B. Lall

On the Robustness of Temporal Vision-Language Models for Surgical Endoscopy Videos

Endo-C6, a compact corruption benchmark of six endoscopy-realistic perturbations evaluated at a fixed high severity, is introduced and RobustEndoCLIP, obtained by few-shot parameter-efficient tuning with VeRA, outperforming existing TVLM baselines are presented.

HALO: Hybrid Adaptive Load Offloading of Grant-Based Traffic to Grant-Free Bandwidth for Spectrum Efficiency in Next Generation Networks

Efficient spectrum utilization is critical for next-generation cellular networks such as 5G-Advanced and 6G, which must support diverse services with heterogeneous quality-of-service (QoS) requirements. Grant-free (GF) communication in 5G new radio enables low-latency unscheduled transmissions but often suffers from un...

DeepQ-Charge: A Decentralized Model-Free Framework for Real-Time Mobile EV Charger Dispatch Using Deep Reinforcement Learning

Can Experts Adapt Without Training? On Test-Time Modality Generalization in MVLMs

MoBE is proposed: a fully optimization-free framework that performs dynamic expert selection and adaptation at test time that combines entropy-guided dynamic routing in MoE settings with expert-wise Bayesian adaptation, enabling experts to update their confidence and adapt online without gradient updates.

Performance Analysis of FD C-NOMA With Intelligent TS and Battery Management in Non-Linear Energy Harvesting Networks

An intelligent dynamic battery energy (DBE) management scheme that calculates the precise energy deficit per symbol required to exactly achieve target transmit power per symbol interval, ensuring stable QoS while minimizing the long-term ergodic battery energy consumption per symbol compared to fixed battery energy (FB...