ArtBeat - Deep Convolutional Networks for Emotional Inference to Enhance Art with Music. - Liam Hebert; Elizabeth Eddy; Will Harrington; Lauryn Marchand; Jason d'Eon; Sageev Oore (ICMI Companion, 2021)

Robust Candidate Generation for Entity Linking on Short Social Media Texts. - Liam Hebert; Raheleh Makki; Shubhanshu Mishra; Hamidreza Saghir; Anusha Kamath; Yuval Merhav (W-NUT@COLING, 2022)

Predicting Hateful Discussions on Reddit using Graph Transformer Networks and Communal Context. - Liam Hebert; Lukasz Golab; Robin Cohen (WI/IAT, 2022)

FedFormer: Contextual Federation with Attention in Reinforcement Learning. - Liam Hebert; Lukasz Golab; Pascal Poupart; Robin Cohen (AAMAS, 2023)

Qualitative Analysis of a Graph Transformer Approach to Addressing Hate Speech: Adapting to Dynamically Changing Content. - Liam Hebert; Hong Yi Chen; Robin Cohen; Lukasz Golab (CoRR, 2023)

Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media. - Liam Hebert; Gaurav Sahu; Nanda Kishore Sreenivas; Lukasz Golab; Robin Cohen (CoRR, 2023)

Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Media. - Liam Hebert; Gaurav Sahu; Yuxuan Guo; Nanda Kishore Sreenivas; Lukasz Golab; Robin Cohen (AAAI, 2024)

SignSpeak: Open-Source Time Series Classification for ASL Translation. - Aditya Makkar; Divya Makkar; Aarav Patel; Liam Hebert (CoRR, 2024)

PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting. - Liam Hebert; Krishna Sayana; Ambarish Jash; Alexandros Karatzoglou; Sukhdeep S. Sodhi; Sumanth Doddapaneni; Yanli Cai; Dima Kuzmin (CoRR, 2024)

Beyond Retrieval: Generating Narratives in Conversational Recommender Systems. - Krishna Sayana; Raghavendra Vasudeva; Yuri Vasilevski; Kun Su; Liam Hebert; Hubert Pham; Ambarish Jash; Sukhdeep S. Sodhi (CoRR, 2024)

Graphormer-IR: Graph Transformers Predict Experimental IR Spectra Using Highly Specialized Attention. - Cailum M. K. Stienstra; Liam Hebert; Patrick Thomas; Alexander Haack; Jason Guo; W. Scott Hopkins (J. Chem. Inf. Model., 2024)

Mining User Study Data to Judge the Merit of a Model for Supporting User-Specific Explanations of AI Systems. - Owen Chambers; Robin Cohen; Maura R. Grossman; Liam Hebert; Elias Awad (Comput. Intell., 2024)

FLARE: Fusing Language Models and Collaborative Architectures for Recommender Enhancement. - Liam Hebert; Marialena Kyriakidi; Hubert Pham; Krishna Sayana; James Pine; Sukhdeep S. Sodhi; Ambarish Jash (WWW (Companion Volume), 2025)

Beyond Retrieval: Generating Narratives in Conversational Recommender Systems. - Krishna Sayana; Raghavendra Vasudeva; Yuri Vasilevski; Kun Su; Liam Hebert; James Pine; Hubert Pham; Ambarish Jash; Sukhdeep S. Sodhi (WWW (Companion Volume), 2025)

A Machine-Learned "Chemical Intuition" to Overcome Spectroscopic Data Scarcity. - Cailum M. K. Stienstra; Teun van Wieringen; Liam Hebert; Patrick Thomas; Kas J. Houthuijs; Giel Berden; Jos Oomens; Jonathan Martens; W. Scott Hopkins (J. Chem. Inf. Model., 2025)

REGEN: A Dataset and Benchmarks with Natural Language Critiques and Narratives. - Kun Su; Krishna Sayana; Hubert Pham; James Pine; Yuri Vasilevski; Raghavendra Vasudeva; Marialena Kyriakidi; Liam Hebert; Ambarish Jash; Anushya Subbiah; Sukhdeep S. Sodhi (CoRR, 2025)

Infomod: information-theoretic machine learning model diagnostics. - Armin Esmaelizadeh; Sunil Cotterill; Liam Hebert; Lukasz Golab; Kazem Taghva (Distributed Parallel Databases, 2025)