3 papers
cs.AI2026
Narrow Fine-Tuning Erodes Safety Alignment in Vision-Language Agents
Idhant Gulati, Shivam Raval
Lifelong multimodal agents must continuously adapt to new tasks through post-training, but this creates a fundamental tension between acquiring capabilities and preserving safety a…
cs.LG2026
MoE Lens -- An Expert Is All You Need
Marmik Chaudhari, Idhant Gulati, Nishkal Hundia +2
Mixture of Experts (MoE) models enable parameter-efficient scaling through sparse expert activations, yet optimizing their inference and memory costs remains challenging due to lim…
cs.LG2026
Sparse Crosscoders for diffing MoEs and Dense models
Marmik Chaudhari, Nishkal Hundia, Idhant Gulati
Mixture of Experts (MoE) achieve parameter-efficient scaling through sparse expert routing, yet their internal representations remain poorly understood compared to dense models. We…