924 citations · 1.5k across the 16 of their papers we have counts for
6 papers · 1 filter
Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5
Nghi D. Q. Bui, Yue Wang, Steven Hoi
Automated software debugging is a crucial task for improving the productivity of software developers. Many neural-based techniques have been proven effective for debugging-related…
Learning Label Modular Prompts for Text Classification in the Wild
Hailin Chen, Amrita Saha, Shafiq Joty +1
Machine learning models usually assume i.i.d data during training and testing, but data and tasks in real world often change over time. To emulate the transient nature of real worl…
From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models
Jiaxian Guo, Junnan Li, Dongxu Li +4
Large language models (LLMs) have demonstrated excellent zero-shot generalization to new language tasks. However, effective utilization of LLMs for zero-shot visual question-answer…
BotSIM: An End-to-End Bot Simulation Toolkit for Commercial Task-Oriented Dialog Systems
Guangsen Wang, Shafiq Joty, Junnan Li +1
We introduce BotSIM, a modular, open-source Bot SIMulation environment with dialog generation, user simulation and conversation analytics capabilities. BotSIM aims to serve as a on…
BotSIM: An End-to-End Bot Simulation Framework for Commercial Task-Oriented Dialog Systems
Guangsen Wang, Samson Tan, Shafiq Joty +3
We present BotSIM, a data-efficient end-to-end Bot SIMulation toolkit for commercial text-based task-oriented dialog (TOD) systems. BotSIM consists of three major components: 1) a…
Masked Unsupervised Self-training for Label-free Image Classification
Junnan Li, Silvio Savarese, Steven C. H. Hoi
State-of-the-art computer vision models are mostly trained with supervised learning using human-labeled images, which limits their scalability due to the expensive annotation cost.…