OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding? Paper • 2501.05510 • Published 18 days ago • 39
Gradient-Mask Tuning Elevates the Upper Limits of LLM Performance Paper • 2406.15330 • Published Jun 21, 2024
Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training Paper • 2411.14318 • Published Nov 21, 2024
EpiCoder: Encompassing Diversity and Complexity in Code Generation Paper • 2501.04694 • Published 19 days ago • 13
LLaVA-UHD: an LMM Perceiving Any Aspect Ratio and High-Resolution Images Paper • 2403.11703 • Published Mar 18, 2024 • 17
Sherpa3D: Boosting High-Fidelity Text-to-3D Generation via Coarse 3D Prior Paper • 2312.06655 • Published Dec 11, 2023 • 24
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model Paper • 2311.13231 • Published Nov 22, 2023 • 27
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model Paper • 2311.13231 • Published Nov 22, 2023 • 27
From Knowledge Distillation to Self-Knowledge Distillation: A Unified Approach with Normalized Loss and Customized Soft Labels Paper • 2303.13005 • Published Mar 23, 2023
For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal Paper • 2304.04591 • Published Apr 10, 2023 • 2