1 citations · 1 across the 2 of their papers we have counts for
4 papers
LLMs as Scalable, General-Purpose Simulators For Evolving Digital Agent Training
Yiming Wang, Da Yin, Yuedong Cui +8
Digital agents require diverse, large-scale UI trajectories to generalize across real-world tasks, yet collecting such data is prohibitively expensive in both human annotation, inf…
SafeWorld: Geo-Diverse Safety Alignment
Da Yin, Haoyi Qiu, Kung-Hsiang Huang +2
In the rapidly evolving field of Large Language Models (LLMs), ensuring safety is a crucial and widely discussed topic. However, existing works often overlook the geo-diversity of…
VISCO: Benchmarking Fine-Grained Critique and Correction Towards Self-Improvement in Visual Reasoning
Xueqing Wu, Yuheng Ding, Bingxuan Li +4
The ability of large vision-language models (LVLMs) to critique and correct their reasoning is an essential building block towards their self-improvement. However, a systematic ana…
Verbalized Representation Learning for Interpretable Few-Shot Generalization
Cheng-Fu Yang, Da Yin, Wenbo Hu +4
Humans recognize objects after observing only a few examples, a remarkable capability enabled by their inherent language understanding of the real-world environment. Developing ver…