6 citations · 11 across the 7 of their papers we have counts for
4 papers · 1 filter
QUOTA: Quantifying Objects with Text-to-Image Models for Any Domain
Wenfang Sun, Yingjun Du, Gaowen Liu +2
We tackle the problem of quantifying the number of objects by a generative text-to-image model. Rather than retraining such a model for each new image domain of interest, which lea…
Prompt Diffusion Robustifies Any-Modality Prompt Learning
Yingjun Du, Gaowen Liu, Yuzhang Shang +3
Foundation models enable prompt-based classifiers for zero-shot and few-shot learning. Nonetheless, the conventional method of employing fixed prompts suffers from distributional s…
A Survey on Large Language Model-Based Game Agents
Sihao Hu, Tiansheng Huang, Gaowen Liu +6
Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities…
Training-Free Semantic Segmentation via LLM-Supervision
Wenfang Sun, Yingjun Du, Gaowen Liu +2
Recent advancements in open vocabulary models, like CLIP, have notably advanced zero-shot classification and segmentation by utilizing natural language for class-specific embedding…