4 citations · 4 across the 3 of their papers we have counts for
4 papers
OTAP: Structure-Aware Optimal Transport for Evaluating Planning and Execution in Agent Trajectories
Babak Barazandeh, Subhabrata Majumdar, George Michailidis
Large language model agents solve tasks by generating trajectories that interleave planning, tool calls, and intermediate results. Current evaluation metrics reduce such a trajecto…
Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing
Babak Barazandeh, Subhabrata Majumdar, Vinay Prithyani +1
Large Language Models (LLMs) and high-dimensional perception networks increasingly rely on parameter-efficient fine-tuning (PEFT) to adapt to diverse operational contexts. However,…
Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain
Dmitrii M. Ostrovskii, Babak Barazandeh, Meisam Razaviyayn
We study the problem of finding approximate first-order stationary points in optimization problems of the form , where the sets are conv…
Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning
Babak Barazandeh, Subhabrata Majumdar, Om Rajyaguru +1
Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, offer compact and effective alternatives to full model fine-tuning by introducing low-rank updates to pre-trained weig…