AI Coding with CodeRL: Toward Mastering Program Synthesis with Deep Reinforcement Learning

TL;DR: CodeRL is a new framework for program synthesis through holistic integration of pretrained language models and deep reinforcement learning. By utilizing unit test feedback as part of model training and inference, and integrating with an improved CodeT5 model, CodeRL achieves state-of-the-art results on competition-level programming tasks. The following

19 Jul 2022 •

OmniXAI: Making Explainable AI Easy for Any Data, Any Models, Any Tasks

Authors: Wenzhuo Yang, Steven Hoi, Donald Rose TL;DR:  OmniXAI (short for Omni eXplainable AI) is designed to address many of the pain points in explaining decisions made by AI models. This open-source library aims to provide data scientists, machine learning engineers, and researchers with a one-stop Explainable AI (XAI)

14 Jun 2022 • #OmniXAI

ALPRO: Understanding Video and Language by Aligning Visual Regions and Text Entities

Lead Author: Dongxu Li TL;DR: We propose ALPRO, a new video-and-language representation learning framework which achieves state-of-the-art performance on video-text retrieval and video question answering by learning fine-grained alignment between video regions and textual entities via entity prompts. For more background (a review of key concepts used in this

31 May 2022 • #ALPRO

CodeT5: The Code-aware Encoder-Decoder based Pre-trained Programming Language Models

TL; DR: Introducing CodeT5 --- the first code-aware, encoder-decoder-based pre-trained programming language model, which enables a wide range of code intelligence applications including code understanding and generation tasks. CodeT5 achieves state-of-the-art performance on 14 sub-tasks in the CodeXGLUE code intelligence benchmark. CodeT5 for code-related understanding and generation tasksGiven the goal

03 Sep 2021 • #code-intelligence