18 citations · 18 across the 9 of their papers we have counts for
11 papers
FRESHLATENT: Channel-Aware Latent Adaptation for Resource-Constrained Embodied VLM Perception
Rajat Bhattacharjya, Minwoo Kim, Arnab Sarkar +5
Mission-critical UAVs increasingly rely on split vision-language model (VLM) perception under tight onboard-resource and wireless-communication constraints. However, corruption of…
FloodReasonBench: Benchmarking VLM Reasoning Segmentation for Embodied Flood Response at the Edge
Rajat Bhattacharjya, Yoomee Jung, Minwoo Kim +4
Reasoning segmentation enables vision-language models (VLMs) to translate mission-relevant language requests into pixel-level visual grounding, offering a natural perception interf…
MemoGuard: An Adaptive Runtime for Guarding Against Memory Traps in Communication-Limited Robot Navigation
Rajat Bhattacharjya, Hyeonjong Ju, Sing-Yao Wu +2
Communication-limited robots in mission-critical scenarios such as disaster inspection and search-and-rescue must make reliable onboard decisions without access to remote operators…
T-SAR: A Full-Stack Co-design for CPU-Only Ternary LLM Inference via In-Place SIMD ALU Reorganization
Hyunwoo Oh, KyungIn Nam, Rajat Bhattacharjya +7
Recent advances in LLMs have outpaced the computational and memory capacities of edge platforms that primarily employ CPUs, thereby challenging efficient and scalable deployment. W…
AVERY: Intent-Driven Adaptive VLM Split Computing via Embodied Self-Awareness for Efficient Disaster Response Systems
Rajat Bhattacharjya, Sing-Yao Wu, Hyunwoo Oh +5
Unmanned Aerial Vehicles (UAVs) in disaster response require complex, queryable intelligence that onboard CNNs cannot provide. While Vision-Language Models (VLMs) offer this semant…
HYPERDOA: Robust and Efficient DoA Estimation using Hyperdimensional Computing
Rajat Bhattacharjya, Woohyeok Park, Arnab Sarkar +3
Direction of Arrival (DoA) estimation techniques face a critical trade-off, as classical methods often lack accuracy in challenging, low signal-to-noise ratio (SNR) conditions, whi…
ACCESS-AV: Adaptive Communication-Computation Codesign for Sustainable Autonomous Vehicle Localization in Smart Factories
Rajat Bhattacharjya, Arnab Sarkar, Ish Kool +2
Autonomous Delivery Vehicles (ADVs) are increasingly used for transporting goods in 5G network-enabled smart factories, with the compute-intensive localization module presenting a…
MUSIC-lite: Efficient MUSIC using Approximate Computing: An OFDM Radar Case Study
Rajat Bhattacharjya, Arnab Sarkar, Biswadip Maity +1
Multiple Signal Classification (MUSIC) is a widely used Direction of Arrival (DoA)/Angle of Arrival (AoA) estimation algorithm applied to various application domains such as autono…
Ellora: Exploring Low-Power OFDM-based Radar Processors using Approximate Computing
Rajat Bhattacharjya, Alish Kanani, A Anil Kumar +3
In recent times, orthogonal frequency-division multiplexing (OFDM)-based radar has gained wide acceptance given its applicability in joint radar-communication systems. However, rea…
Locate: Low-Power Viterbi Decoder Exploration using Approximate Adders
Rajat Bhattacharjya, Biswadip Maity, Nikil Dutt
Viterbi decoders are widely used in communication systems, natural language processing (NLP), and other domains. While Viterbi decoders are compute-intensive and power-hungry, we c…
An Approximate Carry Estimating Simultaneous Adder with Rectification
Rajat Bhattacharjya, Vishesh Mishra, Saurabh Singh +2
Approximate computing has in recent times found significant applications towards lowering power, area, and time requirements for arithmetic operations. Several works done in recent…