Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward | Paper Citation Record

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward online" 'onlinestring :=

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward write newline

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Understanding intermediate layers using linear classifier probes

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Flamingo: a Visual Language Model for Few-Shot Learning

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward See It from My Perspective: How Language Affects Cultural Bias in Image Understanding

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Qwen Technical Report

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agents

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward The Llama 3 Herd of Models

Reference 21

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward BLINK: Multimodal Large Language Models Can See but Not Perceive

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward H2OVL-Mississippi Vision Language Models Technical Report

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Self-Correction is More than Refinement: A Learning Framework for Visual and Language Reasoning Tasks

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MMBoundary: Advancing MLLM Knowledge Boundary Awareness through Reasoning Step Confidence Calibration

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Uncovering Bias in Large Vision-Language Models with Counterfactuals

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLM

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Mistral 7B

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Benchmarking Cognitive Biases in Large Language Models as Evaluators

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward VHELM: A Holistic Evaluation of Vision Language Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward The Power of Scale for Parameter-Efficient Prompt Tuning

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward LLaVA-OneVision: Easy Visual Task Transfer

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward SEED-Bench-2: Benchmarking Multimodal Large Language Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward HEMM: Holistic Evaluation of Multimodal Foundation Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Visual Instruction Tuning

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MMBench: Is Your Multi-modal Model an All-around Player?

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward DeepSeek-VL: Towards Real-World Vision-Language Understanding

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward RePaint: Inpainting using Denoising Diffusion Probabilistic Models

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Understanding the Effective Receptive Field in Deep Convolutional Neural Networks

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward GPT-4 Technical Report

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward DINOv2: Learning Robust Visual Features without Supervision

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Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Fung, Weizhu Chen, Minhao Cheng, and Furu Wei

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.942314Z

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Observation 59fac2be-1fed-4eb4-93ce-d1457a97f957 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Learning Transferable Visual Models From Natural Language Supervision

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.946890Z

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Observation 8887fab4-65cf-4412-9199-5ecaedfbfb23 · outbound

This paper cites Do Vision Transformers See Like Convolutional Neural Networks?.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Do Vision Transformers See Like Convolutional Neural Networks?

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.951802Z

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Observation 4fc1710d-c783-46fa-aa99-7f0434b99d22 · outbound

This paper cites an unresolved cited work.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

Reference 61

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Observation 8d42653b-fb23-4fa9-9598-e93da7c83d6f · outbound

This paper cites an unresolved cited work.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.961208Z

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Observation 6e7b3624-e1ef-44ea-b6c7-b0ad977327e2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward LLaMA: Open and Efficient Foundation Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.966661Z

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Observation f4adc990-3dc9-41f2-94b0-f50969ae1594 · outbound

This paper cites Is ChatGPT a Good NLG Evaluator? A Preliminary Study.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Is ChatGPT a Good NLG Evaluator? A Preliminary Study

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.971339Z

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Observation 8b9c1474-9b5a-4f77-9bfe-1f1c04b2e7e5 · outbound

This paper cites To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.976358Z

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Observation de59de8d-922f-4c0d-bb8b-d3596fbe2d23 · outbound

This paper cites Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.981135Z

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Observation 7ccbd96a-56da-4428-b16e-9c6134bf9dc0 · outbound

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

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.985980Z

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Observation 0d8d37d1-8d89-41ba-8052-6ca97de4ea45 · outbound

This paper cites VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.990724Z

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Observation 3eee00be-a2b6-4228-9583-7cfae4873657 · outbound

This paper cites EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:39.995700Z

Source-reported events for the cited work

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Observation 972bbe9d-0cd6-4950-ae6b-8ab2272aabcf · outbound

This paper cites CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward CALM: Unleashing the Cross-Lingual Self-Aligning Ability of Language Model Question Answering

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:01:40.448586Z

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 d085772f-4ad8-4177-9522-0bbf42e505ff · outbound

This paper cites V*: Guided Visual Search as a Core Mechanism in Multimodal LLMs.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward V*: Guided Visual Search as a Core Mechanism in Multimodal LLMs

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.010747Z

Source-reported events for the cited work

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Observation 54803c1c-4f9f-43f5-8e39-a41e4de698cc · outbound

This paper cites an unresolved cited work.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:01:41.824079Z

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 e2415dfe-1ed6-4450-ad08-508b124350ed · outbound

This paper cites Sadler, Dinesh Manocha, and Amrit Bedi.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Sadler, Dinesh Manocha, and Amrit Bedi

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:41.805654Z

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 d3382be4-a904-4460-8a3b-1e7de1b34b7d · outbound

This paper cites CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.025936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0922a4bb-0077-4694-b316-048a59fc417c · outbound

This paper cites GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.030970Z

Source-reported events for the cited work

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Observation 6aa326c0-2ad9-43b2-aedd-a54905e6fd8e · outbound

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

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.035975Z

Source-reported events for the cited work

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Observation 4c6d869c-3eb4-4f67-b1e1-6f2f1bfcabc1 · outbound

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

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.040858Z

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Observation a75edee2-559d-49d5-8e73-38109433dc06 · outbound

This paper cites AppAgent: Multimodal Agents as Smartphone Users.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward AppAgent: Multimodal Agents as Smartphone Users

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.046199Z

Source-reported events for the cited work

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Observation f46a637a-2a90-47e8-a35d-77a7e578fd7f · outbound

This paper cites B-AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Black-box Adversarial Visual-Instructions.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward B-AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Black-box Adversarial Visual-Instructions

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.051890Z

Source-reported events for the cited work

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Observation d7057694-7f5b-47c6-ba10-83085e0531f5 · outbound

This paper cites VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.057148Z

Source-reported events for the cited work

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Observation 88c25f89-f030-4fce-b34f-1cf6a821bafd · outbound

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

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.063205Z

Source-reported events for the cited work

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Observation dabc7c38-4091-404a-81af-d52e9aeafb39 · outbound

This paper cites SVIT: Scaling up Visual Instruction Tuning.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward SVIT: Scaling up Visual Instruction Tuning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.068908Z

Source-reported events for the cited work

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Observation 80d7c525-3310-4514-b9ec-67852d498a50 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.074153Z

Source-reported events for the cited work

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Observation dc96f8b9-6047-48d9-ab5a-b7f50bfb9628 · outbound

This paper cites Calibrated Self-Rewarding Vision Language Models.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward Calibrated Self-Rewarding Vision Language Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.079295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 168bf0b1-a005-45c2-8981-8aab8554305f · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:40.085249Z

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