Arun Kirubarajan


pdf bib
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
Liam Dugan | Daphne Ippolito | Arun Kirubarajan | Chris Callison-Burch
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

In recent years, large neural networks for natural language generation (NLG) have made leaps and bounds in their ability to generate fluent text. However, the tasks of evaluating quality differences between NLG systems and understanding how humans perceive the generated text remain both crucial and difficult. In this system demonstration, we present Real or Fake Text (RoFT), a website that tackles both of these challenges by inviting users to try their hand at detecting machine-generated text in a variety of domains. We introduce a novel evaluation task based on detecting the boundary at which a text passage that starts off human-written transitions to being machine-generated. We show preliminary results of using RoFT to evaluate detection of machine-generated news articles.


pdf bib
ChatEval: A Tool for Chatbot Evaluation
João Sedoc | Daphne Ippolito | Arun Kirubarajan | Jai Thirani | Lyle Ungar | Chris Callison-Burch
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)

Open-domain dialog systems (i.e. chatbots) are difficult to evaluate. The current best practice for analyzing and comparing these dialog systems is the use of human judgments. However, the lack of standardization in evaluation procedures, and the fact that model parameters and code are rarely published hinder systematic human evaluation experiments. We introduce a unified framework for human evaluation of chatbots that augments existing tools and provides a web-based hub for researchers to share and compare their dialog systems. Researchers can submit their trained models to the ChatEval web interface and obtain comparisons with baselines and prior work. The evaluation code is open-source to ensure standardization and transparency. In addition, we introduce open-source baseline models and evaluation datasets. ChatEval can be found at


pdf bib
ChatEval: A Tool for the Systematic Evaluation of Chatbots
João Sedoc | Daphne Ippolito | Arun Kirubarajan | Jai Thirani | Lyle Ungar | Chris Callison-Burch
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)