Junjie Hu

compare-mt: A Tool for Holistic Comparison of Language Generation Systems

2019

Graham Neubig, Zi-Yi Dou, Junjie Hu, Paul Michel, Danish Pruthi, Xinyi Wang. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations). 2019.

TICO-19: the Translation Initiative for COvid-19

2020

Antonios Anastasopoulos, Alessandro Cattelan, Zi-Yi Dou, Marcello Federico, Christian Federmann, Dmitriy Genzel, Franscisco Guzmán, Junjie Hu, Macduff Hughes, Philipp Koehn, Rosie Lazar, Will Lewis, Graham Neubig, Mengmeng Niu, Alp Öktem, Eric Paquin, Grace Tang, Sylwia …

MultiRoboLearn: An open-source Framework for Multi-robot Deep Reinforcement Learning

2022 · arXiv (Cornell University)

It is well known that it is difficult to have a reliable and robust framework to link multi-agent deep reinforcement learning algorithms with practical multi-robot applications. To fill this gap, we propose and build an …

Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks

2024 · arXiv (Cornell University)

Creating human-like large language model (LLM) agents is crucial for faithful social simulation. Having LLMs role-play based on demographic information sometimes improves human likeness but often does not. This study assessed whether LLM alignment with …

Rapid Adaptation of Neural Machine Translation to New Languages

2018

This paper examines the problem of adapting neural machine translation systems to new, low-resourced languages (LRLs) as effectively and rapidly as possible. We propose methods based on starting with massively multilingual "seed models", which can …

XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

2020 · arXiv (Cornell University)

Much recent progress in applications of machine learning models to NLP has been driven by benchmarks that evaluate models across a wide variety of tasks. However, these broad-coverage benchmarks have been mostly limited to English, …