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Are Large Language Models All You Need for Task-Oriented Dialogue?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10476275" target="_blank" >RIV/00216208:11320/23:10476275 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Are Large Language Models All You Need for Task-Oriented Dialogue?

  • Original language description

    Instruction-finetuned large language models (LLMs) gained a huge popularity recently, thanks to their ability to interact with users through conversation. In this work, we aim to evaluate their ability to complete multi-turn tasks and interact with external databases in the context of established task-oriented dialogue benchmarks. We show that in explicit belief state tracking, LLMs underperform compared to specialized task-specific models. Nevertheless, they show some ability to guide the dialogue to a successful ending through their generated responses if they are provided with correct slot values. Furthermore, this ability improves with few-shot in-domain examples.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LM2023062" target="_blank" >LM2023062: Digital Research Infrastructure for Language Technologies, Arts and Humanities</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

  • ISBN

    979-8-89176-028-8

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    216-228

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Stroudsubrgh, PA, USA

  • Event location

    Prague, Czechia

  • Event date

    Sep 13, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article