4 papers
DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
Siqi Guo, Ming Lin, Tianbao Yang
Developing efficient CUDA kernels is a fundamental yet challenging task in the generative AI industry. Recent research leverages Large Language Models (LLMs) to automatically conve…
IL3D: A Large-Scale Indoor Layout Dataset for LLM-Driven 3D Scene Generation
Wenxu Zhou, Kaixuan Nie, Hang Du +5
In this study, we present IL3D, a large-scale dataset meticulously designed for large language model (LLM)-driven 3D scene generation, addressing the pressing demand for diverse, h…
CityGPT: Empowering Urban Spatial Cognition of Large Language Models
Jie Feng, Tianhui Liu, Yuwei Du +3
Large language models(LLMs), with their powerful language generation and reasoning capabilities, have already achieved notable success in many domains, e.g., math and code generati…
CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
Jie Feng, Jun Zhang, Tianhui Liu +6
As large language models (LLMs) continue to advance and gain widespread use, establishing systematic and reliable evaluation methodologies for LLMs and vision-language models (VLMs…