193 citations · 565 across the 21 of their papers we have counts for
21 papers
CodeTF: One-stop Transformer Library for State-of-the-art Code LLMs
Nghi D. Q. Bui, Hung Le, Yue Wang +3
Code intelligence plays a key role in transforming modern software engineering. Recently, deep learning-based models, especially Transformer-based large language models (LLMs), hav…
CodeT5+: Open Code Large Language Models for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Deepak Gotmare +3
Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations in terms of…
CinPatent: Datasets for Patent Classification
Minh-Tien Nguyen, Nhung Bui, Manh Tran-Tien +2
Patent classification is the task that assigns each input patent into several codes (classes). Due to its high demand, several datasets and methods have been introduced. However, t…
Improving Document Image Understanding with Reinforcement Finetuning
Bao-Sinh Nguyen, Dung Tien Le, Hieu M. Vu +3
Successful Artificial Intelligence systems often require numerous labeled data to extract information from document images. In this paper, we investigate the problem of improving t…
LAVIS: A Library for Language-Vision Intelligence
Dongxu Li, Junnan Li, Hung Le +3
We introduce LAVIS, an open-source deep learning library for LAnguage-VISion research and applications. LAVIS aims to serve as a one-stop comprehensive library that brings recent a…
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Hung Le, Yue Wang, Akhilesh Deepak Gotmare +2
Program synthesis or code generation aims to generate a program that satisfies a problem specification. Recent approaches using large-scale pretrained language models (LMs) have sh…
Multimodal Dialogue State Tracking
Hung Le, Nancy F. Chen, Steven C. H. Hoi
Designed for tracking user goals in dialogues, a dialogue state tracker is an essential component in a dialogue system. However, the research of dialogue state tracking has largely…
OmniXAI: A Library for Explainable AI
Wenzhuo Yang, Hung Le, Tanmay Laud +2
We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpret…
Make The Most of Prior Data: A Solution for Interactive Text Summarization with Preference Feedback
Duy-Hung Nguyen, Nguyen Viet Dung Nghiem, Bao-Sinh Nguyen +4
For summarization, human preference is critical to tame outputs of the summarizer in favor of human interests, as ground-truth summaries are scarce and ambiguous. Practical setting…
: Compositional Counterfactual Contrastive Learning for Video-grounded Dialogues
Hung Le, Nancy F. Chen, Steven C. H. Hoi
Video-grounded dialogue systems aim to integrate video understanding and dialogue understanding to generate responses that are relevant to both the dialogue and video context. Most…
VGNMN: Video-grounded Neural Module Network to Video-Grounded Language Tasks
Hung Le, Nancy F. Chen, Steven C. H. Hoi
Neural module networks (NMN) have achieved success in image-grounded tasks such as Visual Question Answering (VQA) on synthetic images. However, very limited work on NMN has been s…
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
Hung Le, Nancy F. Chen, Steven C. H. Hoi
Compared to traditional visual question answering, video-grounded dialogues require additional reasoning over dialogue context to answer questions in a multi-turn setting. Previous…
DVD: A Diagnostic Dataset for Multi-step Reasoning in Video Grounded Dialogue
Hung Le, Chinnadhurai Sankar, Seungwhan Moon +3
A video-grounded dialogue system is required to understand both dialogue, which contains semantic dependencies from turn to turn, and video, which contains visual cues of spatial a…
BiST: Bi-directional Spatio-Temporal Reasoning for Video-Grounded Dialogues
Hung Le, Doyen Sahoo, Nancy F. Chen +1
Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances whi…
Video-Grounded Dialogues with Pretrained Generation Language Models
Hung Le, Steven C. H. Hoi
Pre-trained language models have shown remarkable success in improving various downstream NLP tasks due to their ability to capture dependencies in textual data and generate natura…
UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues
Hung Le, Doyen Sahoo, Chenghao Liu +2
Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons. First, tracking dialogue states of multiple do…
Multimodal Transformer with Pointer Network for the DSTC8 AVSD Challenge
Hung Le, Nancy F. Chen
Audio-Visual Scene-Aware Dialog (AVSD) is an extension from Video Question Answering (QA) whereby the dialogue agent is required to generate natural language responses to address u…
Non-Autoregressive Dialog State Tracking
Hung Le, Richard Socher, Steven C. H. Hoi
Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot…
FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
Doyen Sahoo, Wang Hao, Shu Ke +5
An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular…
Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems
Hung Le, Doyen Sahoo, Nancy F. Chen +1
Developing Video-Grounded Dialogue Systems (VGDS), where a dialogue is conducted based on visual and audio aspects of a given video, is significantly more challenging than traditio…
URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection
Hung Le, Quang Pham, Doyen Sahoo +1
Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of…