activity
20212026
most citedMulti3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems

3 citations · 4 across the 7 of their papers we have counts for

collaborators

5 papers

cs.CL2026

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…

cs.CY2026

Artificial intelligence is creating a new global linguistic hierarchy

Giulia Occhini, Kumiko Tanaka-Ishii, Anna Barford +9

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…

cs.CL2025

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…

cs.LG2021

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…

cs.CL2021

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…