This paper presents an in-depth study of ChatGPT, a state-of-the-art language model that is
revolutionizing generative text. We provide a comprehensive analysis of its architecture …

The new era of technology has brought us to the point where it is convenient for people to
share their opinions over an abundance of platforms. These platforms have a provision for …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Video question answering (VideoQA) is a complex task that requires diverse multi-modal
data for training. Manual annotation of question and answers for videos, however, is tedious …

Large-scale Transformer-based models trained for generation tasks (eg, GPT-3) have
recently attracted huge interest, emphasizing the need for system support for serving models …

As humans, we navigate a multimodal world, building a holistic understanding from all our
senses. We introduce MERLOT Reserve, a model that represents videos jointly over time …

The goal of this work is to build flexible video-language models that can generalize to
various video-to-text tasks from few examples. Existing few-shot video-language learners …

Training an effective video-and-language model intuitively requires multiple frames as
model inputs. However, it is unclear whether using multiple frames is beneficial to …

We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image,
language, audio, and video. Guided by ImageBind, we construct a joint embedding space …

The extent to which text-only language models (LMs) learn to represent features of the non-
linguistic world is an open question. Prior work has shown that pretrained LMs can be taught …