5 papers
Chameleon: Dynamic Format Adapter for Efficient Diffusion
Arnab Sanyal, Sandeep Chinchali
Post-training quantization (PTQ) is the standard way to run modern diffusion models on memory-constrained accelerators, yet every existing diffusion PTQ scheme fixes the $\mathit{n…
Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision
Chengwei Zhou, Abu Masum, Xuming Chen +7
In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the logic chip integrated with a CMOS…
RT-NeuS: Towards Real-Time Neuro-Symbolic Video Understanding via Adaptive Temporal Verification
Shawn Liang, Sahil Shah, Chengwei Zhou +5
Long-form video question answering (LVQA) requires answering natural-language queries about videos spanning minutes to hours, demanding temporal reasoning across thousands of frame…
OASIS: Optimized Lightweight Autoencoder System for Distributed In-Sensor computing
Chengwei Zhou, Sreetama Sarkar, Yuming Li +5
In-sensor computing, which integrates computation directly within the sensor, has emerged as a promising paradigm for machine vision applications such as AR/VR and smart home syste…
EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices
Arnab Sanyal, Gourav Datta, Prithwish Mukherjee +2
Large Language Models (LLMs) achieve strong performance across tasks, but face storage and compute challenges on edge devices. We propose EntroLLM, a compression framework combinin…