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20162021
most citedOverview of the Ninth Dialog System Technology Challenge: DSTC9

37 citations · 41 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CL20212 cited

Zero-Shot Dialogue State Tracking via Cross-Task Transfer

Zhaojiang Lin, Bing Liu, Andrea Madotto +8

Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data. In…

cs.CL2021

Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking

Zhaojiang Lin, Bing Liu, Seungwhan Moon +7

Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper,…

cs.CL20202 cited

Continual Learning in Task-Oriented Dialogue Systems

Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou +6

Continual learning in task-oriented dialogue systems can allow us to add new domains and functionalities through time without incurring the high cost of a whole system retraining.…

cs.CL202037 cited

Overview of the Ninth Dialog System Technology Challenge: DSTC9

Chulaka Gunasekara, Seokhwan Kim, Luis Fernando D'Haro +36

This paper introduces the Ninth Dialog System Technology Challenge (DSTC-9). This edition of the DSTC focuses on applying end-to-end dialog technologies for four distinct tasks in…

cs.CL2020

Situated and Interactive Multimodal Conversations

Seungwhan Moon, Satwik Kottur, Paul A. Crook +9

Next generation virtual assistants are envisioned to handle multimodal inputs (e.g., vision, memories of previous interactions, in addition to the user's utterances), and perform m…