DeSkew-LSH based Code-to-Code Recommendation Engine. - Fran Silavong; Sean J. Moran; Antonios Georgiadis; Rohan Saphal; Robert Otter (CoRR, 2021)

CV4Code: Sourcecode Understanding via Visual Code Representations. - Ruibo Shi; Lili Tao; Rohan Saphal; Fran Silavong; Sean J. Moran (ACCV (2), 2022)

Senatus - A Fast and Accurate Code-to-Code Recommendation Engine. - Fran Silavong; Sean J. Moran; Antonios Georgiadis; Rohan Saphal; Robert Otter (MSR, 2022)

ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation. - Antonios Georgiadis; Varun Babbar; Fran Silavong; Sean J. Moran; Robert Otter (CoRR, 2022)

Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies. - Shaltiel Eloul; Fran Silavong; Sanket Kamthe; Antonios Georgiadis; Sean J. Moran (CoRR, 2022)

Topical: Learning Repository Embeddings from Source Code using Attention. - Agathe Lherondelle; Yash Satsangi; Fran Silavong; Shaltiel Eloul; Sean J. Moran (CoRR, 2022)

API-Spector: an API-to-API Specification Recommendation Engine. - Sae Young Moon; Fran Silavong; Sean J. Moran (CoRR, 2022)

A Baseline Generative Probabilistic Model for Weakly Supervised Learning. - Georgios Papadopoulos 007; Fran Silavong; Sean J. Moran (ECML/PKDD (6), 2023)

A New Baseline for GreenAI: Finding the Optimal Sub-Network via Layer and Channel Pruning. - Xiaoying Zhi; Varun Babbar; Pheobe Sun; Fran Silavong; Ruibo Shi; Sean J. Moran (CoRR, 2023)

A Benchmark Generative Probabilistic Model for Weak Supervised Learning. - Georgios Papadopoulos 007; Fran Silavong; Sean J. Moran (CoRR, 2023)

Topical: Automatic Repository Tagging using Attention on Hybrid Code Embeddings. - Agathe Lherondelle; Varun Babbar; Yash Satsangi; Fran Silavong; Shaltiel Eloul; Sean J. Moran (FinanSE@ICSE, 2024)

API-Miner: an API-to-API Specification Recommendation Engine. - Sae Young Moon; Gregor Kerr; Fran Silavong; Sean J. Moran (FinanSE@ICSE, 2024)

DriftWatch: A Tool that Automatically Detects Data Drift and Extracts Representative Examples Affected by Drift. - Myeongjun Jang; Antonios Georgiadis; Yiyun Zhao; Fran Silavong (NAACL (Industry Track), 2024)

Mixing Gradients in Neural Networks as a Strategy to Enhance Privacy in Federated Learning. - Shaltiel Eloul; Fran Silavong; Sanket Kamthe; Antonios Georgiadis; Sean J. Moran (WACV, 2024)

Automatic Labelling with Open-source LLMs using Dynamic Label Schema Integration. - Thomas Walshe; Sae Young Moon; Chunyang Xiao; Yawwani Gunawardana; Fran Silavong (CoRR, 2025)

A probabilistic model for API contract specification retrieval focusing on the openAPI standard. - Sae Young Moon; Gregor Kerr; Fran Silavong; Sean J. Moran (Data Min. Knowl. Discov., 2025)

Learning a consensus sub-network with polarization regularization and one pass training. - Xiaoying Zhi; Varun Babbar; Rundong Liu; Pheobe Sun; Fran Silavong; Ruibo Shi; Sean J. Moran (Data Min. Knowl. Discov., 2025)