SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension | Paper Citation Record

Observation eb1b67c9-cb8f-4cf3-9bed-c91a0b6ad9eb · inbound

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? cites this paper.

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 32

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MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs cites this paper.

MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 40

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Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey cites this paper.

Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 230

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Detailed Object Description with Controllable Dimensions cites this paper.

Detailed Object Description with Controllable Dimensions SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 57

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GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks cites this paper.

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 21

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Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey cites this paper.

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 26

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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? SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 31

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EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios cites this paper.

EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 24

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

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 125

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OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning cites this paper.

OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 15

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Observation 611c7e4c-0ec4-4ffb-99de-ecdc32dfe686 · inbound

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment cites this paper.

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 33

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Observation 6ffa1d7f-aaee-47f1-9efa-8d2f643abf52 · inbound

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

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 61

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SeriesBench: A Benchmark for Narrative-Driven Drama Series Understanding cites this paper.

SeriesBench: A Benchmark for Narrative-Driven Drama Series Understanding SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 15

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GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling cites this paper.

GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 10

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Observation 31e98ba9-e124-4b41-b4d7-cd1e9217cb1a · inbound

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning cites this paper.

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 34

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ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation cites this paper.

ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 41

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Reasoning-OCR: Can Large Multimodal Models Solve Complex Logical Reasoning Problems from OCR Cues? cites this paper.

Reasoning-OCR: Can Large Multimodal Models Solve Complex Logical Reasoning Problems from OCR Cues? SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 12

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Observation a5bc9a1d-66e4-4615-8dc2-80065ca6c88b · inbound

OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning cites this paper.

OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 23

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ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models cites this paper.

ID-Align: RoPE-Conscious Position Remapping for Dynamic High-Resolution Adaptation in Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 21

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FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation cites this paper.

FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 22

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Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces cites this paper.

Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 53

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Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review cites this paper.

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 203

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MiMo-VL Technical Report cites this paper.

MiMo-VL Technical Report SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 25

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Native Visual Understanding: Resolving Resolution Dilemmas in Vision-Language Models cites this paper.

Native Visual Understanding: Resolving Resolution Dilemmas in Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 19

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GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 54

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Observation 0f0d8dc1-58fc-44ab-9453-12b949975ae9 · inbound

ProactiveVideoQA: A Comprehensive Benchmark Evaluating Proactive Interactions in Video Large Language Models cites this paper.

ProactiveVideoQA: A Comprehensive Benchmark Evaluating Proactive Interactions in Video Large Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 12

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

MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 29

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MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents cites this paper.

MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 17

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

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 59

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BLUEX Revisited: Enhancing Benchmark Coverage with Automatic Captioning cites this paper.

BLUEX Revisited: Enhancing Benchmark Coverage with Automatic Captioning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 16

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DeepEyesV2: Toward Agentic Multimodal Model cites this paper.

DeepEyesV2: Toward Agentic Multimodal Model SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 25

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Observation 8b799e30-2925-4d39-a890-2e38cc6736f3 · inbound

FinCriticalED: A Visual Benchmark for Financial Fact-Level OCR cites this paper.

FinCriticalED: A Visual Benchmark for Financial Fact-Level OCR SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 13

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Observation d2f8dcbc-db99-45ae-9962-7e9141e36ba9 · inbound

Forest Before Trees: Latent Superposition for Efficient Visual Reasoning cites this paper.

Forest Before Trees: Latent Superposition for Efficient Visual Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 43

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Observation 9ed6f8f7-af64-4e22-8ed1-c90afa19f5ab · inbound

Learning More from Less: Unlocking Internal Representations for Benchmark Compression cites this paper.

Reference 2025

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Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion cites this paper.

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 20

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

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 15

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Visual Enhanced Depth Scaling for Multimodal Latent Reasoning cites this paper.

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 29

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Observation 4adad9f9-fad9-43a7-8d8e-15396f9d3750 · inbound

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning cites this paper.

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 29

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Observation 4b66fcbb-5d88-4ff7-abdd-cff4dad2ba57 · inbound

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning cites this paper.

Visual Enhanced Depth Scaling for Multimodal Latent Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 29

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Observation f451cf29-e6b8-4dd3-a0e5-1b08896683eb · inbound

Aligning What Vision-Language Models See and Perceive with Adaptive Information Flow cites this paper.

Aligning What Vision-Language Models See and Perceive with Adaptive Information Flow SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:03:24.877582Z

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Observation 75727995-6101-4240-89b7-3e9c522d0f1c · inbound

HyLaR: Hybrid Latent Reasoning with Decoupled Policy Optimization cites this paper.

HyLaR: Hybrid Latent Reasoning with Decoupled Policy Optimization SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 19

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Observation b0fe877f-5bf5-449c-9e76-3a59ace3047f · inbound

HyLaR: Hybrid Latent Reasoning with Decoupled Policy Optimization cites this paper.

HyLaR: Hybrid Latent Reasoning with Decoupled Policy Optimization SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 19

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Observation abb05a70-1fbc-41c8-a357-413b306d3a7e · inbound

DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging cites this paper.

DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:42:58.909922Z

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

Observation 16914475-6daa-40bb-ad3e-c59290015fe3 · inbound

DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging cites this paper.

DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-21T09:14:05.730394Z

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Observation 579364dd-983f-4c76-bfd3-ebb0c2944b74 · inbound

Deep Pre-Alignment for VLMs cites this paper.

Deep Pre-Alignment for VLMs SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 146

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Observation efcc01c1-daba-4837-90d9-1bdce7d19ce4 · inbound

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding cites this paper.

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:43:38.878107Z

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Observation 46758ddf-3d42-469b-872d-32c4c5cb52da · inbound

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models cites this paper.

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-02T17:37:14.447465Z

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Observation 0ecaf041-da59-4b17-bf3e-18d4eb31c305 · inbound

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning cites this paper.

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.039683Z

Source-reported events for the cited work

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

Observation 929228b3-17f2-4f93-a933-9619e559e750 · inbound

HPP: Hierarchical Programmatic Probing for Long Video Understanding by Decoupling Perception and Reasoning cites this paper.

HPP: Hierarchical Programmatic Probing for Long Video Understanding by Decoupling Perception and Reasoning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 171

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T06:39:37.641668Z

Source-reported events for the cited work

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

Observation 7c4026ce-6994-4e23-8df0-612519f719b0 · inbound

ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering cites this paper.

ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:39:57.614558Z

Source-reported events for the cited work

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

Observation 238a0bfb-d25a-41b8-90ea-c3601466b7c3 · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 149

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:45:47.731258Z

Source-reported events for the cited work

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

Observation 8e6216d3-e66c-4f9a-9e92-8eb022bc2b9a · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 149

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:24.162441Z

Source-reported events for the cited work

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

Observation 73ee3721-3cd8-460a-a73f-6e71170c2f86 · inbound

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning cites this paper.

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:07:03.920797Z

Source-reported events for the cited work

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

Observation 6c79f30b-a7c0-4f88-904a-6c8d6a29cdf5 · inbound

Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions cites this paper.

Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T01:58:01.879688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8adfbc4-0697-4892-8d1e-9bce6b39468f · inbound

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model cites this paper.

Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 143

Resolution: unresolved; no resolver link, observed 2026-07-31T06:20:14.200481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6899fd5-23ac-494e-848d-f0574a043eac · inbound

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs cites this paper.

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T04:16:08.312878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

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