activity
20242026
most citedAnnotation-Free Human Sketch Quality Assessment

3 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SynMind: Reducing Semantic Hallucination in fMRI-Based Image Reconstruction

Lan Yang, Minghan Yang, Ke Li +3

Recent advances in fMRI-based image reconstruction have achieved remarkable photo-realistic fidelity. Yet, a persistent limitation remains: while reconstructed images often appear…

cs.AI20251 cited

Rethinking Reasoning Quality in Large Language Models through Enhanced Chain-of-Thought via RL

Haoyang He, Zihua Rong, Kun Ji +5

Reinforcement learning (RL) has recently become the dominant paradigm for strengthening the reasoning abilities of large language models (LLMs). Yet the rule-based reward functions…

cs.SD2025

Amadeus: Autoregressive Model with Bidirectional Attribute Modelling for Symbolic Music

Hongju Su, Ke Li, Lan Yang +2

Existing state-of-the-art symbolic music generation models predominantly adopt autoregressive or hierarchical autoregressive architectures, modelling symbolic music as a sequence o…

cs.CV20253 cited

Annotation-Free Human Sketch Quality Assessment

Lan Yang, Kaiyue Pang, Honggang Zhang +1

As lovely as bunnies are, your sketched version would probably not do them justice (Fig.~\ref{fig:intro}). This paper recognises this very problem and studies sketch quality assess…

cs.CV2024

VersaGen: Unleashing Versatile Visual Control for Text-to-Image Synthesis

Zhipeng Chen, Lan Yang, Yonggang Qi +4

Despite the rapid advancements in text-to-image (T2I) synthesis, enabling precise visual control remains a significant challenge. Existing works attempted to incorporate multi-face…