On how to avoid exacerbating spurious correlations when models are overparameterized. - Tina Behnia; Ke Wang 035; Christos Thrampoulidis (ISIT, 2022)

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)

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)

Supervised Contrastive Representation Learning: Landscape Analysis with Unconstrained Features. - Tina Behnia; Christos Thrampoulidis (ISIT, 2024)

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

In-Context Occam's Razor: How Transformers Prefer Simpler Hypotheses on the Fly. - Puneesh Deora; Bhavya Vasudeva; Tina Behnia; Christos Thrampoulidis (CoRR, 2025)