3 papers
cs.NE2026
TurboEvolve: Towards Fast and Robust LLM-Driven Program Evolution
Yang Yang, Zining Zhong, Jindong Li +5
LLM-driven program evolution can discover high-quality programs, but its cost and run-to-run variance hinder reliable progress. We propose TurboEvolve, a multi-island evolutionary…
cs.CV2025
LUMA: Low-Dimension Unified Motion Alignment with Dual-Path Anchoring for Text-to-Motion Diffusion Model
Haozhe Jia, Wenshuo Chen, Yuqi Lin +8
While current diffusion-based models, typically built on U-Net architectures, have shown promising results on the text-to-motion generation task, they still suffer from semantic mi…
cs.AI2025
Hypothesis Generation via LLM-Automated Language Bias for ILP
Yang Yang, Jiemin Wu, Yutao Yue
Inductive Logic Programming (ILP) is a principled approach for generalizing regularities from data and constructing hypotheses as interpretable logic programs. However, a key limit…