Large Language models (LLMs) have shown remarkable success in assisting ...
Recent years have seen an increasing trend in the volume of personal med...
People capture photos and videos to relive and share memories of persona...
We present IMU2CLIP, a novel pre-training approach to align Inertial
Mea...
Searching vast troves of videos with textual descriptions is a core
mult...
Existing studies in dialogue system research mostly treat task-oriented
...
Zero-shot transfer learning for dialogue state tracking (DST) enables us...
Zero-shot cross-domain dialogue state tracking (DST) enables us to handl...
We present a new corpus for the Situated and Interactive Multimodal
Conv...
A video-grounded dialogue system is required to understand both dialogue...
Continual learning in task-oriented dialogue systems can allow us to add...
This paper introduces the Ninth Dialog System Technology Challenge (DSTC...
Existing conversational systems are mostly agent-centric, which assumes ...
The existing dialogue corpora and models are typically designed under tw...
Next generation virtual assistants are envisioned to handle multimodal i...
We study a conversational recommendation model which dynamically manages...
Open-ended human learning and information-seeking are increasingly media...
Federated Learning allows for population level models to be trained with...
Collaborative personalization, such as through learned user representati...
We introduce a new task called Multimodal Named Entity Recognition (MNER...
We propose a transfer deep learning (TDL) framework that can transfer th...