7 citations · 8 across the 3 of their papers we have counts for
4 papers
EV-JEPA: Elastic V-JEPA for Any Device and Cross-Device Inference
Anxhelo Diko, Jieyu Lin, Stefano Ambrogio +5
Foundation models like V-JEPA are increasingly deployed across a heterogeneous edge-cloud continuum spanning smart glasses, phones, robots, and servers. Yet, they are typically tra…
AdaDINO: Context-Adaptive DINO-Distilled Vision Foundation Models for Efficient Open-Vocabulary Edge Inference
Yiwei Zhao, Yi Zheng, Huapeng Su +9
Always-on contextual AI runs language-aligned vision foundation models (VFMs) on edge devices, where the on-device model is the dominant continuous compute cost under strict latenc…
Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization
Prashanth Vijayaraghavan, Apoorva Nitsure, Charles Mackin +9
Large Language Models (LLMs) have become widely used across diverse NLP tasks and domains, demonstrating their adaptability and effectiveness. In the realm of Electronic Design Aut…
VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation
Prashanth Vijayaraghavan, Luyao Shi, Stefano Ambrogio +4
With the unprecedented advancements in Large Language Models (LLMs), their application domains have expanded to include code generation tasks across various programming languages.…