Group-Adaptive Threshold Optimization for Robust AI-Generated Text Detection
ICML (In submission) | February 2025
Minseok Jung, Cynthia Fuertes Panizo, Liam Dugan, Pin-Yu Chen, Paul Pu Liang
Publications
GenAI Content Detection Task 3: Cross-Domain Machine-Generated Text Detection Challenge
GenAI Content Detection Workshop @ COLING | January 2025
Liam Dugan, Andrew Zhu, Firoj Alam, Preslav Nakov, Marianna Apidianaki, Chris Callison-Burch
MiRAGeNews: Multimodal Realistic AI-Generated News Detection
Findings of EMNLP | October 2024
Runsheng Huang, Liam Dugan, Yue Yang, Chris Callison-Burch
ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems
EMNLP (System Demonstrations) | August 2024
Andrew Zhu, Liam Dugan, Chris Callison-Burch
RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors
ACL (Long Papers) | May 2024
Liam Dugan, Alyssa Hwang, Filip Trhlik, Josh Magnus Ludan, Andrew Zhu, Hainiu Xu, Daphne Ippolito, Chris Callison-Burch
FanOutQA: Multi-Hop, Multi-Document Question Answering for Large Language Models
ACL (Short Papers) | February 2024
Andrew Zhu, Alyssa Hwang, Liam Dugan, and Chris Callison-Burch
Interpretable-by-Design Text Classification with Iteratively Generated Concept Bottleneck
ArXiv | October 2023
Josh Magnus Ludan, Qing Lyu, Yue Yang, Liam Dugan, Mark Yatskar, and Chris Callison-Burch
Kani: A Lightweight and Highly Hackable Framework for Building Language Model Applications
NLP-OSS Workshop @ EMNLP | September 2023
Andrew Zhu*, Liam Dugan*, Alyssa Hwang, and Chris Callison-Burch
Enhancing Human Summaries for Question-Answer Generation in Education
BEA Workshop @ ACL | June 2023
Hannah Gonzalez, Liam Dugan, Eleni Miltsakaki, Zhiqi Cui, Jiaxuan Ren, Bryan Li, Shriyash Upadhyay, Etan Ginsberg, and Chris Callison-Burch
Learning When to Speak: Latency and Quality Trade-offs for Simultaneous Speech-to-Speech Translation with Offline Models
Interspeech | June 2023
Liam Dugan, Anshul Wadhawan, Kyle Spence, Chris Callison-Burch, Morgan McGuire, and Victor Zordan
Exploring the Curious Case of Code Prompts
NLRSE Workshop @ ACL | April 2023
Li Zhang*, Liam Dugan*, Hainiu Xu*, and Chris Callison-Burch
Real or Fake Text? Investigating Human Ability to Detect Boundaries Between Human-Written and Machine-Generated Text
AAAI (Long Papers) | February 2023
Liam Dugan*, Daphne Ippolito*, Arun Kirubarajan, Sherry Shi, and Chris Callison-Burch
The Case for a Single Model that can both Generate Continuations and Fill-in-the-Blank
Findings of NAACL (Short Papers) | June 2022
Daphne Ippolito, Liam Dugan, Emily Reif, Ann Yuan, Andy Coenen, and Chris Callison-Burch
Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models
Transactions on Machine Learning Research (TMLR) | June 2022
Aarohi Srivastava, Abhinav Rastogi, and (440 others)
A Feasibility Study of Answer-Agnostic Question Generation for Education
Findings of ACL (Short Papers) | March 2022
Liam Dugan, Eleni Miltsakaki, Shriyash Upadhyay, Etan Ginsberg, Hannah Gonzalez, DaHyeon Choi, Chuning Yuan, and Chris Callison-Burch
Learning Formality from Japanese-English Parallel Corpora
Masters Theses | December 2020
Liam Dugan
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
EMNLP (System Demonstrations) | October 2020
Liam Dugan, Daphne Ippolito*, Arun Kirubarajan*, and Chris Callison-Burch
Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices
ICMV | October 2018
Zhengyi Luo, Austin Small, Liam Dugan, and Stephen Lane