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检索条件"任意字段=Proceedings of the 29th International ACM Conference on 3D Web Technology"

共 459 条记录，以下是31-40 订阅

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Slapo: A Schedule Language for Progressive Optimization of Large deep Learning Model Training 24

Slapo: A Schedule Language for Progressive Optimization of L...

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29th acm international conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)

作者： Chen, Hongzheng Yu, Cody Hao Zheng, Shuai Zhang, Zhen Zhang, Zhiru Wang, Yida Cornell Univ Ithaca NY 14850 USA Boson AI Inc Santa Clara CA USA Amazon Web Serv Santa Clara CA USA Amazon Seattle WA USA

ISBN: (纸本)9798400703850

Recent years have seen an increase in the development of large deep learning (dL) models, which makes training efficiency crucial. Common practice is struggling with the trade-off between usability and performance. On one hand, dL frameworks such as PyTorch use dynamic graphs to facilitate model developers at a price of sub-optimal model training performance. On the other hand, practitioners propose various approaches to improving the training efficiency by sacrificing some of the flexibility, ranging from making the graph static for more thorough optimization (e.g., XLA) to customizing optimization towards large-scale distributed training (e.g., deepSpeed and Megatron-LM). In this paper, we aim to address the tension between usability and training efficiency through separation of concerns. Inspired by dL compilers that decouple the platform-specific optimizations of a tensor-level operator from its arithmetic definition, this paper proposes a schedule language, Slapo, to decouple model execution from definition. Specifically, Slapo works on a PyTorch model and uses a set of schedule primitives to convert the model for common model training optimizations such as high-performance kernels, effective 3d parallelism, and efficient activation checkpointing. Com- pared to existing optimization solutions, Slapo progressively optimizes the model "as-needed" through high-level primi- tives, and thus preserving programmability and debuggabil- ity for users to a large extent. Our evaluation results show that by scheduling the existing hand-crafted optimizations in a systematic way using Slapo, we are able to improve training throughput by up to 2.92x on a single machine with 8 NVIdIA V100 GPUs, and by up to 1.41x on multiple machines with up to 64 GPUs, when compared to the out-of-the-box performance of deepSpeed and Megatron-LM.

关键词： Schedule Language distributed Training Compiler Optimization deep Learning Large Language Models

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ASSEMBLY OF SPACE FRAMES IN HYBRId TEAMS Adaptive digital Fabrication Workflows for Human-Robot Collaboration 29th

ASSEMBLY OF SPACE FRAMES IN HYBRID TEAMS Adaptive Digital Fa...

引用

29th international conference of the Association-for-Computer-Aided-Architectural-design-Research-in-Asia (CAAdRIA)

作者： Skevaki, Eleni Kladeftira, Marirena Pittiglio, Alexandra Nicole Parascho, Stefana Ecole Polytech Fed Lausanne Lab Creat Computat Lausanne Switzerland

ISBN: (纸本)9789887891833

In spatial timber assemblies, a multitude of factors can lead to errors that hinder the implementation of complete automation including but not limited to inaccuracies of the robotic setup, deformations of the structures during assembly, or the natural dimensional variability of wood. Any unplanned event, construction detail, or material variability that was not embedded ahead of time in the CAd environment can cause failure. To mitigate these challenges, this paper expands this conventional one-directional design-to-fabrication pipeline and proposes interactive digital fabrication workflows where humans and robots work synergistically, blending the adaptability of human craft with the precision of robotic technology. the method is validated with two prototypes comprising linear timber elements and 3d printed connections that showcase adaptability in the fabrication setup and allow for design changes to happen concurrently with fabrication. In this paradigm, human operators are not mere extensions of the robotic system but rather central to dynamic problem-solving and instrumental in making immediate adjustments.

关键词： Human-Robot Interaction 3d Printed Connections Timber Assemblies Human-In-the-Loop Multi-Agent Fabrication Adaptive digital Fabrication

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EXTRUdING dREdGEd-BASEd MATERIAL FOR CONCRETE FORMWORK thROUGH RAPId LIQUId PRINTING 29th

EXTRUDING DREDGED-BASED MATERIAL FOR CONCRETE FORMWORK THROU...

引用

29th international conference of the Association-for-Computer-Aided-Architectural-design-Research-in-Asia (CAAdRIA)

作者： Lo, Tzu-Hsien Liu, Bosheng Feng Chia Univ Taichung Taiwan

ISBN: (纸本)9789887891833

the research delves into investigating the printed reusable dredged-Based Material (dBM) concrete formwork using Rapid Liquid Printing (RLP) technology, revealing its potential impact on existing concrete construction by substituting sacrificial formwork usage. this is an initial exploration of the Rapid Liquid Printing process injecting dredged-Based-Material material (M1) into the water environment (M2), where the water acts as the suspension and phasechanging accelerator. the dredged-Based Material injection involves meticulously blended dredged material with bio-based cetyl palmitate. this paper focuses on designing and implementing an extrusion system and the extruder head utilizing stepper motors to control the flow rate, ensuring a stable extrusion state while monitoring the temperature. the dredged-Based Material for the Rapid Liquid Printing experiment uncovered the challenge and the solution of creating a consistent extrusion through a custom extruder that can maintain the dredged-Based-Material workability and construct a proportionally scaled prototype to validate the findings and practicality for the dredged-Based Material Rapid Liquid Printing approach.

关键词： Rapid Liquid Printing dredged-Based Material Reusable Material 3d Printed Formwork Reusable Concrete Formwork

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AdAPTING thE SOFTWARE dESIGN PATTERN MOdEL FOR AI-ENABLEd dESIGN COMPUTING 29th

ADAPTING THE SOFTWARE DESIGN PATTERN MODEL FOR AI-ENABLED DE...

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29th international conference of the Association-for-Computer-Aided-Architectural-design-Research-in-Asia (CAAdRIA)

作者： Kimm, Geoff White, Marcus Burry, Mark Swinburne Univ Technol Hawthorn Vic 3122 Australia

ISBN: (纸本)9789887891819

Exponential AI development requires an adaptation to new technology by traditionally reluctant architects and allied practitioners. this paper examines the potential of the software design pattern (SdP) model, used in software engineering to capture and reapply designs, as one underpinning. Patterns have creativity and pedagogical benefits in parametric modelling, yet consideration of AI and broader design computing as well as the derivation and versatility implied by an SdP model are underexamined. this research questions how, in an AI context, new patterns may evolve for varied AI levels and non-geometrical features. It is undertaken in the Unity game engine with critical application of two prominent extant patterns as a computational workflow design response to a real-world citizen engagement scenario. A novel, feature-agnostic pattern is derived with a simple AI model and is verified for other AI models. the work concludes design computing patterns can abstract existing pattern knowledge to flexibly evolve and apply across rapidly changing AI-enabled design computing contexts and thereby assist practitioners to positively respond to AI advances.

关键词： Artificial Intelligence Computational design Software design Patterns Architectural Practice Unity 3d Intelligent Agents

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MORGAN: MPEG Original Reference Geometric Avatar Neutral 23

MORGAN: MPEG Original Reference Geometric Avatar Neutral

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28th international conference on web3d technology (web3d)

作者： Avril, Quentin Regateiro, Joao Gosselin, Philippe Henri Le Clerc, Francois Guillotel, Philippe Interdigital Cesson Sevigne France

ISBN: (纸本)9798400703249

To address the need for interoperable user representations (avatars) cross-platform exchange format for immersive realities, ISO/IEC JTC 1/SC29/WG03 MPEG Systems has standardized a Scene description framework in ISO/IEC 23090-14 [ISO/IEC 2023]. It serves as a baseline format for user representation format to enrich the interactive experience between 3d objects in an immersive scene. this work presents the MPEG Original Reference Geometric Avatar Neutral (Morgan), a humanoid avatar specified as informative content in the MPEG-I Scene description (MPEG-I Sd) standardization group. Morgan is a generic avatar representation that facilitates interactivity and manipulation in immersive realities and is accompanied by a complete body mesh and realistic appearance, hierarchical skeletal representation, blend shapes, eye globes, jaws with teeth and semantical representation of human body parts.

关键词： humanoid avatar 3d model standards animation graphics

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Exploring the Potential of Generative AI in dIY Assistive technology design by Occupational therapists 24

Exploring the Potential of Generative AI in DIY Assistive Te...

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26th international acm SIGACCESS conference on Computers and Accessibility (ASSETS)

作者： Li, Mixuan Aflatoony, Leila Georgia Inst Technol Sch Ind Design Atlanta GA 30332 USA

ISBN: (纸本)9798400706776

this paper examines the potential integration of generative AI into the assistive technology (AT) making and adaptation process, with Occupational therapists (OTs) as the primary beneficiaries, as they are often involved in designing 'do-it-yourself assistive technology' (dIY AT) to support independent living for individuals with disabilities. We initiated the study by considering the traditional AT-making processes performed by OTs and prototyped a web interface that incorporates generative AI to support these processes. through a series of user studies, we collected OTs' preliminary insights on how generative AI could bridge the gap between clinical reasoning and technical design, potentially streamlining the AT creation and adaptation process while maintaining the crucial element of personalized AT solutions. the study's findings highlight several key benefits of generative AI in OT practice: 1) customization of AT solutions tailored to individual client needs, 2) improved visualization capabilities for client communication, 3) inspiration for new AT design ideas, and 4) potential for rapid prototyping and practice. However, key drawbacks were noted, including limitations in inputting measurements, which can lead to inaccurate outputs and necessitate substantial modifications to the created AT, along with challenges associated with the current state of generative AI.

关键词： Assistive technology Occupational therapy Generative AI Hand Impairment 3d printing Adaptation design Tool

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web-based Long-term Spine Treatment Outcome Forecasting 23

Web-based Long-term Spine Treatment Outcome Forecasting

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29th acm SIGKdd conference on Knowledge discovery and data Mining (Kdd)

作者： Ye, Hangting Liu, Zhining Cao, Wei Amiri, Amir M. Bian, Jiang Chang, Yi Lurie, Jon d. Weinstein, Jim Liu, Tie-Yan Jilin Univ Sch Artificial Intelligence Changchun Peoples R China Univ Illinois Champaign IL USA Microsoft Res Beijing Peoples R China Microsoft Res Redmond WA USA Dartmouth Inst Hanover NH USA

ISBN: (纸本)9798400701030

the aging of global population is witnessing increasing prevalence of spinal disorders. According to latest statistics, nearly five percent of the global population is suffering from spinal disorders. To relieve the pain, many spine patients tend to choose surgeries. However, recent evidences reveal that some spine patients can self-heal over time with nonoperative treatment and even surgeries may not ease the pain for some others, which raises a critical question regarding the appropriateness of such surgeries [31, 32]. Furthermore, the complex and time-consuming diagnostic process places a great burden on both clinicians and patients. due to the development of web technology, it is possible for spine patients to obtain decision making suggestions on the Internet. the uniqueness of web technology, including its popularity, convenience, and immediacy, makes intelligent healthcare techniques, especially Treatment Outcome Forecasting (TOF), able to support clinical decision-making for doctors and healthcare providers. despite a few machine-learning-based methods have been proposed for TOF, their performance and feasibility are mostly unsatisfactory due to the neglect of a few practical challenges (caused by applying on the Internet), including biased data selection, noisy supervision, and patient noncompliance. In light of this, we propose deepTOF, a novel end-to-end deep learning model to cope with the unique challenges in web-based long-term continuous spine TOF. In particular, we combine different patient groups and train a unified predictive model to eliminate the data selection bias. Towards robust learning, we further take advantage of indirect but fine-grained supervision signals to mutually calibrate with the noisy training labels. Additionally, a feature selector was co-trained with deepTOF to select the most important features (i.e., answers/indicators that need to be collected) for inference, thus easing the use of deepTOF during web-based real-world applic

关键词： Intelligent healthcare Medical forecasting Health informatics

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GSCore: Efficient Radiance Field Rendering via Architectural Support for 3d Gaussian Splatting 24

GSCore: Efficient Radiance Field Rendering via Architectural...

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29th acm international conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2024

作者： Lee, Junseo Lee, Seokwon Lee, Jungi Park, Junyong Sim, Jaewoong Seoul National University Korea Republic of

ISBN: (纸本)9798400703867

this paper presents GSCore, a hardware acceleration unit that efficiently executes the rendering pipeline of 3d Gaussian Splatting with algorithmic optimizations. GSCore builds on the observations from an in-depth analysis of Gaussian-based radiance field rendering to enhance computational efficiency and bring the technique to wide adoption. In doing so, we present several optimization techniques, Gaussian shape-aware intersection test, hierarchical sorting, and subtile skipping, all of which are synergistically integrated with GSCore. We implement the hardware design of GSCore, synthesize it using a commercial 28nm technology, and evaluate the performance across a range of synthetic and real-world scenes with varying image resolutions. Our evaluation results show that GSCore achieves a 15.86× speedup on average over the mobile consumer GPU with a substantially smaller area and lower energy consumption. © 2024 Copyright held by the owner/author(s).

关键词： Image resolution

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USER-CENTEREd dESIGN (UCd) BASEd web VR FOR thE VALUE OF CULTURAL HERITAGE 29th

USER-CENTERED DESIGN (UCD) BASED WEB VR FOR THE VALUE OF CUL...

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29th international conference on Computer-Aided Architectural design Research in Asia, CAAdRIA 2024

作者： Choi, Jin Woo Jin Park, Jong Kim, Eonyong Jong Jun, Han Hanyang University Korea Republic of Andong National University Korea Republic of

ISBN: (纸本)9789887891826

this study explores the use of web-based Virtual Reality(web VR) in effectively communicating the value of cultural heritage. At the heart of this research is the integration of User-Centered design(UCd) principles to enhance User Experience (UX) within web VR environments. the research underscores the accessibility and cost effectiveness of web VR in overcoming the limitations of traditional museum visits and in broadening public engagement with cultural heritage. Additionally, it highlights how UCd contributes to creating immersive and interactive experiences, with a focus on user needs and expectations. Furthermore, the study points out the critical importance of storytelling, advanced 3d modeling, and intuitive interfaces in delivering the complex narratives and values of cultural heritage. these approaches aid in facilitating a deeper understanding and emotional connection with the heritage, beyond just visual experiences. the findings of this study suggest that web VR, enriched with UCd principles, storytelling, 3d modeling, and intuitive interfaces, offers a comprehensive and appealing approach to making cultural heritage accessible and meaningful to a diverse audience. this research provides foundational insights for future studies and practical applications in the field of digital cultural heritage exhibition. © 2024 and published by the Association for Computer-Aided Architectural design Research in Asia (CAAdRIA), Hong Kong.

关键词： Virtual reality

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S²phere: Semi-Supervised Pre-training forweb Search over Heterogeneous Learning to Rank data 23

S<SUP>2</SUP>phere: Semi-Supervised Pre-training forWeb Sear...

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29th acm SIGKdd conference on Knowledge discovery and data Mining (Kdd)

作者： Li, Yuchen Xiong, Haoyi Kong, Linghe Wang, Qingzhong Wang, Shuaiqiang Chen, Guihai Yin, dawei Shanghai Jiao Tong Univ Shanghai Peoples R China Baidu Inc Beijing Peoples R China

ISBN: (纸本)9798400701030

While Learning to Rank (LTR) models on top of transformers have been widely adopted to achieve decent performance, it is still challenging to train the model with sufficient data as only an extremely small number of query-webpage pairs could be annotated versus trillions ofwebpages available online and billions ofweb search queries everyday. In the meanwhile, industry research communities have released a number of open-source LTR datasets with well annotations but incorporating different designs of LTR features/labels (i.e., heterogeneous domains). In this work, inspired by the recent progress in pre-training transformers for performance advantages, we study the problem of pre-training LTR models using both labeled and unlabeled samples, especially we focus on the use of well-annotated samples in heterogeneous open-source LTR datasets to boost the performance of pre-training. Hereby, we propose S(2)phere- SemiSupervised Pre-training with Heterogeneous LTR data strategies for LTR models using both unlabeled and labeled query-webpage pairs across heterogeneous LTR datasets. S(2)phere consists of a threestep approach: (1) Semi-supervised Feature Extraction Pre-training via Perturbed Contrastive Loss, (2) Cross-domain Ranker Pre-training over Heterogeneous LTR datasets and (3) End-to-end LTR Fine-tuning via Modular Network Composition. Specifically, given an LTR model composed of a backbone (the feature extractor), a neck (the module to reason the orders) and a head (the predictor of ranking scores), S(2)phere uses unlabeled/labeled data from the search engine to pre-train the backbone in Step (1) via semi-supervised learning;then Step (2) incorporates multiple open-source heterogeneous LTR datasets to improve pre-training of the neck module as shared parameters of cross-domain learning;and finally, S(2)phere in Step (3) composes the backbone and neck with a randomly-initialized head into a whole LTR model and fine-tunes the model using search engine data with various l

关键词： Learning to Rank Large-scale web Search Pre-training Heterogeneous data

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