Imbalance Trouble: Revisiting Neural-Collapse Geometry. - Christos Thrampoulidis; Ganesh Ramachandra Kini; Vala Vakilian; Tina Behnia (NeurIPS, 2022)

On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data. - Tina Behnia; Ganesh Ramachandra Kini; Vala Vakilian; Christos Thrampoulidis (AISTATS, 2023)

Supervised-Contrastive Loss Learns Orthogonal Frames and Batching Matters. - Ganesh Ramachandra Kini; Vala Vakilian; Tina Behnia; Jaidev Gill; Christos Thrampoulidis (CoRR, 2023)

Engineering the Neural Collapse Geometry of Supervised-Contrastive Loss (Student Abstract). - Jaidev Gill; Vala Vakilian; Christos Thrampoulidis (AAAI, 2024)

Engineering the Neural Collapse Geometry of Supervised-Contrastive Loss. - Jaidev Gill; Vala Vakilian; Christos Thrampoulidis (ICASSP, 2024)

Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching. - Ganesh Ramachandra Kini; Vala Vakilian; Tina Behnia; Jaidev Gill; Christos Thrampoulidis (ICLR, 2024)

Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations. - Yize Zhao; Tina Behnia; Vala Vakilian; Christos Thrampoulidis (CoRR, 2024)

DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models. - Wenlong Deng; Yize Zhao; Vala Vakilian; Minghui Chen; Xiaoxiao Li; Christos Thrampoulidis (ICLR, 2025)