most citedReassessing the Role of Supervised Fine-Tuning: An Empirical Study in VLM Reasoning

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

One Size, Many Fits: Aligning Diverse Group-Wise Click Preferences in Large-Scale Advertising Image Generation

Shuo Lu, Haohan Wang, Wei Feng +14

Advertising image generation has increasingly focused on online metrics like Click-Through Rate (CTR), yet existing approaches adopt a ``one-size-fits-all" strategy that optimizes…

cs.CL2025

DeepResearch-Slice: Bridging the Retrieval-Utilization Gap via Explicit Text Slicing

Shuo Lu, Yinuo Xu, Jianjie Cheng +3

Deep Research agents predominantly optimize search policies to maximize retrieval probability. However, we identify a critical bottleneck: the retrieval-utilization gap, where mode…

cs.LG20251 cited

Reassessing the Role of Supervised Fine-Tuning: An Empirical Study in VLM Reasoning

Yongcan Yu, Lingxiao He, Shuo Lu +10

Recent advances in vision-language models (VLMs) reasoning have been largely attributed to the rise of reinforcement Learning (RL), which has shifted the community's focus away fro…

cs.CV2025

Frustratingly Easy Feature Reconstruction for Out-of-Distribution Detection

Yingsheng Wang, Shuo Lu, Jian Liang +2

Out-of-distribution (OOD) detection helps models identify data outside the training categories, crucial for security applications. While feature-based post-hoc methods address this…

cs.CV2025

Uni-Layout: Integrating Human Feedback in Unified Layout Generation and Evaluation

Shuo Lu, Yanyin Chen, Wei Feng +7

Layout generation plays a crucial role in enhancing both user experience and design efficiency. However, current approaches suffer from task-specific generation capabilities and pe…