3 citations · 5 across the 9 of their papers we have counts for
10 papers
Dial HEALTHDIAL for Advice: A Multilingual and Multi-Parallel Spoken Dialogue Dataset for Knowledge-Grounded Information Seeking
Songbo Hu, Yinhong Liu, Ej Zhou +5
Creating spoken dialogue datasets is methodologically challenging, and these challenges are amplified when the goal is to build multilingual, multi-parallel datasets at scale. This…
Artificial intelligence is creating a new global linguistic hierarchy
Giulia Occhini, Kumiko Tanaka-Ishii, Anna Barford +10
Artificial intelligence (AI) has the potential to transform healthcare, education, governance and socioeconomic equity, but its benefits remain concentrated in a small number of la…
Quantifying Language Disparities in Multilingual Large Language Models
Songbo Hu, Ivan Vulić, Anna Korhonen
Results reported in large-scale multilingual evaluations are often fragmented and confounded by factors such as target languages, differences in experimental setups, and model choi…
DIALIGHT: Lightweight Multilingual Development and Evaluation of Task-Oriented Dialogue Systems with Large Language Models
Songbo Hu, Xiaobin Wang, Zhangdie Yuan +2
We present DIALIGHT, a toolkit for developing and evaluating multilingual Task-Oriented Dialogue (ToD) systems which facilitates systematic evaluations and comparisons between ToD…
A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems
Songbo Hu, Han Zhou, Moy Yuan +5
Achieving robust language technologies that can perform well across the world's many languages is a central goal of multilingual NLP. In this work, we take stock of and empirically…
Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems
Songbo Hu, Han Zhou, Mete Hergul +5
Creating high-quality annotated data for task-oriented dialog (ToD) is known to be notoriously difficult, and the challenges are amplified when the goal is to create equitable, cul…
Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems
Songbo Hu, Ivan Vulić, Fangyu Liu +1
End-to-end (E2E) task-oriented dialogue (ToD) systems are prone to fall into the so-called "likelihood trap", resulting in generated responses which are dull, repetitive, and often…
Can Pretrained Language Models (Yet) Reason Deductively?
Zhangdie Yuan, Songbo Hu, Ivan Vulić +2
Acquiring factual knowledge with Pretrained Language Models (PLMs) has attracted increasing attention, showing promising performance in many knowledge-intensive tasks. Their good p…
What Does The User Want? Information Gain for Hierarchical Dialogue Policy Optimisation
Christian Geishauser, Songbo Hu, Hsien-chin Lin +5
The dialogue management component of a task-oriented dialogue system is typically optimised via reinforcement learning (RL). Optimisation via RL is highly susceptible to sample ine…
Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems
Hsien-chin Lin, Nurul Lubis, Songbo Hu +5
Dialogue policy optimisation via reinforcement learning requires a large number of training interactions, which makes learning with real users time consuming and expensive. Many se…