Other authors include: Can Qin, Stefano Ermon, Yun Fu GlueGen was accepted by ICCV. In the rapidly advancing field of text-to-image synthesis, the remarkable progress in generating lifelike images from textual prompts has…
In the kind of production environment our customers operate in, models are just the start.
Equal contribution between Erik Nijkamp and Hiroaki Hayashi. PaperCodeTweet Abstract The family of Salesforce CodeGen models is growing with CodeGen2.5 – a small, but mighty model! While there has been a recent trend…
TLDR We trained a series of 7B LLMs named XGen-7B with standard dense attention on up to 8K sequence length for up to 1.5T tokens. We also fine tune the models on public-domain…
AUTHORS: Huan Wang, Aadyot Bhatnagar, Doyen Sahoo, Wenzhuo Yang, Steven Hoi, Caiming Xiong, Donald Rose TL;DR: Time series data is a critical source of insights for many applications, including IT Operations, Quality Management,…
Discover CTRLsum, a novel framework for controllable text summarization that enables users to control multiple aspects of generated summaries by interacting with the summarization system through textual input in the form of a set of keywords or descriptive prompts.
Deep reinforcement learning (deep RL) is a popular and successful family of methods for teaching computers tasks ranging from playing Go and Atari games to controlling industrial robots.
Automatically generating captions for images has emerged as a prominent interdisciplinary research problem in both academia and industry.
Neural network architectures with memory and attention mechanisms exhibit certain reasoning capabilities required for question answering.
