Songbo Hu

Orcid: 0000-0002-2132-6988

According to our database1, Songbo Hu authored at least 12 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Large Language Models and Thematic Analysis: Human-AI Synergy in Researching Hate Speech on Social Media.
CoRR, 2024

DIALIGHT: Lightweight Multilingual Development and Evaluation of Task-Oriented Dialogue Systems with Large Language Models.
CoRR, 2024

DIALIGHT: Lightweight Multilingual Development and Evaluation of Task-Oriented Dialogue Systems with Large Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, 2024

Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023
Multi 3 WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems.
Trans. Assoc. Comput. Linguistics, 2023

Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems.
CoRR, 2023

A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Can Pretrained Language Models (Yet) Reason Deductively?
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2021
Spatial Spillover Effect of Government Public Health Spending on Regional Economic Growth during the COVID-19 Pandemic: An Evidence from China.
Complex., 2021

Automation and optimization in crane lift planning: A critical review.
Adv. Eng. Informatics, 2021

Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems.
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2021

What does the User Want? Information Gain for Hierarchical Dialogue Policy Optimisation.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021


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