Finding by Counting: A Probabilistic Packet Count Model for Indoor Localization in BLE Environments. - Subham De; Shreyans Chowdhary; Aniket Shirke; Yat Long Lo; Robin Kravets; Hari Sundaram (WiNTECH, 2017)

The necessary roadblock to artificial general intelligence: corrigibility. - Yat Long Lo; Chung Yu Woo; Ka Lok Ng (AI Matters, 2019)

Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps. - Yat Long Lo; Sina Ghiassian (CoRR, 2019)

Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks. - Sina Ghiassian; Banafsheh Rafiee; Yat Long Lo; Adam White 001 (AAMAS, 2020)

Learning to Ground Decentralized Multi-Agent Communication with Contrastive Learning. - Yat Long Lo; Biswa Sengupta (CoRR, 2022)

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. - Yat Long Lo; Christian Schröder de Witt; Samuel Sokota; Jakob Nicolaus Foerster; Shimon Whiteson (ICLR, 2023)

Learning to Communicate using Contrastive Learning. - Yat Long Lo; Biswa Sengupta; Jakob N. Foerster; Michael Noukhovitch (CoRR, 2023)

Improving International Climate Policy via Mutually Conditional Binding Commitments. - Jobst Heitzig; Jörg Oechssler; Christoph Pröschel; Niranjana Ragavan; Yat Long Lo (CoRR, 2023)

Generative Image as Action Models. - Mohit Shridhar; Yat Long Lo; Stephen James (CoRL, 2024)

Learning Multi-Agent Communication with Contrastive Learning. - Yat Long Lo; Biswa Sengupta; Jakob Nicolaus Foerster; Michael Noukhovitch (ICLR, 2024)