SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement | Paper Citation Record

Observation 87a779a4-5d37-4ccc-9100-ca4a1055b45e · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Flamingo: a visual language model for few-shot learning

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This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

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This paper cites Qwen2.5-VL Technical Report.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Qwen2.5-VL Technical Report

Reference 4

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This paper cites OCR-IDL: OCR Annotations for Industry Document Library Dataset.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement OCR-IDL: OCR Annotations for Industry Document Library Dataset

Reference 5

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This paper cites Coyo-700m: Image-text pair dataset.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Coyo-700m: Image-text pair dataset

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This paper cites Reversible Column Networks.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Reversible Column Networks

Reference 7

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This paper cites InternLM2 Technical Report.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement InternLM2 Technical Report

Reference 8

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement An augmented benchmark dataset for geometric question answering through dual parallel text encoding

Reference 9

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This paper cites End-to-end object detection with transformers.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement End-to-end object detection with transformers

Reference 10

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Observation 846e9db1-cacd-4b1a-ac71-bd61cb2742e9 · outbound

This paper cites Sharegpt4v: Improving large multi-modal models with better captions.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Sharegpt4v: Improving large multi-modal models with better captions

Reference 11

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 12

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Observation 190292f5-0b9c-450d-b19e-a5b00cc01660 · outbound

This paper cites Vision Transformer Adapter for Dense Predictions.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Vision Transformer Adapter for Dense Predictions

Reference 13

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 14

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This paper cites How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites

Reference 15

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 16

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Opencompass: A universal evaluation platform for foundation models

Reference 17

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This paper cites Grok-1.5 vision preview: Connecting the digital and physicalworlds with our first multimodal model, 2024.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Grok-1.5 vision preview: Connecting the digital and physicalworlds with our first multimodal model, 2024

Reference 18

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This paper cites Sharegpt-4o: Comprehensive multimodal annotations with gpt-4o, 2024.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Sharegpt-4o: Comprehensive multimodal annotations with gpt-4o, 2024

Reference 19

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This paper cites Deformable convolutional networks.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Deformable convolutional networks

Reference 20

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This paper cites Scaling vision transformers to 22 billion parameters.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Scaling vision transformers to 22 billion parameters

Reference 21

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This paper cites Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Reference 22

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Imagenet: A large- scale hierarchical image database

Reference 23

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This paper cites Scalable Vision Language Model Training via High Quality Data Curation.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Scalable Vision Language Model Training via High Quality Data Curation

Reference 24

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This paper cites Benchmarking and Improving Detail Image Caption.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Benchmarking and Improving Detail Image Caption

Reference 25

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This paper cites Adalrs: Loss- guided adaptive learning rate search for efficient foundation model pretraining.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Adalrs: Loss- guided adaptive learning rate search for efficient foundation model pretraining

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Vlmevalkit: An open-source toolkit for evaluating large multi-modality models

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Scalable Pre-training of Large Autoregressive Image Models

Reference 29

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Scaling Language-Free Visual Representation Learning

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Data Filtering Networks

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Slowfast networks for video recognition

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Multimodal Autoregressive Pre-training of Large Vision Encoders

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mme: A comprehensive evaluation benchmark for multimodal large language models, 2024

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Making the v in vqa matter: Elevating the role of image understanding in visual question answering

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction Data

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mask r-cnn

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Deep residual learning for image recognition

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This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization,.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement The many faces of robustness: A critical analysis of out-of-distribution generalization,

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Natural adversarial examples, 2021

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Squeeze-and-excitation networks

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image Pyramid

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Scaling up visual and vision-language representation learning with noisy text supervision

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Deep visual-semantic alignments for generating image de- scriptions

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement A diagram is worth a dozen images

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Lisa: Reasoning segmentation via large language model

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This paper cites Building and better under- standing vision-language models: insights and future directions.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Building and better under- standing vision-language models: insights and future directions

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This paper cites What matters when building vision-language models? Advances in Neural Information Processing Systems, 37:87874– 87907, 2024.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement What matters when building vision-language models? Advances in Neural Information Processing Systems, 37:87874– 87907, 2024

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement LLaVA-OneVision: Easy Visual Task Transfer

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models

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This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

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This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Evaluating Object Hallucination in Large Vision-Language Models

Reference 55

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Observation 0283545d-c372-412b-b1ce-0e4581157c35 · outbound

This paper cites Improved baselines with visual instruction tuning.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Improved baselines with visual instruction tuning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:16.185468Z

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Observation 4a2fe0a4-b236-4c80-8df4-5eaf3dd23463 · outbound

This paper cites Visual instruction tuning.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Visual instruction tuning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.961535Z

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Observation a5a01265-787c-40d3-adc5-597f0b495cdd · outbound

This paper cites Muon is Scalable for LLM Training.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Muon is Scalable for LLM Training

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:06.548354Z

Source-reported events for the cited work

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Observation ae89d1a8-3bec-4090-ba17-80b3218be92e · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mmbench: Is your multi-modal model an all-around player? In European conference on computer vision, pages 216–233

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.741340Z

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Observation 345b18e4-314a-4e36-8430-5d72da46ed77 · outbound

This paper cites Ocrbench: on the hidden mystery of ocr in large multimodal models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Ocrbench: on the hidden mystery of ocr in large multimodal models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.552804Z

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Observation 2df5e4c3-e566-4e69-b955-7148d92b9383 · outbound

This paper cites Decoupled Weight Decay Regularization.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Decoupled Weight Decay Regularization

Reference 61

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Source-reported events for the cited work

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Observation e37a86bd-b7da-4470-9ad4-db79d3c5e662 · outbound

This paper cites DeepSeek-VL: Towards Real-World Vision-Language Understanding.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement DeepSeek-VL: Towards Real-World Vision-Language Understanding

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:06.917722Z

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Observation a29d00c8-d994-499b-a20e-78726d285db5 · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:07.020742Z

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Observation bbbcbdee-0cf1-4a78-ac00-b63f7b284021 · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.393314Z

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Observation ed625676-9ef6-457f-8452-fdcc4955ba73 · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:07.221154Z

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Observation aea5201b-43bc-4e53-925d-97fcc6f8ebe8 · outbound

This paper cites Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:07.312239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 831dbd81-8405-4b6e-8b64-aefbf16eef2b · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Ok-vqa: A visual question answering benchmark requiring external knowledge

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.233277Z

Source-reported events for the cited work

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Observation 63e2f7dd-ad86-4244-a702-b01fb1db3d3a · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:07.511190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fde217ee-d772-4282-b2c7-64e7d15c94d0 · outbound

This paper cites Infographicvqa.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Infographicvqa

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:15.058601Z

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Observation 01ba0488-e905-41f9-87f4-b2895e1b06cd · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Docvqa: A dataset for vqa on document images

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.878279Z

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Observation 1afdc95a-9888-4be3-a8da-0751921568e7 · outbound

This paper cites Ocr-vqa: Visual question answering by reading text in images.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Ocr-vqa: Visual question answering by reading text in images

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.694685Z

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Observation d7e7995f-9a97-4699-b4fa-2833ed44db52 · outbound

This paper cites Introducing chatgpt, 2022.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Introducing chatgpt, 2022

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.509068Z

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Observation 65d44a07-4e93-4451-bfc2-fb2aad7ba817 · outbound

This paper cites Learning transferable visual models from natural language supervision.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Learning transferable visual models from natural language supervision

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.329003Z

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Observation b61bca55-9d38-466c-a543-7801a7c5a1d9 · outbound

This paper cites Zero: Memory opti- mizations toward training trillion parameter models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Zero: Memory opti- mizations toward training trillion parameter models

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.195330Z

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Observation cbcbd198-0e40-451d-bb14-ea29fa46ad0a · outbound

This paper cites Do imagenet classifiers generalize to imagenet?, 2019.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Do imagenet classifiers generalize to imagenet?, 2019

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:14.040246Z

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Observation 67b0689a-37ba-48e2-97be-68b05328c0e7 · outbound

This paper cites Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:08.277308Z

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Observation 9f4b5191-474d-4218-a490-47ba5b5a4763 · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:08.389462Z

Source-reported events for the cited work

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Observation 129c05bc-c99d-480f-9f80-c2b7fbf1fc79 · outbound

This paper cites Hollywood in homes: Crowdsourcing data collection for activity understanding.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Hollywood in homes: Crowdsourcing data collection for activity understanding

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.840234Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d499bfdf-0ff9-40e4-b799-59f07d5dab77 · outbound

This paper cites Towards vqa models that can read.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Towards vqa models that can read

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.673354Z

Source-reported events for the cited work

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Observation 446b6f94-7e19-4f2a-bf2f-8b0c05c62892 · outbound

This paper cites Kimi-VL Technical Report.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Kimi-VL Technical Report

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:08.679854Z

Source-reported events for the cited work

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Observation e03a2961-db65-42c8-b3da-05e24ef9ad89 · outbound

This paper cites Qwen3, April 2025.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Qwen3, April 2025

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.554335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fcb05f98-913a-4806-b5f8-fbd495febd22 · outbound

This paper cites Openhermes 2.5: An open dataset of synthetic data for generalist llm assistants,.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Openhermes 2.5: An open dataset of synthetic data for generalist llm assistants,

Reference 82

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Observation 366e44a7-412d-4023-a12b-e1e04d53176d · outbound

This paper cites Cambrian-1: A fully open, vision-centric exploration of multimodal llms.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Cambrian-1: A fully open, vision-centric exploration of multimodal llms

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.392724Z

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Observation 01b2c095-0adc-41bd-b71b-925321588093 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.011049Z

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Observation 84feef7a-bfbd-46ec-adaa-a9571bf3c6ae · outbound

This paper cites VGR: Visual Grounded Reasoning.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement VGR: Visual Grounded Reasoning

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.114205Z

Source-reported events for the cited work

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Observation 68de02d4-03e1-4ab7-b0da-48d7c9ffbfc4 · outbound

This paper cites World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and Filtering.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and Filtering

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.193598Z

Source-reported events for the cited work

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Observation 99cb87b7-ae69-4d36-a51b-54a0499edfd3 · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.284570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34bcd4d3-5a97-49c0-87ce-d15e2db08641 · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Pvt v2: Improved baselines with pyramid vision transformer

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.252292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 275553a3-2d36-4427-becc-762e4e7daf42 · outbound

This paper cites Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.464295Z

Source-reported events for the cited work

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Observation df4f8766-c159-4818-9a53-645cf33e705d · outbound

This paper cites DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding

Reference 90

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 42533c59-304e-48d5-b8b2-58c198e861a9 · outbound

This paper cites Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents

Reference 91

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:53:11.031292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 21a80b97-285b-427d-8e2a-9042d2fba491 · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Convnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:13.058543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 665e9818-9536-480e-a7e3-16e73fe9a998 · outbound

This paper cites Seeing the image: Prioritizing visual correlation by contrastive alignment.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Seeing the image: Prioritizing visual correlation by contrastive alignment

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:12.875815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e00b62d-a9a6-4216-aa41-1eb5feb23ef1 · outbound

This paper cites Aggregated residual transformations for deep neural networks.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Aggregated residual transformations for deep neural networks

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:12.734487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3da9d2ac-8853-4031-9f32-69a7b568ddd4 · outbound

This paper cites Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:09.990394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b775d07d-d57c-4e11-ac09-ae766d755e34 · outbound

This paper cites Qwen2.5 Technical Report.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Qwen2.5 Technical Report

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:10.097531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7de236ae-333d-48c8-ab3d-74acdbdccaac · outbound

This paper cites Pediatricsgpt: Large language models as chinese medical assistants for pediatric applications.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Pediatricsgpt: Large language models as chinese medical assistants for pediatric applications

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:12.585192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 431a2d12-4355-440a-81a5-9cd058174da8 · outbound

This paper cites Improving factuality in large language models via decoding-time hallucinatory and truthful comparators.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Improving factuality in large language models via decoding-time hallucinatory and truthful comparators

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:12.432758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 841289a6-f86c-493d-9105-fad874f1c0bb · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:10.285746Z

Source-reported events for the cited work

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Observation 559193a3-2037-4663-b025-4d310ebbb974 · outbound

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

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Mmmu: A massive multi-discipline multi- modal understanding and reasoning benchmark for expert agi

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:12.313580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers