Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

Abstract Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks across different data modalities. A PFM (eg, BERT, ChatGPT, GPT-4) is …

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 …

A big convergence of language, vision, and multimodal pretraining is emerging. In this work,
we introduce a general-purpose multimodal foundation model BEiT-3, which achieves …

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 …

Large multimodal models (LMMs) extend large language models (LLMs) with multi-sensory
skills, such as visual understanding, to achieve stronger generic intelligence. In this paper …

In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning
model pretrained on narrated videos which are readily-available at scale. The Vid2Seq …

This paper presents a new framework for open-vocabulary semantic segmentation with the
pre-trained vision-language model, named SAN. Our approach models the semantic …

We present X-Decoder, a generalized decoding model that can predict pixel-level
segmentation and language tokens seamlessly. X-Decoder takes as input two types of …

Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …