ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3613904.3642646

F. McGee, Rod McCall, Joan Baixauli

引用次数: 0

Exploring the Impact of Interconnected External Interfaces in Autonomous Vehicleson Pedestrian Safety and Experience 探索自动驾驶汽车互联外部接口对行人安全和体验的影响

ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3613904.3642118

Tram Thi Minh Tran, Callum Parker, Marius Hoggenmüller, Yiyuan Wang, M. Tomitsch

{"title":"Exploring the Impact of Interconnected External Interfaces in Autonomous Vehicleson Pedestrian Safety and Experience","authors":"Tram Thi Minh Tran, Callum Parker, Marius Hoggenmüller, Yiyuan Wang, M. Tomitsch","doi":"10.1145/3613904.3642118","DOIUrl":"https://doi.org/10.1145/3613904.3642118","url":null,"abstract":"Policymakers advocate for the use of external Human-Machine Interfaces (eHMIs) to allow autonomous vehicles (AVs) to communicate their intentions or status. Nonetheless, scalability concerns in complex traffic scenarios arise, such as potentially increasing pedestrian cognitive load or conveying contradictory signals. Building upon precursory works, our study explores 'interconnected eHMIs,' where multiple AV interfaces are interconnected to provide pedestrians with clear and unified information. In a virtual reality study (N=32), we assessed the effectiveness of this concept in improving pedestrian safety and their crossing experience. We compared these results against two conditions: no eHMIs and unconnected eHMIs. Results indicated interconnected eHMIs enhanced safety feelings and encouraged cautious crossings. However, certain design elements, such as the use of the colour red, led to confusion and discomfort. Prior knowledge slightly influenced perceptions of interconnected eHMIs, underscoring the need for refined user education. We conclude with practical implications and future eHMI design research directions.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"32 52","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is Cosine-Similarity of Embeddings Really About Similarity? 嵌入的余弦相似性真的与相似性有关吗？

ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3589335.3651526

Harald Steck, Chaitanya Ekanadham, Nathan Kallus

{"title":"Is Cosine-Similarity of Embeddings Really About Similarity?","authors":"Harald Steck, Chaitanya Ekanadham, Nathan Kallus","doi":"10.1145/3589335.3651526","DOIUrl":"https://doi.org/10.1145/3589335.3651526","url":null,"abstract":"Cosine-similarity is the cosine of the angle between two vectors, or equivalently the dot product between their normalizations. A popular application is to quantify semantic similarity between high-dimensional objects by applying cosine-similarity to a learned low-dimensional feature embedding. This can work better but sometimes also worse than the unnormalized dot-product between embedded vectors in practice. To gain insight into this empirical observation, we study embeddings derived from regularized linear models, where closed-form solutions facilitate analytical insights. We derive analytically how cosine-similarity can yield arbitrary and therefore meaningless `similarities.' For some linear models the similarities are not even unique, while for others they are implicitly controlled by the regularization. We discuss implications beyond linear models: a combination of different regularizations are employed when learning deep models; these have implicit and unintended effects when taking cosine-similarities of the resulting embeddings, rendering results opaque and possibly arbitrary. Based on these insights, we caution against blindly using cosine-similarity and outline alternatives.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"5 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval 图像-文本检索中的跨模态和单模态软标记对齐

ArXiv Pub Date : 2024-03-08 DOI: 10.1609/aaai.v38i16.29789

Hailang Huang, Zhijie Nie, Ziqiao Wang, Ziyu Shang

{"title":"Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval","authors":"Hailang Huang, Zhijie Nie, Ziqiao Wang, Ziyu Shang","doi":"10.1609/aaai.v38i16.29789","DOIUrl":"https://doi.org/10.1609/aaai.v38i16.29789","url":null,"abstract":"Current image-text retrieval methods have demonstrated impressive performance in recent years. However, they still face two problems: the inter-modal matching missing problem and the intra-modal semantic loss problem. These problems can significantly affect the accuracy of image-text retrieval. To address these challenges, we propose a novel method called Cross-modal and Uni-modal Soft-label Alignment (CUSA). Our method leverages the power of uni-modal pre-trained models to provide soft-label supervision signals for the image-text retrieval model. Additionally, we introduce two alignment techniques, Cross-modal Soft-label Alignment (CSA) and Uni-modal Soft-label Alignment (USA), to overcome false negatives and enhance similarity recognition between uni-modal samples. Our method is designed to be plug-and-play, meaning it can be easily applied to existing image-text retrieval models without changing their original architectures. Extensive experiments on various image-text retrieval models and datasets, we demonstrate that our method can consistently improve the performance of image-text retrieval and achieve new state-of-the-art results. Furthermore, our method can also boost the uni-modal retrieval performance of image-text retrieval models, enabling it to achieve universal retrieval. The code and supplementary files can be found at https://github.com/lerogo/aaai24_itr_cusa.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"30 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spectrum Translation for Refinement of Image Generation (STIG) Based on Contrastive Learning and Spectral Filter Profile 基于对比学习和光谱滤波器轮廓的图像生成改进（STIG）频谱转换

ArXiv Pub Date : 2024-03-08 DOI: 10.1609/aaai.v38i4.28074

Seokjun Lee, Seung-Won Jung, Hyunseok Seo

{"title":"Spectrum Translation for Refinement of Image Generation (STIG) Based on Contrastive Learning and Spectral Filter Profile","authors":"Seokjun Lee, Seung-Won Jung, Hyunseok Seo","doi":"10.1609/aaai.v38i4.28074","DOIUrl":"https://doi.org/10.1609/aaai.v38i4.28074","url":null,"abstract":"Currently, image generation and synthesis have remarkably progressed with generative models. Despite photo-realistic results, intrinsic discrepancies are still observed in the frequency domain. The spectral discrepancy appeared not only in generative adversarial networks but in diffusion models. In this study, we propose a framework to effectively mitigate the disparity in frequency domain of the generated images to improve generative performance of both GAN and diffusion models. This is realized by spectrum translation for the refinement of image generation (STIG) based on contrastive learning. We adopt theoretical logic of frequency components in various generative networks. The key idea, here, is to refine the spectrum of the generated image via the concept of image-to-image translation and contrastive learning in terms of digital signal processing. We evaluate our framework across eight fake image datasets and various cutting-edge models to demonstrate the effectiveness of STIG. Our framework outperforms other cutting-edges showing significant decreases in FID and log frequency distance of spectrum. We further emphasize that STIG improves image quality by decreasing the spectral anomaly. Additionally, validation results present that the frequency-based deepfake detector confuses more in the case where fake spectrums are manipulated by STIG.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"31 52","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

RLPeri: Accelerating Visual Perimetry Test with Reinforcement Learning and Convolutional Feature Extraction RLPeri：利用强化学习和卷积特征提取加速视觉直观测试

ArXiv Pub Date : 2024-03-08 DOI: 10.1609/aaai.v38i20.30247

Tanvi Verma, LinhLe Dinh, Nicholas Tan, Xinxing Xu, Chingyu Cheng, Yong Liu

{"title":"RLPeri: Accelerating Visual Perimetry Test with Reinforcement Learning and Convolutional Feature Extraction","authors":"Tanvi Verma, LinhLe Dinh, Nicholas Tan, Xinxing Xu, Chingyu Cheng, Yong Liu","doi":"10.1609/aaai.v38i20.30247","DOIUrl":"https://doi.org/10.1609/aaai.v38i20.30247","url":null,"abstract":"Visual perimetry is an important eye examination that helps detect vision problems caused by ocular or neurological conditions. During the test, a patient's gaze is fixed at a specific location while light stimuli of varying intensities are presented in central and peripheral vision. Based on the patient's responses to the stimuli, the visual field mapping and sensitivity are determined. However, maintaining high levels of concentration throughout the test can be challenging for patients, leading to increased examination times and decreased accuracy.\u0000\u0000In this work, we present RLPeri, a reinforcement learning-based approach to optimize visual perimetry testing. By determining the optimal sequence of locations and initial stimulus values, we aim to reduce the examination time without compromising accuracy. Additionally, we incorporate reward shaping techniques to further improve the testing performance. To monitor the patient's responses over time during testing, we represent the test's state as a pair of 3D matrices. We apply two different convolutional kernels to extract spatial features across locations as well as features across different stimulus values for each location. Through experiments, we demonstrate that our approach results in a 10-20% reduction in examination time while maintaining the accuracy as compared to state-of-the-art methods. With the presented approach, we aim to make visual perimetry testing more efficient and patient-friendly, while still providing accurate results.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"33 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140397057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting 利用变分层次变换器考虑多变量时间序列中的非平稳性以进行预测

ArXiv Pub Date : 2024-03-08 DOI: 10.1609/aaai.v38i14.29483

Muyao Wang, Wenchao Chen, Bo Chen

{"title":"Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting","authors":"Muyao Wang, Wenchao Chen, Bo Chen","doi":"10.1609/aaai.v38i14.29483","DOIUrl":"https://doi.org/10.1609/aaai.v38i14.29483","url":null,"abstract":"The forecasting of Multivariate Time Series (MTS) has long been an important but challenging task. Due to the non-stationary problem across long-distance time steps, previous studies primarily adopt stationarization method to attenuate the non-stationary problem of original series for better predictability. However, existed methods always adopt the stationarized series, which ignore the inherent non-stationarity, and have difficulty in modeling MTS with complex distributions due to the lack of stochasticity. To tackle these problems, we first develop a powerful hierarchical probabilistic generative module to consider the non-stationarity and stochastity characteristics within MTS, and then combine it with transformer for a well-defined variational generative dynamic model named Hierarchical Time series Variational Transformer (HTV-Trans), which recovers the intrinsic non-stationary information into temporal dependencies. Being an powerful probabilistic model, HTV-Trans is utilized to learn expressive representations of MTS and applied to the forecasting tasks. Extensive experiments on diverse datasets show the efficiency of HTV-Trans on MTS forecasting tasks.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"6 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Wellbeing Redefined: Toward User-Centric Approach for Positive Social Media Engagement 重新定义数字福祉：以用户为中心的积极社交媒体参与方法

ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3647632.3651392

Yixue Zhao, Tianyi Li, Michael Sobolev

引用次数: 0

To Reach the Unreachable: Exploring the Potential of VR Hand Redirection for Upper Limb Rehabilitation 触及无法触及者：探索虚拟现实手部重定向技术在上肢康复中的潜力

ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3613904.3642912

Peixuan Xiong, Yukai Zhang, Nandi Zhang, Shihan Fu, Xin Li, Yadan Zheng, Jinni Zhou, Xiquan Hu, Mingming Fan

{"title":"To Reach the Unreachable: Exploring the Potential of VR Hand Redirection for Upper Limb Rehabilitation","authors":"Peixuan Xiong, Yukai Zhang, Nandi Zhang, Shihan Fu, Xin Li, Yadan Zheng, Jinni Zhou, Xiquan Hu, Mingming Fan","doi":"10.1145/3613904.3642912","DOIUrl":"https://doi.org/10.1145/3613904.3642912","url":null,"abstract":"Rehabilitation therapies are widely employed to assist people with motor impairments in regaining control over their affected body parts. Nevertheless, factors such as fatigue and low self-efficacy can hinder patient compliance during extensive rehabilitation processes. Utilizing hand redirection in virtual reality (VR) enables patients to accomplish seemingly more challenging tasks, thereby bolstering their motivation and confidence. While previous research has investigated user experience and hand redirection among able-bodied people, its effects on motor-impaired people remain unexplored. In this paper, we present a VR rehabilitation application that harnesses hand redirection. Through a user study and semi-structured interviews, we examine the impact of hand redirection on the rehabilitation experiences of people with motor impairments and its potential to enhance their motivation for upper limb rehabilitation. Our findings suggest that patients are not sensitive to hand movement inconsistency, and the majority express interest in incorporating hand redirection into future long-term VR rehabilitation programs.","PeriodicalId":513202,"journal":{"name":"ArXiv","volume":"31 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140396802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Culture Shapes What People Want From AI 文化如何影响人们对人工智能的需求

ArXiv Pub Date : 2024-03-08 DOI: 10.1145/3613904.3642660

Xiao Ge, Chunchen Xu, Daigo Misaki, Hazel Rose Markus, Jeanne L Tsai

引用次数: 1

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