Papers by Jonathan Tong
MultiCAT: Multimodal Communication Annotations for Teams (2025.findings-naacl)
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Adarsh Pyarelal, John M Culnan, Ayesha Qamar, Meghavarshini Krishnaswamy, Yuwei Wang, Cheonkam Jeong, Chen Chen, Md Messal Monem Miah, Shahriar Hormozi, Jonathan Tong, Ruihong Huang
| Challenge: | Recent flagship models from OpenAI and Google are only capable of 1-on-1 interactions with humans, limiting the potential for integration into human-machine teams of the future. |
| Approach: | They propose a dataset that allows team members to make multiple types of predictions on the same dataset. |
| Outcome: | The proposed dataset builds upon data from teams working collaboratively to save victims in a simulated search and rescue mission. |
BotEval: Facilitating Interactive Human Evaluation (2024.acl-demos)
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| Challenge: | Using language models to perform complex interactive tasks is becoming more common with the rapid progress in natural language processing (NLP) models. |
| Approach: | They develop an evaluation toolkit that enables human-bot interactions as part of the evaluation process. |
| Outcome: | The evaluation toolkit enables human-bot interactions as part of the evaluation process, rather than making judgements for a static input. |
Evaluating Gender Bias of LLMs in Making Morality Judgements (2024.findings-emnlp)
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| Challenge: | Large Language Models (LLMs) have shown remarkable capabilities in a multitude of NLP tasks, but are still not immune to limitations such as gender bias. |
| Approach: | They propose to use a dataset to examine whether LLMs possess gender bias when asked to give moral opinions. |
| Outcome: | The proposed models show that they are biased when asked to give moral opinions. |
LegalCore: A Dataset for Event Coreference Resolution in Legal Documents (2025.findings-acl)
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Kangda Wei, Xi Shi, Jonathan Tong, null Sai Ramana Reddy, Anandhavelu Natarajan, Rajiv Jain, Aparna Garimella, Ruihong Huang
| Challenge: | Existing research on event coreference resolution is limited to news articles . existing datasets for news articles are limited to events and coreferences . |
| Approach: | They present a dataset for the legal domain LegalCore which has been annotated with event and event coreference information. |
| Outcome: | The legal contract documents annotated in this dataset are several times longer than news articles, with an average length of around 25k tokens per document. |
EMONA: Event-level Moral Opinions in News Articles (2024.naacl-long)
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Yuanyuan Lei, Md Messal Monem Miah, Ayesha Qamar, Sai Ramana Reddy, Jonathan Tong, Haotian Xu, Ruihong Huang
| Challenge: | Recent work on news articles has focused on social media short texts, but little has explored moral sentiment within news articles. |
| Approach: | They propose to extract event-level moral opinions from news articles using a new dataset . they use annotated event-based moral opinions to analyze news articles . |
| Outcome: | The proposed dataset consists of 400 news articles containing over 10k sentences and 45k events, among which 9,613 events received moral foundation labels. |
Do LLMs Understand Dialogues? A Case Study on Dialogue Acts (2025.acl-long)
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| Challenge: | Large Language Models (LLMs) have shown remarkable performance on many unseen tasks in a zero-shot setting. |
| Approach: | They propose to identify three key pre-tasks essential for accurate DA prediction: Turn Management, Communicative Function Identification, and Dialogue Structure Prediction. |
| Outcome: | The proposed model fails to outperform basic rule-based tasks on three key pre-tasks, and the results suggest that the model is flawed. |