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Research#RTL🔬 ResearchAnalyzed: Jan 10, 2026 07:53

NotSoTiny: A Benchmark for RTL Code Generation

Published:Dec 23, 2025 22:53
1 min read
ArXiv

Analysis

This research introduces a novel benchmark, "NotSoTiny," specifically designed to evaluate the performance of AI models in generating Register Transfer Level (RTL) code. The use of a 'living' benchmark suggests ongoing updates and adaptation, making it a valuable tool for tracking progress in AI-driven hardware design.
Reference

“The paper is published on ArXiv.”

PermalinkArXiv
Research#Zero-shot🔬 ResearchAnalyzed: Jan 10, 2026 11:35

Fine-Grained Zero-Shot Learning: Attribute-Centric Approach

Published:Dec 13, 2025 07:12
1 min read
ArXiv

Analysis

This research explores zero-shot learning within the challenging domain of fine-grained classification, likely improving object recognition and categorization. The attribute-centric representations represent a novel approach, potentially leading to more robust and accurate model performance.
Reference

“This article is based on an ArXiv paper.”

PermalinkArXiv