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20192022
most citedMars: Modeling Context & State Representations with Contrastive Learning for End-to-End Task-Oriented Dialog

7 citations · 18 across the 7 of their papers we have counts for

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Showing 2022 · cs.CLShow all

5 papers · 2 filters

cs.CL2022★ 2 cited

MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Tracking

Haoning Zhang, Junwei Bao, Haipeng Sun +4

Dialogue state tracking (DST) aims to convert the dialogue history into dialogue states which consist of slot-value pairs. As condensed structural information memorizing all histor…

cs.CL2022★ 1 cited

CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking

Haoning Zhang, Junwei Bao, Haipeng Sun +3

Few-shot dialogue state tracking (DST) is a realistic problem that trains the DST model with limited labeled data. Existing few-shot methods mainly transfer knowledge learned from…

cs.CL2022★ 7 cited

Mars: Modeling Context & State Representations with Contrastive Learning for End-to-End Task-Oriented Dialog

Haipeng Sun, Junwei Bao, Youzheng Wu +1

Traditional end-to-end task-oriented dialog systems first convert dialog context into belief state and action state before generating the system response. The system response perfo…

cs.CL2022★ 2 cited

BORT: Back and Denoising Reconstruction for End-to-End Task-Oriented Dialog

Haipeng Sun, Junwei Bao, Youzheng Wu +1

A typical end-to-end task-oriented dialog system transfers context into dialog state, and upon which generates a response, which usually faces the problem of error propagation from…

cs.CL2022

OPERA:Operation-Pivoted Discrete Reasoning over Text

Yongwei Zhou, Junwei Bao, Chaoqun Duan +7

Machine reading comprehension (MRC) that requires discrete reasoning involving symbolic operations, e.g., addition, sorting, and counting, is a challenging task. According to this…