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Can Small Language Models be Good Reasoners for Sequential Recommendation? 24

Can Small Language Models be Good Reasoners for Sequential R...

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33rd acm Web Conference, WWW 2024

作者： Wang, Yuling Tian, Changxin Hu, Binbin Yu, Yanhua Liu, Ziqi Zhang, Zhiqiang Zhou, Jun Pang, Liang Wang, Xiao Beijing University of Posts and Telecommunications Ant Group Beijing China Ant Group Hangzhou China Beijing University of Posts and Telecommunications Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China Beihang University Beijing China

ISBN: (纸本)9798400701719

Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations empowered by LLMs. Firstly, user behavior patterns are often complex, and relying solely on one-step reasoning from LLMs may lead to incorrect or task-irrelevant responses. Secondly, the prohibitively resource requirements of LLM (e.g., ChatGPT-175B) are overwhelmingly high and impractical for real sequential recommender systems. In this paper, we propose a novel Step-by-step knowLedge dIstillation fraMework for recommendation (SLIM), paving a promising path for sequential recommenders to enjoy the exceptional reasoning capabilities of LLMs in a "slim"(i.e. resource-efficient) manner. We introduce CoT prompting based on user behavior sequences for the larger teacher model. The rationales generated by the teacher model are then utilized as labels to distill the downstream smaller student model (e.g., LLaMA2-7B). In this way, the student model acquires the step-by-step reasoning capabilities in recommendation tasks. We encode the generated rationales from the student model into a dense vector, which empowers recommendation in both ID-based and ID-agnostic scenarios. Extensive experiments demonstrate the effectiveness of SLIM over state-of-the-art baselines, and further analysis showcasing its ability to generate meaningful recommendation reasoning at affordable costs. © 2024 acm.

关键词： Recommender systems

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Sustainability, Development, and Human-Computer Interaction 25

Sustainability, Development, and Human-Computer Interaction

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Sharma, Vishal Kumar, Neha School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Georgia Tech Atlanta GA United States

ISBN: (纸本)9798400713941

Researchers in Human-Computer Interaction (HCI) have studied the design and use of technologies for sustainability and development, contributing to the subfields of Sustainable HCI and HCI for Development. Increasingly, there have been calls within and outside HCI for a more integrated approach to sustainable development. To identify the potential of such an approach, we present a comprehensive review of HCI scholarship on sustainability and development, combined with an analysis of interviews with researchers working in and across both subfields. Using the lens of political economy, we uncover understandings, critiques, tensions, and considerations toward advancing scholarship at the intersections of sustainability, development, and HCI. We conclude by inviting the larger Special Interest Group on Computer-Human Interaction (SIGCHI) community to join us in collectively devising pathways for technology-mediated sustainable development. © 2025 Copyright held by the owner/author(s).

关键词： Development HCI4D SHCI Sustainability Sustainable Development

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Demonstrating OpenEarable 2.0: An AI-Powered Ear Sensing Platform

Demonstrating OpenEarable 2.0: An AI-Powered Ear Sensing Pla...

引用

2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Röddiger, Tobias Zitz, Valeria Hummel, Jonas Küttner, Michael Lepold, Philipp King, Tobias Paradiso, Joseph A. Clarke, Christopher Beigl, Michael TECO Pervasive Computing Systems Karlsruhe Institute of Technology (KIT) Baden-Wuertemberg Karlsruhe Germany MIT Media Lab. Massachusetts Institute of Technology Cambridge MA United States University of Bath Bath United Kingdom

ISBN: (纸本)9798400713958

In this demo, we present OpenEarable 2.0, an open-source earphone platform designed to provide an interactive exploration of physiological ear sensing and the development of AI applications. Attendees will have the opportunity to explore real-time sensor data and understand the capabilities of OpenEarable 2.0’s sensing components. OpenEarable 2.0 integrates a rich set of sensors, including two ultrasound-capable microphones (inward/outward), a 3-axis ear canal accelerometer/bone conduction microphone, a 9-axis head inertial measurement unit, a pulse oximeter, an optical temperature sensor, an ear canal pressure sensor, a microSD slot, and a microcontroller. Participants will be able to try out the web-based dashboard and mobile app for real-time control and data visualization. Furthermore, the demo will show different applications and real-time data based on OpenEarable 2.0 across physiological sensing and health monitoring, movement and activity tracking, and human-computer interaction. © 2025 Copyright held by the owner/author(s).

关键词： earables earphones hearables hearing aid in-ear open hardware open wearables open-source

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Performance Portability of Electron Repulsion Integrals and Their Related Methods across Peta to Exascale Architectures

Performance Portability of Electron Repulsion Integrals and ...

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2024 Workshops of the International Conference for High Performance computing, Networking, Storage and analysis, SC Workshops 2024

作者： Sattasathuchana, Tosaporn Xu, Peng Oryspayev, Dossay Bertoni, Colleen Roskop, Luke B. Gordon, Mark S. University of Hawai'i at Manoa Department of Chemistry HonoluluHI United States Iowa State University Ames National Laboratory Department of Chemistry AmesIA United States Stony Brook University Institute for Advanced Computational Science Stony BrookNY United States Argonne National Laboratory Leadership Computing Facility LemontIL United States Hewlett Packard Enterprise HPC Systems Software BloomingtonMN United States

ISBN: (纸本)9798350355543

Entering the exascale era, graphical processing units (GPUs) have been developed by various vendors for large-scale HPC machines. Nine of the top 10 computers on the Top500 List have heterogeneous architectures containing GPUs as accelerators. To take advantage of these computational resources, it is essential to maintain a balance between performance and portability, i.e., making the codes functional, performant, and portable across GPU vendors. In this work, the efforts of restructuring and porting several key CPU kernels in the GAMESS quantum chemistry software package to AMD, Intel, and NVIDIA GPUs via an OpenMP API will be discussed. The use of the OpenMP directive model allows one to successfully run the same code across many GPUs of different vendors. However, since OpenMP is a high-level programming model, it relies on vendor implementations to handle the GPU code generation, and since implementations vary, there are large differences in performance even on the same hardware with different vendor compilers. Presented here are challenges faced during porting CPU code to GPU code with OpenMP, which other porting efforts may also face, such as memory limitations, major restructuring needed for code with branching, and differences in compiler optimizations and tuning. The strategies and approaches to address these challenges are discussed. In this work, the performance results across the supercomputing systems, Summit, Aurora, Frontier, and Perlmutter with a variety of vendor software stacks are presented. © 2024 IEEE.

关键词： Aurora CPHF Frontier Hartree Fock Perlmutter Summit TDHF

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Translation and Validation of The Video Game Demand Scale to Spanish 25

Translation and Validation of The Video Game Demand Scale to...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Lee, Heejae Dominguez Partida, Gabriel Bowman, Nicholas David Chauveau, Philippe De Villemor S.I. Newhouse School of Public Communications Syracuse University Syracuse NY United States Escuela de Comunicación Universidad Panamericana Mexico City Mexico Department of Humanities and Communication Embry-Riddle Aeronautical University Prescott AZ United States

ISBN: (纸本)9798400713941

With efforts to investigate the role of interactivity on user psychology in video games, scholars have demonstrated that interactivity may induce cognitive, emotional, physical (controller and exertional), and social demands of global gamers. However, existing studies are missing Latin American gamers as critical yet understudied gaming communities. Drawing on the interactivity-as-demand model, we conducted a mixed-method online survey to test measurement validity on localized versions of the video game demand scale (VGDS) for Spanish-speaking gamers (N = 195). Results showed that the Spanish-translated scale replicated the a priori five-factor structure of VGDS. Emergent themes from gamers' comments mirrored VGDS factors, with additional insights into the cognitive demand of creative thinking, emotional demand of feeling nostalgia, physical demand of being precise, and social demand of interacting with non-player characters. These findings provide a pancultural perspective of Spanish-speaking gamers' perceptions of their gaming while offering nuanced insights into their experiences for future research. © 2025 Copyright held by the owner/author(s).

关键词： interactivity-as-demand measurement validity Mexico player psychology Spanish video game demand scale

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Literature Reviews in HCI: A Review of Reviews 23

Literature Reviews in HCI: A Review of Reviews

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CHI conference on Human Factors in computing systems (CHI)

作者： Stefanidi, Evropi Bentvelzen, Marit Wozniak, Pawel W. Kosch, Thomas Wozniak, Mikolaj P. Mildner, Thomas Schneegass, Stefan Mueller, Heiko Niess, Jasmin Univ Bremen Bremen Germany Univ Utrecht Utrecht Netherlands Chalmers Univ Technol Gothenburg Sweden HU Berlin Bremen Germany Carl von Ossietzky Univ Oldenburg Oldenburg Germany Univ Duisburg Essen Essen Germany OFFIS Inst Informat Univ Oldenburg Germany Univ St Gallen St Gallen Switzerland Univ Oslo Oslo Norway

ISBN: (纸本)9781450394215

This paper analyses Human-Computer Interaction (HCI) literature reviews to provide a clear conceptual basis for authors, reviewers, and readers. HCI is multidisciplinary and various types of literature reviews exist, from systematic to critical reviews in the style of essays. Yet, there is insufcient consensus of what to expect of literature reviews in HCI. Thus, a shared understanding of literature reviews and clear terminology is needed to plan, evaluate, and use literature reviews, and to further improve review methodology. We analysed 189 literature reviews published at all SIGCHI conferences and acm Transactions on Computer-Human Interaction (TOCHI) up until August 2022. We report on the main dimensions of variation: (i) contribution types and topics;and (ii) structure and methodologies applied. We identify gaps and trends to inform future meta work in HCI and provide a starting point on how to move towards a more comprehensive terminology system of literature reviews in HCI.

关键词： literature review meta review meta-analysis literature survey method

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A Comparative analysis of Information Gathering by Chatbots, Questionnaires, and Humans in Clinical Pre-Consultation 25

A Comparative Analysis of Information Gathering by Chatbots,...

引用

2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Li, Brenna Tauseef, Saba Truong, Khai N. Mariakakis, Alex Computer Science University of Toronto Toronto ON Canada Independent Researcher Brampton ON Canada

ISBN: (纸本)9798400713941

Information gathering is an important capability that allows chatbots to understand and respond to users' needs, yet the effectiveness of LLM-powered chatbots at this task remains underexplored. Our work investigates this question in the context of clinical pre-consultation, wherein patients provide information to an intermediary before meeting with a physician to facilitate communication and reduce consultation inefficiencies. We conducted a study at a walk-in clinic with 45 patients who interacted with one of three conversational agents: a chatbot, a questionnaire, and a Wizard-of-Oz. We analyzed patients' messages using metrics adapted from Grice's maxims to assess the quality of information gathered at each conversation turn. We found that the Wizard and LLM were more successful than the questionnaire because they modified questions and asked follow-ups when participants provided unsatisfactory answers. However, the LLM did not ask nearly as many follow-up questions as the Wizard, particularly when participants provided unclear answers. © 2025 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： chatbot LLM Pre-consultation primary care walk-in clinic

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CamPU: A Multi-Camera Processing Unit for Deep Learning-based 3D Spatial computing systems 57

CamPU: A Multi-Camera Processing Unit for Deep Learning-base...

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57th Annual IEEE/acm International Symposium on Microarchitecture, MICRO 2024

作者： Im, Dongseok Yoo, Hoi-Jun Information & Electronics Research Institute KAIST Daejeon Korea Republic of School of Electrical Engineering KAIST Daejeon Korea Republic of

ISBN: (纸本)9798350350579

A 3D spatial computing system that understands a surrounding environment and interacts with real-world objects has emerged with the development of deep learning technologies. A multi-camera system captures a surrounding view of a scene using multiple cameras, and a deep neural network (DNN) system extracts semantic features from multi-camera images and provides useful information to users. However, processing a multi-camera system requires massive memory accesses as the number of cameras increases while processing a DNN system can improve throughput by exploiting batch processing. This performance gap limits the overall performance of 3D spatial computing systems. To solve this problem, a multi-camera processing unit (CamPU) is proposed. CamPU exploits the inter-and intra-data reuse methods on multi-camera images, minimizing memory accesses for image projection. Moreover, the out-of-order image projection unit with cache memory is designed to increase multi-image projection throughput by avoiding redundant cache accesses and hiding the latency of high-level memory accesses. Lastly, the overlap-Aware blending unit speeds up image blending by efficiently handling overlapping regions between adjacent images. The CamPU architecture is evaluated through RTL-level simulation, and the CamPU-integrated DNN platform provides a comprehensive analysis of end-To-end multi-camera deep learning-based 3D spatial systems. Finally, CamPU speedups the overall system performance 2.9 x faster than an NVIDIA RTX2080Ti GPU platform. © 2024 IEEE.

关键词： Cache memory

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Woes, Workarounds, and Wishes of Users Living in a Multinetwork Reality

Woes, Workarounds, and Wishes of Users Living in a Multinetw...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in computing systems, CHI EA 2023

作者： Hossain, Md Nazmul Vigil-Hayes, Morgan Northern Arizona University FlagstaffAZ United States

ISBN: (纸本)9781450394222

Despite efforts towards pervasive, high-speed broadband connectivity, users worldwide continue to experience a persistent multinetwork reality-a reality of intermittent Internet access over multiple networks of varying capacities across space and time. In this late-breaking work, we investigate the challenges users face while using different Internet-based services and the mitigating strategies they adopt to overcome those challenges in a multinetwork reality. In addition, we also investigate how users envision software-based interventions that might augment their existing strategies and help them better manage their activities in a multinetwork reality. Finally, based on our findings from a qualitative analysis of semi-structured interviews, we explore a two-dimensional design space defined by cognitive and resource costs and discuss directions for future work. © 2023 Owner/Author.

关键词： broadband connectivity design space digital divide multinetwork reality qualitative analysis

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SoK: Machine Learning for Continuous Integration

SoK: Machine Learning for Continuous Integration

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2023 IEEE/acm International Workshop on Cloud Intelligence and AIOps, AIOps 2023

作者： Arani, Ali Kazemi Zahedi, Mansooreh Le, Triet Huynh Minh Babar, Muhammad Ali School of Computer Science University of Adelaide Adelaide Australia School of Computing and Information Systems University of Melbourne Melbourne Australia

ISBN: (纸本)9798350323740

Continuous Integration (CI) has become a well- established software development practice for automatically and continuously integrating code changes during software development. An increasing number of Machine Learning (ML) based approaches for automation of CI phases are being reported in the literature. It is timely and relevant to provide a Systemization of Knowledge (SoK) of ML-based approaches for CI phases. This paper reports an SoK of different aspects of the use of ML for CI. Our systematic analysis also highlights the deficiencies of the existing ML-based solutions that can be improved for advancing the state-of-the-art. © 2023 IEEE.

关键词： Machine learning

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