Search Results for author: Minfeng Zhu

Found 13 papers, 8 papers with code

Exploring Multimodal Prompt for Visualization Authoring with Large Language Models

no code implementations18 Apr 2025 Zhen Wen, Luoxuan Weng, Yinghao Tang, Runjin Zhang, Yuxin Liu, Bo Pan, Minfeng Zhu, Wei Chen

To explore the potential of multimodal prompting in visualization authoring, we design VisPilot, which enables users to easily create visualizations using multimodal prompts, including text, sketches, and direct manipulations on existing visualizations.

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization

1 code implementation13 Mar 2025 Yi Yang, Xiaoxuan He, Hongkun Pan, Xiyan Jiang, Yan Deng, Xingtao Yang, Haoyu Lu, Dacheng Yin, Fengyun Rao, Minfeng Zhu, Bo Zhang, Wei Chen

Existing visual-language models often struggle to effectively analyze and reason visual content, resulting in suboptimal performance on complex reasoning tasks.

Multimodal Reasoning

DataLab: A Unified Platform for LLM-Powered Business Intelligence

no code implementations3 Dec 2024 Luoxuan Weng, Yinghao Tang, Yingchaojie Feng, Zhuo Chang, Ruiqin Chen, Haozhe Feng, Chen Hou, Danqing Huang, Yang Li, Huaming Rao, Haonan Wang, Canshi Wei, Xiaofeng Yang, Yuhui Zhang, Yifeng Zheng, Xiuqi Huang, Minfeng Zhu, Yuxin Ma, Bin Cui, Peng Chen, Wei Chen

To achieve this unification, we design a domain knowledge incorporation module tailored for enterprise-specific BI tasks, an inter-agent communication mechanism to facilitate information sharing across the BI workflow, and a cell-based context management strategy to enhance context utilization efficiency in BI notebooks.

Large Language Model Task Planning

MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model

no code implementations19 Aug 2024 Xinyang Wang, Yi Yang, Minfeng Zhu, Kecheng Zheng, Shi Liu, Wei Chen

Recent advancements in pre-trained Vision-Language Models (VLMs) have highlighted the significant potential of prompt tuning for adapting these models to a wide range of downstream tasks.

Domain Generalization Language Modeling +1

JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models

no code implementations12 Apr 2024 Yingchaojie Feng, Zhizhang Chen, Zhining Kang, Sijia Wang, Minfeng Zhu, Wei zhang, Wei Chen

Addressing these concerns necessitates a comprehensive analysis of jailbreak prompts to evaluate LLMs' defensive capabilities and identify potential weaknesses.

Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning

1 code implementation21 Feb 2024 Zhaorui Yang, Tianyu Pang, Haozhe Feng, Han Wang, Wei Chen, Minfeng Zhu, Qian Liu

The surge in Large Language Models (LLMs) has revolutionized natural language processing, but fine-tuning them for specific tasks often encounters challenges in balancing performance and preserving general instruction-following abilities.

Instruction Following Language Modeling +2

PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation

1 code implementation18 Jul 2023 Yingchaojie Feng, Xingbo Wang, Kam Kwai Wong, Sijia Wang, Yuhong Lu, Minfeng Zhu, Baicheng Wang, Wei Chen

Generative text-to-image models have gained great popularity among the public for their powerful capability to generate high-quality images based on natural language prompts.

Prompt Engineering

CoSDA: Continual Source-Free Domain Adaptation

1 code implementation13 Apr 2023 Haozhe Feng, Zhaorui Yang, Hesun Chen, Tianyu Pang, Chao Du, Minfeng Zhu, Wei Chen, Shuicheng Yan

Recently, SFDA has gained popularity due to the need to protect the data privacy of the source domain, but it suffers from catastrophic forgetting on the source domain due to the lack of data.

Source-Free Domain Adaptation

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

3 code implementations21 Nov 2020 Hao-Zhe Feng, Kezhi Kong, Minghao Chen, Tianye Zhang, Minfeng Zhu, Wei Chen

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference results.

4k Semi-Supervised Image Classification +1

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