1 citations · 1 across the 8 of their papers we have counts for
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GIST: Generator-state-Informed Supervision for Tabular Foundation Models
Zhangyang Peng, Jingze Shi, Tongyi Zhang +1
Tabular foundation models (TFMs) based on prior-data fitted networks typically use sampled hard query labels, leaving avoidable sampling variability in pretraining. A key observati…
Towards Automated Kernel Generation in the Era of LLMs
Yang Yu, Peiyu Zang, Chi Hsu Tsai +11
The performance of modern AI systems is fundamentally constrained by the quality of their underlying GPU kernels, which translate high-level algorithmic semantics into low-level ha…
Wonderful Matrices: Combining for a More Efficient and Effective Foundation Model Architecture
Jingze Shi, Bingheng Wu
In order to make the foundation model more efficient and effective, our idea is combining sequence transformation and state transformation. First, we prove the availability of rota…
Wonderful Matrices: More Efficient and Effective Architecture for Language Modeling Tasks
Jingze Shi, Bingheng Wu, Lu He +1
We prove the availability of inner product form position encoding in the state space dual algorithm and study the effectiveness of different position embeddings in the hybrid quadr…