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Collections including paper arxiv:2410.02740

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6 • 25
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 12
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 38
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

Interesting Papers

These papers are interesting (to me)

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Paper • 2410.02740 • Published Oct 3 • 52
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging

Paper • 2410.01215 • Published Oct 2 • 30
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25 • 99
EuroLLM: Multilingual Language Models for Europe

Paper • 2409.16235 • Published Sep 24 • 24

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Paper • 2410.02740 • Published Oct 3 • 52

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Paper • 2408.10188 • Published Aug 19 • 51
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Paper • 2408.08872 • Published Aug 16 • 97
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22 • 116
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Paper • 2408.12528 • Published Aug 22 • 50

PDFTriage: Question Answering over Long, Structured Documents

Paper • 2309.08872 • Published Sep 16, 2023 • 53
Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 77
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 39
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 16

General Multimodal Learning

Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities

Paper • 2401.14405 • Published Jan 25 • 11
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

Paper • 2406.18521 • Published Jun 26 • 25
xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations

Paper • 2408.12590 • Published Aug 22 • 33
Law of Vision Representation in MLLMs

Paper • 2408.16357 • Published Aug 29 • 92

Video Understanding

Vript: A Video Is Worth Thousands of Words

Paper • 2406.06040 • Published Jun 10 • 22
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Paper • 2406.04325 • Published Jun 6 • 71
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Paper • 2406.01574 • Published Jun 3 • 42
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Paper • 2405.21075 • Published May 31 • 18

iVideoGPT: Interactive VideoGPTs are Scalable World Models

Paper • 2405.15223 • Published May 24 • 12
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 85
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27 • 30

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training

Paper • 2311.17049 • Published Nov 28, 2023
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7 • 13
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

Paper • 2303.17376 • Published Mar 30, 2023
Sigmoid Loss for Language Image Pre-Training

Paper • 2303.15343 • Published Mar 27, 2023 • 4

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