1 citations · 1 across the 8 of their papers we have counts for
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EARL: Entropy-Aware RL Alignment of LLMs for Reliable RTL Code Generation
Jiahe Shi, Zhengqi Gao, Ching-Yun Ko +1
Recent advances in large language models (LLMs) have demonstrated significant potential in hardware design automation, particularly in using natural language to synthesize Register…
RDIT: Residual-based Diffusion Implicit Models for Probabilistic Time Series Forecasting
Chih-Yu Lai, Yu-Chien Ning, Duane S. Boning
Probabilistic Time Series Forecasting (PTSF) plays a critical role in domains requiring accurate and uncertainty-aware predictions for decision-making. However, existing methods of…
RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning
Kaiwen Zha, Zhengqi Gao, Maohao Shen +3
Reinforcement learning (RL) has recently emerged as a compelling approach for enhancing the reasoning capabilities of large language models (LLMs), where an LLM generator serves as…
Simple Feedfoward Neural Networks are Almost All You Need for Time Series Forecasting
Fan-Keng Sun, Yu-Cheng Wu, Duane S. Boning
Time series data are everywhere -- from finance to healthcare -- and each domain brings its own unique complexities and structures. While advanced models like Transformers and grap…