmarking diverse pdf document parsing with comprehensive annota- tions, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Omnidocbench: Benchmarking diverse pdf document parsing with comprehensive annota- tions, 2024

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.760173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 451e32c6-30bd-46f2-af7d-313d7bfb8822 · outbound

This paper cites Sowing information: Cultivating con- textual coherence with mllms in image generation, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Sowing information: Cultivating con- textual coherence with mllms in image generation, 2024

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.743326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation af72decb-b80c-483c-93b6-e71f39f199fd · outbound

This paper cites Rbdash-v1.2-72b.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Rbdash-v1.2-72b

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.726582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e3ad64d-18be-49fe-8188-374e0702de0b · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective High-resolution image synthesis with latent diffusion models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.711065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2e14a600-424d-46e1-ae8d-9f53737c730d · outbound

This paper cites Eagle: Exploring the design space for multimodal llms with mixture of encoders, 2025.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Eagle: Exploring the design space for multimodal llms with mixture of encoders, 2025

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.695399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4f332b9-96ce-415e-8db0-7f0afaeb2b0d · outbound

This paper cites Journeydb: A benchmark for generative im- age understanding.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Journeydb: A benchmark for generative im- age understanding

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.678629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b7d4203c-012c-4d6f-a4ce-96b627f69fb4 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Gemini: A Family of Highly Capable Multimodal Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.658812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7912cc58-07eb-4614-aa15-2a5fd20f5c43 · outbound

This paper cites Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.663550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca0b0a84-17aa-422e-9259-f029bb20aeaa · outbound

This paper cites Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.668528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0680d9d-1c65-4540-8eff-861fabde1c63 · outbound

This paper cites Llama-3-mixsensev1 1.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Llama-3-mixsensev1 1

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.652759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9e32ecc-4031-4d02-b48e-45a77f86cbea · outbound

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

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.678916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77e1f016-8d2a-4f80-bf98-81ea93970981 · outbound

This paper cites Large-scale multi-modal pre-trained models: A comprehensive survey.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Large-scale multi-modal pre-trained models: A comprehensive survey

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.638570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d911fd21-c8b9-428b-b48d-0bd46701a678 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.623022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7530f209-eea4-4070-a986-39e837a3f2e5 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective BloombergGPT: A Large Language Model for Finance

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.693315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10ba1df2-2978-4223-94fa-ad2afe866761 · outbound

This paper cites Unigen: A unified framework for textual dataset generation using large language models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unigen: A unified framework for textual dataset generation using large language models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.698376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec0b6ef1-fb73-4fd3-8e0b-71d15839f9ec · outbound

This paper cites Self-correcting llm-controlled diffu- sion models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Self-correcting llm-controlled diffu- sion models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.607735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90e9bae8-6ace-4529-8971-259e9c382a40 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.592508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b007837a-dc2f-44b1-b02d-f0988bbd5bd7 · outbound

This paper cites LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.711740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1017213b-7fe3-4803-b0f4-1117cc6fb4bb · outbound

This paper cites xgen-mm (blip-3): A family of open large multimodal models, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective xgen-mm (blip-3): A family of open large multimodal models, 2024

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.576802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2eff9fe7-f24f-4fac-a20e-ae515ea03c3c · outbound

This paper cites Cc-ocr: A comprehensive and challenging ocr benchmark for evalu- ating large multimodal models in literacy, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Cc-ocr: A comprehensive and challenging ocr benchmark for evalu- ating large multimodal models in literacy, 2024

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.561138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a146a39-7414-4757-a6de-acab5baa365d · outbound

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

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.726534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7df529b8-8387-446e-9b09-be541edef8e3 · outbound

This paper cites Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.545432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6aa2bdd9-6a97-435c-b870-3ba4ce4dd882 · outbound

This paper cites Benchmarking chinese text recognition: Datasets, baselines, and an empirical study, 2022.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Benchmarking chinese text recognition: Datasets, baselines, and an empirical study, 2022

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.529052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 695ee012-2c3b-46ae-bbba-e70926fb0b97 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.740916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec4128b2-cdd5-4f5d-b7a5-01df68b31685 · outbound

This paper cites Mm-vet: Evaluating large multimodal models for integrated capabilities, 2023.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Mm-vet: Evaluating large multimodal models for integrated capabilities, 2023

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.512768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d00654b8-e5bc-4326-a09e-6b903bbc1853 · outbound

This paper cites Task Me Anything.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Task Me Anything

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.750706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e43a91c-b0d8-44d8-b76c-198276ae641d · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T15:39:32.756471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b12178ac-ae59-4a29-a9c0-45ea07ced1ab · outbound

This paper cites Omchat: A recipe to train multimodal language models with strong long context and video under- standing, 2024.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Omchat: A recipe to train multimodal language models with strong long context and video under- standing, 2024

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.496825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 254e35a6-d337-45af-8368-ab56ccc548e9 · outbound

This paper cites Dyval: Dynamic evalua- tion of large language models for reasoning tasks.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Dyval: Dynamic evalua- tion of large language models for reasoning tasks

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.480755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a8b3be0-124b-4f00-980f-eceea2f9ad56 · outbound

This paper cites role”, “definition.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective role”, “definition

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.463792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a295e12-c4d6-4c4a-aec9-35beabeab30d · outbound

This paper cites image pattern.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective image pattern

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.430819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f766ab4-efdc-4edb-b508-1d5d5eea9f56 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.415152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9fe9aa89-99dd-4282-9ab5-ad91dd43825c · outbound

This paper cites Surreal”: 2262, “Lighting.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Surreal”: 2262, “Lighting

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.397689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 165296a6-f543-4b96-9ec8-fe604d315a75 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.447604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e18433df-7137-4cd0-9fe9-44f9097ecb03 · outbound

This paper cites # Key Points.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective # Key Points

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.382471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7d7f9315-0a39-49e0-91fc-20d079ce331d · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.367650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff20a192-012f-46d2-9461-884fdf8d3c61 · outbound

This paper cites You may annotate multiple patterns as appropriate.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective You may annotate multiple patterns as appropriate

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.351417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cb493ce5-771e-4a9d-a2a8-cd789f8efacb · outbound

This paper cites Surreal”: “This pattern is characterized by its prevalence in depicting scenes that mix elements of fantasy with reality, often creating imaginative or dream-like visuals.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Surreal”: “This pattern is characterized by its prevalence in depicting scenes that mix elements of fantasy with reality, often creating imaginative or dream-like visuals

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.334412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8a05b0ac-0152-48d7-9186-ce600dc46680 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.317571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35228db3-7b17-4e64-868b-e644dd2c0fb4 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.301575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5da42579-5ce4-4599-b205-0e82eb4f5245 · outbound

This paper cites an unresolved cited work.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective Unresolved cited work

Reference 96

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:39:33.286138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a416d5f0-2a35-4b0e-946e-751778cb5ece · outbound

This paper cites BHNORAK TOP.

MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective BHNORAK TOP

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:39:33.269335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers