Paper Citation Record · LEDGER

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

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2404.16790.

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

pith.paper-citation-record.v1
2404.16790 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:48:30.185030Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-05T04:30:40.718071Z

Reference resolution

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

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

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:59:32.782957Z

Source-reported events for the cited work

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Observation bf601f4f-cc32-4b4f-884f-34104f92a460 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:23:58.074856Z

Source-reported events for the cited work

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Observation 7fed4a12-5eaf-40e0-bb7f-58a14df4529b · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:33:26.706356Z

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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

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:41:08.337965Z

Source-reported events for the cited work

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Observation d0599d4f-1320-4427-957d-93ceb82ad4d3 · inbound

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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Observation 3e46d437-d4fa-4afc-800a-916d564b420e · inbound

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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Observation e446c60f-acc8-4f68-9a7d-af9aa250ad29 · inbound

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

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

Reference 29

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Observation 26a51221-4347-4ac5-88fe-8b51366e9d8b · inbound

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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Source-reported events for the cited work

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Observation 92bbbf6b-91b7-40b3-8fd0-8423d9c3780a · inbound

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

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

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:58:59.159584Z

Source-reported events for the cited work

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Observation 93a3a951-c912-49f2-8512-585b1fc62165 · inbound

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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Observation a1b56a09-3792-4a48-af5c-26eeedbf0746 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-16T05:32:29.335668Z

Source-reported events for the cited work

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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

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:20:11.514676Z

Source-reported events for the cited work

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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

Resolution: verified exact; arxiv_id, observed 2026-05-16T16:01:05.178856Z

Source-reported events for the cited work

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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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Observation 87b8e29e-dfbe-4f72-81af-26fe4762df7f · inbound

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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Observation e40648cf-11bb-41eb-af3e-203b45d85a7d · inbound

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

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

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:20:53.805058Z

Source-reported events for the cited work

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Observation 3e929891-5d7f-4ccf-9fc2-81d28e7affe8 · 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

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:11:04.284210Z

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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

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:01:26.854067Z

Source-reported events for the cited work

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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

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:27:29.383248Z

Source-reported events for the cited work

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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

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

Reference 69

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+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

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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

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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

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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

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