…Yanzuo Lu , , Abstract RAVEN enables real-time video generation through causal autoregressive extrapolation with improved training alignment, while CM-GRPO enhances performance via reinforcement learning applied to consistency model sampling. AI-generated…
…On several benchmarks, FEST outperforms baselines with magnitudes less SFT data, even matching their performance with full dataset. View arXiv page View PDF GitHub 0 Add to collection Community This is a…
…However, they suffer from inherent optimization bottlenecks due to the coupling of reasoning and scoring within a single autoregressive inference chain. To harness the generalization benefits of CoT reasoning while mitigating the…
…Yanggan Gu , Shuo Cai , , Wenjun Wang , Yuanyi Wang , , , , , Abstract Feature drift analysis in model merging leads to FeatCal, a calibration method that reduces performance gaps through layer-wise weight updates without gradient…
…Evaluation of six state-of-the-art methods shows that strong global volumetric overlap does not necessarily translate into reliable performance at clinically critical tumor-vessel interfaces. In particular, methods optimized for…
…AI-generated summary Language models excel at diagnostic assessments on currated medical case-studies and vignettes, performing on par with, or better than, clinical professionals. However, existing studies focus on complex scenarios…
…AI-generated summary Test-time scaling (TTS) has become an effective approach for improving large language model performance by allocating additional computation during inference. However, existing TTS strategies are largely hand-crafted…
…Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery (2026) Measurement Reduction in Orbital-Optimized Variational Quantum Eigensolver via Orbital Compression (2026) Please give a thumbs up to…
…Yuanyi Wang , Yanggan Gu , , , , , , , Abstract Empirical scaling laws for language model merging reveal power-law relationships between model size, expert count, and cross-entropy performance, enabling predictive planning for optimal model composition…
…and modular, making it easy to experiment with new features or optimizations. If you’re interested in lightweight, high-performance LLM inference without the complexity, give it a star ⭐ and let me…