arXiv AI By Yiting Wang, Chenhui Deng, Chia-Tung Ho, Yanqing Zhang, Zhuo Feng, Cunxi Yu, Ang Li, Gang Qu, Brucek Khailany

AUTOGATE: Automated Clock Gating via Toggling-Aware LLM-based RTL Rewriting

Read the original on arXiv AI →

arXiv:2606. 17461v1 Announce Type: cross Abstract: Fine-grain clock gating (FGCG) is among the most effective techniques for reducing dynamic power, yet current FGCG optimization flows remain largely manual.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning
Jun 5

GenAutoML: An Agentic Framework for Dynamic Architecture Generation and Optimization in Time-Series Analysis

arXiv:2606. 05860v1 Announce Type: new Abstract: Designing neural architectures for time-series forecasting and anomaly detection remains a resource-intensive task that often requires substantial domain expertise.

By Oleeviya Babu Poikarayil, C\'edric Schockaert, Abdulrahman Nahhas, Christian Daase, Mursal Dawodi, Jawid Ahmad Baktash
arXiv Machine Learning
2d ago

A Configuration-First Framework for Reproducible, Low-Code Localization

arXiv:2510. 25692v4 Announce Type: replace-cross Abstract: As machine learning (ML) increasingly underpins critical applications, credible, comparable, and repeatable experimental results become more important.

By Tim Strnad (Jo\v{z}ef Stefan Institute, Slovenia), Bla\v{z} Bertalani\v{c} (Jo\v{z}ef Stefan Institute, Slovenia), Carolina Fortuna (Jo\v{z}ef Stefan Institute, Slovenia)