Qa dataset explosion: A taxonomy of nlp resources for question answering and reading comprehension
Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …
there has been much work on benchmark datasets needed to track modeling progress …
Monkey: Image resolution and text label are important things for large multi-modal models
Z Li, B Yang, Q Liu, Z Ma, S Zhang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Large Multimodal Models (LMMs) have shown promise in vision-language tasks but
struggle with high-resolution input and detailed scene understanding. Addressing these …
struggle with high-resolution input and detailed scene understanding. Addressing these …
Pix2struct: Screenshot parsing as pretraining for visual language understanding
Visually-situated language is ubiquitous—sources range from textbooks with diagrams to
web pages with images and tables, to mobile apps with buttons and forms. Perhaps due to …
web pages with images and tables, to mobile apps with buttons and forms. Perhaps due to …
Cogagent: A visual language model for gui agents
People are spending an enormous amount of time on digital devices through graphical user
interfaces (GUIs) eg computer or smartphone screens. Large language models (LLMs) such …
interfaces (GUIs) eg computer or smartphone screens. Large language models (LLMs) such …
Qwen-vl: A frontier large vision-language model with versatile abilities
In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models
(LVLMs) designed to perceive and understand both texts and images. Starting from the …
(LVLMs) designed to perceive and understand both texts and images. Starting from the …
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin… - arXiv preprint arXiv …, 2024 - arxiv.org
In this report, we present the latest model of the Gemini family, Gemini 1.5 Pro, a highly
compute-efficient multimodal mixture-of-experts model capable of recalling and reasoning …
compute-efficient multimodal mixture-of-experts model capable of recalling and reasoning …
Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
The exponential growth of large language models (LLMs) has opened up numerous
possibilities for multi-modal AGI systems. However the progress in vision and vision …
possibilities for multi-modal AGI systems. However the progress in vision and vision …
Bliva: A simple multimodal llm for better handling of text-rich visual questions
Vision Language Models (VLMs), which extend Large Language Models (LLM) by
incorporating visual understanding capability, have demonstrated significant advancements …
incorporating visual understanding capability, have demonstrated significant advancements …
HallusionBench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models
We introduce" HallusionBench" a comprehensive benchmark designed for the evaluation of
image-context reasoning. This benchmark presents significant challenges to advanced large …
image-context reasoning. This benchmark presents significant challenges to advanced large …
Pali-x: On scaling up a multilingual vision and language model
We present the training recipe and results of scaling up PaLI-X, a multilingual vision and
language model, both in terms of size of the components and the breadth of its training task …
language model, both in terms of size of the components and the breadth of its training task …