Online Harassment in Majority Contexts: Examining Harms and Remedies across Countries. - Sarita Schoenebeck; Amna Batool; Giang Do; Sylvia Darling; Gabriel Grill; Daricia Wilkinson; Mehtab Khan; Kentaro Toyama; Louise Ashwell (CHI, 2023)

HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts. - Giang Do; Khiem Le; Quang Pham; TrungTin Nguyen; Thanh-Nam Doan; Bint T. Nguyen; Chenghao Liu; Savitha Ramasamy; Xiaoli Li 001; Steven C. H. Hoi (CoRR, 2023)

CompeteSMoE - Effective Training of Sparse Mixture of Experts via Competition. - Quang Pham; Giang Do; Huy Nguyen; TrungTin Nguyen; Chenghao Liu; Mina Sartipi; Binh T. Nguyen 001; Savitha Ramasamy; Xiaoli Li 001; Steven C. H. Hoi; Nhat Ho (CoRR, 2024)

SimSMoE: Solving Representational Collapse via Similarity Measure. - Giang Do; Hung Le 002; Truyen Tran 001 (CoRR, 2024)

On the effectiveness of discrete representations in sparse mixture of experts. - Giang Do; Kha Pham; Hung Le 002; Truyen Tran 001 (CoRR, 2024)

SimSMoE: Toward Efficient Training Mixture of Experts via Solving Representational Collapse. - Giang Do; Hung Le 002; Truyen Tran 001 (NAACL (Findings), 2025)

Sparse Mixture of Experts as Unified Competitive Learning. - Giang Do; Hung Le 002; Truyen Tran 001 (CoRR, 2025)

S2MoE: Robust Sparse Mixture of Experts via Stochastic Learning. - Giang Do; Hung Le 002; Truyen Tran 001 (CoRR, 2025)