INT v.s. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats Paper • 2510.25602 • Published Oct 29 • 76
OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM Paper • 2510.15870 • Published Oct 17 • 89
QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs Paper • 2510.11696 • Published Oct 13 • 176
Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation Paper • 2508.05635 • Published Aug 7 • 73
EmbRACE-3K: Embodied Reasoning and Action in Complex Environments Paper • 2507.10548 • Published Jul 14 • 36
Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation Paper • 2507.08441 • Published Jul 11 • 61
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection Paper • 2411.14794 • Published Nov 22, 2024 • 13
Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free Paper • 2410.10814 • Published Oct 14, 2024 • 51
MC-MoE: Mixture Compressor for Mixture-of-Experts LLMs Gains More Paper • 2410.06270 • Published Oct 8, 2024 • 1
Can OOD Object Detectors Learn from Foundation Models? Paper • 2409.05162 • Published Sep 8, 2024 • 9
SVG: 3D Stereoscopic Video Generation via Denoising Frame Matrix Paper • 2407.00367 • Published Jun 29, 2024 • 10
What Matters in Detecting AI-Generated Videos like Sora? Paper • 2406.19568 • Published Jun 27, 2024 • 16
SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models Paper • 2405.14917 • Published May 23, 2024 • 1
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study Paper • 2404.14047 • Published Apr 22, 2024 • 45
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs Paper • 2402.04291 • Published Feb 6, 2024 • 50