12 papers
No Unique Minimizer, No Problem: On the Consistency of Robust Neural Classifiers
Subhabrata Majumdar, Anand Deo, Partha Pratim Saha +1
Neural network classifiers trained by cross-entropy minimization are highly sensitive to label noise and adversarial contamination. While robust alternatives offer bounded influenc…
Distribution-Specific Curvature Control with Finite-Sample Guarantees for Open-Weight Safety
Domenic Rosati, Ali Dadsetan, Hong Huang +5
A short fine-tuning run can undo the safety guards of an open-weight model---retraining a refusal-trained assistant to aid weapons development or produce hate speech. Preventing su…
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,…
PsychoPass: Geometric Profiling of Multi-Turn Adversarial LLM Conversations
Muberra Ozmen, Subhabrata Majumdar
Multi-turn jailbreak attacks on large language models (LLMs) reveal a mismatch in current guardrails: they operate on individual turns, while attacks unfold as trajectories across…
Next-Billion AI Index: The compass for AI utility and adoption in the global majority
Ambrish Rawat, Jessica He, Subhabrata Majumdar +6
Generative AI assessments remain dominated by frontier capability benchmarks that often fail to capture whether systems can be sustainably deployed, adapted, and trusted in locally…