Wenming Ye — accepted AI-conference papers

2025

Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs

Yifan Shen, Yuanzhe Liu, Jingyuan Zhu, Xu Cao, Xiaofeng Zhang, Yixiao He +3

NeurIPS 2025poster

Current Vision-Language Models (VLMs) struggle with fine-grained spatial reasoning, particularly when multi-step logic and precise spatial alignment are required. In this work, we introduce SpatialReasoner-R1, a vision-language reasoning model designed to address these limitations. To construct high…

Cited by 0 Source ↗Scholar ↗

2024

In-Context Learning with Iterative Demonstration Selection

Chengwei Qin, Aston Zhang, Chen Chen, Anirudh Dagar, Wenming Ye

EMNLP 2024finding

Spurred by advancements in scale, large language models (LLMs) have demonstrated strong few-shot learning ability via in-context learning (ICL). However, the performance of ICL has been shown to be highly sensitive to the selection of few-shot demonstrations. Selecting the most suitable examples as…

Cited by 44 Source ↗PDF ↗Scholar ↗