Search Results for author: Jiaxin Ge

Found 7 papers, 2 papers with code

Iterative Prompt Relabeling for diffusion model with RLDF

no code implementations23 Dec 2023 Jiaxin Ge, Xinyan Chen, Tianjun Zhang, Shanghang Zhang

IP-RLDF first samples a batch of images conditioned on the text, then relabels the text prompts of unmatched text-image pairs with classifier feedback.

Image Generation reinforcement-learning +2

Recursive Visual Programming

no code implementations4 Dec 2023 Jiaxin Ge, Sanjay Subramanian, Baifeng Shi, Roei Herzig, Trevor Darrell

Visual Programming (VP) has emerged as a powerful framework for Visual Question Answering (VQA).

Code Generation Question Answering +1

From Wrong To Right: A Recursive Approach Towards Vision-Language Explanation

no code implementations21 Nov 2023 Jiaxin Ge, Sanjay Subramanian, Trevor Darrell, Boyi Li

Addressing the challenge of adapting pre-trained vision-language models for generating insightful explanations for visual reasoning tasks with limited annotations, we present ReVisE: a $\textbf{Re}$cursive $\textbf{Vis}$ual $\textbf{E}$xplanation algorithm.

Explanation Generation Visual Question Answering (VQA) +1

Lyfe Agents: Generative agents for low-cost real-time social interactions

no code implementations3 Oct 2023 Zhao Kaiya, Michelangelo Naim, Jovana Kondic, Manuel Cortes, Jiaxin Ge, Shuying Luo, Guangyu Robert Yang, Andrew Ahn

Meanwhile, our techniques enabled Lyfe Agents to operate at a computational cost 10-100 times lower than existing alternatives.

Entailment as Robust Self-Learner

1 code implementation26 May 2023 Jiaxin Ge, Hongyin Luo, Yoon Kim, James Glass

Experiments on binary and multi-class classification tasks show that SimPLE leads to more robust self-training results, indicating that the self-trained entailment models are more efficient and trustworthy than large language models on language understanding tasks.

Multi-class Classification Natural Language Understanding +1

Chain of Thought Prompt Tuning in Vision Language Models

no code implementations16 Apr 2023 Jiaxin Ge, Hongyin Luo, Siyuan Qian, Yulu Gan, Jie Fu, Shanghang Zhang

Chain of Thought is a simple and effective approximation to human reasoning process and has been proven useful for natural language processing (NLP) tasks.

Domain Generalization Image Classification +4

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