2 citations · 3 across the 24 of their papers we have counts for
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Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
Wenhao Deng, Long Wei, Chenglei Yu +1
Reinforcement learning with verifiable rewards (RLVR) has recently enhanced the reasoning capabilities of large language models (LLMs), particularly for mathematical problem solvin…
BuildArena: A Physics-Aligned Interactive Benchmark of LLMs for Engineering Construction
Tian Xia, Tianrun Gao, Wenhao Deng +4
Engineering construction automation aims to transform natural language specifications into physically viable structures, requiring complex integrated reasoning under strict physica…
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
Peiyan Hu, Xiaowei Qian, Wenhao Deng +8
The application of deep learning for partial differential equation (PDE)-constrained control is gaining increasing attention. However, existing methods rarely consider safety requi…
On the Guidance of Flow Matching
Ruiqi Feng, Chenglei Yu, Wenhao Deng +2
Flow matching has shown state-of-the-art performance in various generative tasks, ranging from image generation to decision-making, where generation under energy guidance (abbrevia…
VFScale: Intrinsic Reasoning through Verifier-Free Test-time Scalable Diffusion Model
Tao Zhang, Jia-Shu Pan, Ruiqi Feng +1
Inspired by human SYSTEM 2 thinking, LLMs excel at complex reasoning tasks via extended Chain-of-Thought. However, similar test-time scaling for diffusion models to tackle complex…