7 papers
Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation
Mengshi Qi, Wei Deng, Xianlin Zhang +1
Large Vision-Language Models have achieved significant reasoning performance in various tasks. However, there are few studies on text-to-3D indoor scene generation with LVLMs. The…
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
Wei Deng, Xianlin Zhang, Mengshi Qi
Enabling Vision-Language Models (VLMs) to perform spatial reasoning remains challenging. Existing approaches treat VLMs as passive observers, which is difficult for real-world appl…
Restoring Initial Noise Sensitivity in Text-to-Image Distillation via Geometric Alignment
Huayang Huang, Ruoyu Wang, Jinhui Zhao +5
Generative distillation significantly accelerates text-to-image (T2I) generation by compressing multi-step trajectories into few-step student models while preserving perceptual qua…
Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization
Kevin Rojas, Jiahe Lin, Kashif Rasul +4
Diffusion language models (DLMs) enable parallel, order-agnostic generation with iterative refinement, offering a flexible alternative to autoregressive large language models (LLMs…
Is Your LLM Really Mastering the Concept? A Multi-Agent Benchmark
Shuhang Xu, Weijian Deng, Yixuan Zhou +1
Concepts serve as fundamental abstractions that support human reasoning and categorization. However, it remains unclear whether large language models truly capture such conceptual…
Reinforcing Multi-Turn Reasoning in LLM Agents via Fine-Grained Reward Structure and Credit Assignment
Quan Wei, Siliang Zeng, Chenliang Li +9
Reinforcement Learning (RL) approaches have been wildly used to enhance the reasoning capabilities of Large Language Model (LLM) agents in long-horizon, multi-turn scenarios. Such…