no code implementations • 31 Jul 2024 • Simon Valentin, Jinmiao Fu, Gianluca Detommaso, Shaoyuan Xu, Giovanni Zappella, Bryan Wang
Large language models (LLMs) can be prone to hallucinations - generating unreliable outputs that are unfaithful to their inputs, external facts or internally inconsistent.
no code implementations • 22 Apr 2024 • Yanhui Guo, Shaoyuan Xu, Jinmiao Fu, Jia Liu, Chaosheng Dong, Bryan Wang
This paper introduces \textbf{Q-tuning}, a novel approach for continual prompt tuning that enables the lifelong learning of a pre-trained language model.
no code implementations • 15 Feb 2024 • Bryan Wang, Yuliang Li, Zhaoyang Lv, Haijun Xia, Yan Xu, Raj Sodhi
Based on these findings, we propose design implications to inform the future development of agent-assisted content editing.
no code implementations • 7 Dec 2023 • Stephen Brade, Bryan Wang, Mauricio Sousa, Gregory Lee Newsome, Sageev Oore, Tovi Grossman
This is achieved with three main features: a multimodal search engine for a large library of synthesizer sounds; a user centered genetic algorithm by which completely new sounds can be created and selected given the users preferences; a sound editing support feature which highlights and gives examples for key control parameters with respect to a text or audio based query.
no code implementations • 12 Oct 2023 • Tao Li, Gang Li, Zhiwei Deng, Bryan Wang, Yang Li
To perform a task, recent works often require a model to learn from trace examples of the task via either supervised learning or few/many-shot prompting.
no code implementations • 12 Sep 2023 • Moyan Li, Jinmiao Fu, Shaoyuan Xu, Huidong Liu, Jia Liu, Bryan Wang
Unlike public data, another practical challenge on shopping websites is that some paired images are of low quality.
no code implementations • 11 Sep 2023 • Chien-Chih Wang, Shaoyuan Xu, Jinmiao Fu, Yang Liu, Bryan Wang
Firstly, an outer SNN is trained using labeled and unlabeled data.
no code implementations • 19 Jun 2023 • Minghe Zhang, Chaosheng Dong, Jinmiao Fu, Tianchen Zhou, Jia Liang, Jia Liu, Bo Liu, Michinari Momma, Bryan Wang, Yan Gao, Yi Sun
In this paper, we introduce AdaSelection, an adaptive sub-sampling method to identify the most informative sub-samples within each minibatch to speed up the training of large-scale deep learning models without sacrificing model performance.
no code implementations • 18 Apr 2023 • Stephen Brade, Bryan Wang, Mauricio Sousa, Sageev Oore, Tovi Grossman
Text-to-image generative models have demonstrated remarkable capabilities in generating high-quality images based on textual prompts.
1 code implementation • 18 Sep 2022 • Bryan Wang, Gang Li, Yang Li
This paper investigates the feasibility of enabling versatile conversational interactions with mobile UIs using a single LLM.
no code implementations • 7 Dec 2021 • Huidong Liu, Shaoyuan Xu, Jinmiao Fu, Yang Liu, Ning Xie, Chien-Chih Wang, Bryan Wang, Yi Sun
In this paper, we propose the Cross-Modality Attention Contrastive Language-Image Pre-training (CMA-CLIP), a new framework which unifies two types of cross-modality attentions, sequence-wise attention and modality-wise attention, to effectively fuse information from image and text pairs.
2 code implementations • 7 Aug 2021 • Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, Yang Li
Mobile User Interface Summarization generates succinct language descriptions of mobile screens for conveying important contents and functionalities of the screen, which can be useful for many language-based application scenarios.
1 code implementation • 11 Nov 2018 • Bryan Wang, Yi-Hsuan Yang
To build such an AI performer, we propose in this paper a deep convolutional model that learns in an end-to-end manner the score-to-audio mapping between a symbolic representation of music called the piano rolls and an audio representation of music called the spectrograms.
Sound Multimedia Audio and Speech Processing