97 citations · 103 across the 7 of their papers we have counts for
8 papers
ChipMEM: Verification-Grounded Memory for EDA Agents
Abdulrahman AlRabah, Joshua Mabry, Dilek Hakkani-Tür +4
Large language model (LLM)-based agents use Electronic Design Automation (EDA) tools to generate and revise register-transfer-level (RTL) designs under synthesis and verification f…
DUET: Agentic Design Understanding via Experimentation and Testing
Gus Henry Smith, Sandesh Adhikary, Vineet Thumuluri +5
AI agents powered by large language models (LLMs) are being used to solve increasingly complex software engineering challenges, but struggle with hardware design tasks. Register Tr…
Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning
Aaron Bell, Amit Aides, Amr Helmy +57
Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…
Aligning Audio Captions with Human Preferences
Kartik Hegde, Rehana Mahfuz, Yinyi Guo +1
Current audio captioning relies on supervised learning with paired audio-caption data, which is costly to curate and may not reflect human preferences in real-world scenarios. To a…
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
Kartik Hegde, Po-An Tsai, Sitao Huang +3
Modern day computing increasingly relies on specialization to satiate growing performance and efficiency requirements. A core challenge in designing such specialized hardware archi…
HTS: A Hardware Task Scheduler for Heterogeneous Systems
Kartik Hegde, Abhishek Srivastava, Rohit Agrawal
As the Moore's scaling era comes to an end, application specific hardware accelerators appear as an attractive way to improve the performance and power efficiency of our computing…
Morph: Flexible Acceleration for 3D CNN-based Video Understanding
Kartik Hegde, Rohit Agrawal, Yulun Yao +1
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the archite…
UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition
Kartik Hegde, Jiyong Yu, Rohit Agrawal +3
Convolutional Neural Networks (CNNs) have begun to permeate all corners of electronic society (from voice recognition to scene generation) due to their high accuracy and machine ef…