activity
20182021
most citedNon-Autoregressive Dialog State Tracking

25 citations · 30 across the 3 of their papers we have counts for

collaborators

9 papers

cs.AI2021

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…

cs.CV2020

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…

cs.CL20202 cited

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…

cs.CL2020

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…

cs.CL20203 cited

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…

cs.CL202025 cited

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…