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20182021
most citedTraining Neural Response Selection for Task-Oriented Dialogue Systems

55 citations · 65 across the 4 of their papers we have counts for

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9 papers · 1 filter

cs.CL20211 cited

ConvFiT: Conversational Fine-Tuning of Pretrained Language Models

Ivan Vulić, Pei-Hao Su, Sam Coope +5

Transformer-based language models (LMs) pretrained on large text collections are proven to store a wealth of semantic knowledge. However, 1) they are not effective as sentence enco…

cs.CL2021

Multilingual and Cross-Lingual Intent Detection from Spoken Data

Daniela Gerz, Pei-Hao Su, Razvan Kusztos +6

We present a systematic study on multilingual and cross-lingual intent detection from spoken data. The study leverages a new resource put forth in this work, termed MInDS-14, a fir…

cs.CL2020

Multidirectional Associative Optimization of Function-Specific Word Representations

Daniela Gerz, Ivan Vulić, Marek Rei +2

We present a neural framework for learning associations between interrelated groups of words such as the ones found in Subject-Verb-Object (SVO) structures. Our model induces a joi…

cs.CL2020

Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations

Sam Coope, Tyler Farghly, Daniela Gerz +2

We introduce Span-ConveRT, a light-weight model for dialog slot-filling which frames the task as a turn-based span extraction task. This formulation allows for a simple integration…

cs.CL2020

Efficient Intent Detection with Dual Sentence Encoders

Iñigo Casanueva, Tadas Temčinas, Daniela Gerz +2

Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i.e., in few-shot setups). Motivate…

cs.CL2019

PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking

Matthew Henderson, Ivan Vulić, Iñigo Casanueva +7

We present PolyResponse, a conversational search engine that supports task-oriented dialogue. It is a retrieval-based approach that bypasses the complex multi-component design of t…