From the 1 of 6 linked papers with an AI index.
6 papers
HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models
Hei Yi Mak, Shadan Golestan, Hoang Le +10
The paper introduces HiFloat4, a 4-bit floating-point format and a Rollout Residual Quantization technique that enable end-to-end reinforcement learning post‑training of large lang…
All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding
Tanzila Rahman, Renjie Liao, Leonid Sigal
Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object counting, question answering, an…
HiFloat4 Format for Language Model Pre-training on Ascend NPUs
Mehran Taghian, Yunke Peng, Xing Huang +22
Large foundation models have become central to modern machine learning, with performance scaling predictably with model size and data. However, training and deploying such models i…
To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models
Jiayun Luo, Wan-Cyuan Fan, Lyuyang Wang +4
Large Vision Language Models (LVLMs) have recently emerged as powerful architectures capable of understanding and reasoning over both visual and textual information. These models t…
Visual Concept-driven Image Generation with Text-to-Image Diffusion Model
Tanzila Rahman, Shweta Mahajan, Hsin-Ying Lee +3
Text-to-image (TTI) diffusion models have demonstrated impressive results in generating high-resolution images of complex and imaginative scenes. Recent approaches have further ext…
MMFactory: A Universal Solution Search Engine for Vision-Language Tasks
Wan-Cyuan Fan, Tanzila Rahman, Leonid Sigal
With advances in foundational and vision-language models, and effective fine-tuning techniques, a large number of both general and special-purpose models have been developed for a…