5 papers · 1 filter
VecGlypher: Unified Vector Glyph Generation with Language Models
Xiaoke Huang, Bhavul Gauri, Kam Woh Ng +12
Vector glyphs are the atomic units of digital typography, yet most learning-based pipelines still depend on carefully curated exemplar sheets and raster-to-vector postprocessing, w…
A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng +30
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, especially when guided by explicit chain-of-thought (CoT) reasoning that verbalizes intermediate s…
Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains
Juncheng Wu, Sheng Liu, Haoqin Tu +5
Recent advances in reasoning-enhanced Large Language Models such as OpenAI-o1/3 and DeepSeek-R1 have significantly improved performance on complex tasks. However, the quality and t…
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
Hardy Chen, Haoqin Tu, Fali Wang +5
This work revisits the dominant supervised fine-tuning (SFT) then reinforcement learning (RL) paradigm for training Large Vision-Language Models (LVLMs), and reveals a key finding:…
m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models
Xiaoke Huang, Juncheng Wu, Hui Liu +2
Test-time scaling has emerged as a powerful technique for enhancing the reasoning capabilities of large language models. However, its effectiveness in medical reasoning remains unc…