Volume 1 Issue 3

Dev Hemnani1, Arham Sethi2
Abstract-Large language models (LLMs) are increasingly being deployed with extended context windows ranging from 100K to 200K tokens, enabling applications involving long-document analysis, multi-source reasoning, and prolonged conversational interaction. Despite these developments, the practical reliability of long-context processing remains insufficiently understood. This study introduces KS-Probe (Probing Recall Over Boundaries and Extents), a benchmark framework developed to systematically evaluate context fidelity... view more..
KS-Probe: A Multidimensional Benchmark for Evaluating Long-Context Fidelity in Frontier Language Models
Vaidik Tiwari1*, Mr. Jagdish Pampania2
Abstract-This paper presents EVA, an intelligent voice   controlled robotic assistant integrating speech recognition, ESP32-CAM vision, spatial memory and a multi-degree-of freedom robotic arm. The system combines perception, decision making and actuation through a modular architecture. Continuous listening, interrupt-driven control and asynchronous software enable responsive human–robot interaction. The robotic arm executes basic manipulation tasks while the vision module detects objects and supports contextual awareness.... view more..
EVA: An Intelligent Voice-Controlled Robotic Assistant Integrating ESP32-CAM-Based Vision and Spatial Memory
Deepa Tatware1, Priya Geete2
The emerging sixth-generation (6G), beyond-fifth generation (B5G) and fifth-generation (5G) wireless systems are rapidly developing, which has led to the need for antennas that are compact, have wide impedance bandwidth, and have adequate gain and reliable radiation. The planar antennas are desirable for their lightweight, low-profile, economical, and printed circuit manufacturing compatibility. This review reflects recent advances in planar UWB and mmWave antenna research, with a focus... view more..
Design and Development of Compact Ultra-Wideband Millimeter-Wave Planar Antennas for Next-Generation Wireless Communication Systems: A Comprehensive Review
JLISNT

At JLISNT, we believe innovation is the key to solving tomorrow’s challenges today. We provide a global platform for scholars, scientists, and industry experts to present original research, novel applications, and transformative ideas.

© 2025 Journal of Leading Innovations in Science and Technology. All rights reserved.