1 citations · 2 across the 5 of their papers we have counts for
8 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…
: Improving Factuality of Information-Seeking Dialogue via Behavioural Fine-Tuning
Evgeniia Razumovskaia, Ivan Vulić, Pavle Marković +4
Factuality is a crucial requirement in information seeking dialogue: the system should respond to the user's queries so that the responses are meaningful and aligned with the knowl…
SQATIN: Supervised Instruction Tuning Meets Question Answering for Improved Dialogue NLU
Evgeniia Razumovskaia, Goran Glavaš, Anna Korhonen +1
Task-oriented dialogue (ToD) systems help users execute well-defined tasks across a variety of domains (e.g., or ), with their Nat…
Quantifying the Dialect Gap and its Correlates Across Languages
Anjali Kantharuban, Ivan Vulić, Anna Korhonen
Historically, researchers and consumers have noticed a decrease in quality when applying NLP tools to minority variants of languages (i.e. Puerto Rican Spanish or Swiss German), bu…
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…
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
Han Zhou, Xingchen Wan, Ivan Vulić +1
Prompt-based learning has been an effective paradigm for large pretrained language models (LLM), enabling few-shot or even zero-shot learning. Black-box prompt search has received…