8 papers
RubricRL: Simple Generalizable Rewards for Text-to-Image Generation
Xuelu Feng, Yunsheng Li, Ziyu Wan +4
Reinforcement learning (RL) has recently emerged as a promising approach for aligning text-to-image generative models with human preferences. A key challenge, however, lies in desi…
Improving Code Localization with Repository Memory
Boshi Wang, Weijian Xu, Yunsheng Li +4
Code localization is a fundamental challenge in repository-level software engineering tasks such as bug fixing. While existing methods equip language agents with comprehensive tool…
Phi-4-Mini-Reasoning: Exploring the Limits of Small Reasoning Language Models in Math
Haoran Xu, Baolin Peng, Hany Awadalla +11
Chain-of-Thought (CoT) significantly enhances formal reasoning capabilities in Large Language Models (LLMs) by training them to explicitly generate intermediate reasoning steps. Wh…
Olympus: A Universal Task Router for Computer Vision Tasks
Yuanze Lin, Yunsheng Li, Dongdong Chen +3
We introduce Olympus, a new approach that transforms Multimodal Large Language Models (MLLMs) into a unified framework capable of handling a wide array of computer vision tasks. Ut…
Show and Segment: Universal Medical Image Segmentation via In-Context Learning
Yunhe Gao, Di Liu, Zhuowei Li +4
Medical image segmentation remains challenging due to the vast diversity of anatomical structures, imaging modalities, and segmentation tasks. While deep learning has made signific…
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
Microsoft, :, Abdelrahman Abouelenin +73
We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…