Hasil untuk "Manners and customs (General)"

Shiori Nakamura, Masato Kikuchi, Tadachika Ozono

Point of purchase (POP) materials can be created to assist non-experts by combining large language models (LLMs) with human insight. Persuasive POP texts require both customer understanding and expressive writing skills. However, LLM-generated texts often lack creative diversity, while human users may have limited experience in marketing and content creation. To address these complementary limitations, we propose a prototype system for small retail stores that enhances POP creation through human-AI collaboration. The system supports users in understanding target customers, generating draft POP texts, refining expressions, and evaluating candidates through simulated personas. Our experimental results show that this process significantly improves text quality: the average evaluation score increased by 2.37 points on a -3 to +3 scale compared to that created without system support.

Irene Hou, Zeyu Xiong, Philip J. Guo et al.

Instructors are increasingly experimenting with AI chatbots for classroom support. To investigate how instructors adapt chatbots to their own contexts, we first analyzed existing resources that provide prompts for educational purposes. We identified ten common categories of customization, such as persona, guardrails, and personalization. We then conducted interviews with ten university STEM instructors and asked them to card-sort the categories into priorities. We found that instructors consistently prioritized the ability to customize chatbot behavior to align with course materials and pedagogical strategies and de-prioritized customizing persona/tone. However, their prioritization of other categories varied significantly by course size, discipline, and teaching style, even across courses taught by the same individual, highlighting that no single design can meet all contexts. These findings suggest that modular AI chatbots may provide a promising path forward. We offer design implications for educational developers building the next generation of customizable classroom AI systems.

Xiao Ni, Yiwei Wang, Tianjun Feng et al.

In collaboration with Alibaba, this study leverages a large-scale field experiment to assess the impact of a generative AI assistant on worker performance in e-commerce after-sales service. Human agents providing digital chat support were randomly assigned with access to a gen AI assistant that offered two core functions: diagnosis of customer issues and solution proposals, presented as text messages. Agents retained discretion to adopt, modify, or disregard AI-generated messages. To evaluate gen AI's impact, we estimate both the intention-to-treat (ITT) effect of gen AI access and the local average treatment effect (LATE) of gen AI usage. Results show that gen AI significantly improved service speed, measured by issue identification time and chat duration. Gen AI also improved subjective service quality reflected in customer ratings and dissatisfaction rates, but it had no significant effect on objective service quality indicated by customer retrial rates. The performance improvements stemmed not only from automation but also from changes in the dynamics of agent-customer interactions: agent communication became more informative and efficient, while customers experienced reduced communication burdens. Low performers achieved the greatest improvements in both service speed and quality, narrowing the performance gap. In contrast, top-performing agents showed little improvement in service speed but experienced declines in both subjective and objective service quality. Evidence suggests that this decline results from increased multitasking tendency, proxied by longer shift-away times across concurrent chats, which slowed customer responses and raised abandonment and retrial rates. These findings suggest that gen AI reshapes work, demanding tailored deployment strategies.

Jiale Lao, Immanuel Trummer

Database research and development often require a large number of SQL queries for benchmarking purposes. However, acquiring real-world SQL queries is challenging due to privacy concerns, and existing SQL generation methods are limited in customization and in satisfying realistic constraints. To address this issue, we present SQLBarber, a system based on Large Language Models (LLMs) to generate customized and realistic SQL workloads. SQLBarber (i) eliminates the need for users to manually craft SQL templates in advance, while providing the flexibility to accept natural language specifications to constrain SQL templates, (ii) scales efficiently to generate large volumes of queries matching any user-defined cost distribution (e.g., cardinality and execution plan cost), and (iii) uses execution statistics from Amazon Redshift and Snowflake to derive SQL template specifications and query cost distributions that reflect real-world query characteristics. SQLBarber introduces (i) a declarative interface for users to effortlessly generate customized SQL templates, (ii) an LLM-powered pipeline augmented with a self-correction module that profiles, refines, and prunes SQL templates based on query costs, and (iii) a Bayesian Optimizer to efficiently explore different predicate values and identify a set of queries that satisfy the target cost distribution. We construct and open-source ten benchmarks of varying difficulty levels and target query cost distributions based on real-world statistics from Snowflake and Amazon Redshift. Extensive experiments on these benchmarks show that SQLBarber is the only system that can generate customized SQL templates. It reduces query generation time by one to three orders of magnitude, and significantly improves alignment with the target cost distribution, compared with existing methods.

Jieqi Di, Sigrún Andradóttir, Hayriye Ayhan

We investigate the optimal pricing strategy in a service-providing framework, where customers can become impatient and leave the system prior to service completion. In this setting, a price is quoted to an incoming customer based on the current number of customers in the system. When the quoted price is lower than the price the incoming customer is willing to pay (which follows a fixed probability distribution), then the customer joins the system and a reward equal to the quoted price is earned. A cost is incurred upon abandonment and a holding cost is incurred for customers waiting to be served. Our goal is to determine the pricing policy that maximizes the long-run average profit. Unlike traditional queueing systems without abandonments, we show that the optimal quoted prices do not always increase with the queue length in this setting. In particular, we prove that the optimal pricing policy is always uni-modal and provide conditions guaranteeing that the optimal policy is increasing in the number of customers in the system. Moreover, we introduce two heuristics that simplify the optimal dynamic pricing policy. Both heuristics admit customers until the number of customers in the system reaches a certain threshold. The cutoff static policy charges all admitted customers a fixed price while the two price policy charges one price when the arriving customer can enter service immediately and another price if the customer needs to wait. By selecting the price(s) and threshold that maximize the long-run average profit, both heuristics achieve near optimality and the two price policy provides more robustness compared to the cutoff static policy.

Francesco Kruk, Savindu Herath, Prithwiraj Choudhury

In recent years, large language models (LLMs) have demonstrated exponential improvements that promise transformative opportunities across various industries. Their ability to generate human-like text and ensure continuous availability facilitates the creation of interactive service chatbots aimed at enhancing customer experience and streamlining enterprise operations. Despite their potential, LLMs face critical challenges, such as a susceptibility to hallucinations and difficulties handling complex linguistic scenarios, notably code switching and dialectal variations. To address these challenges, this paper describes the design of a multilingual chatbot for Bengali-English customer service interactions utilizing retrieval-augmented generation (RAG) and targeted prompt engineering. This research provides valuable insights for the human-computer interaction (HCI) community, emphasizing the importance of designing systems that accommodate linguistic diversity to benefit both customers and businesses. By addressing the intersection of generative AI and cultural heterogeneity, this late-breaking work inspires future innovations in multilingual and multicultural HCI.

Rosiana Natalie, Ruei-Che Chang, Smitha Sheshadri et al.

Blind and low-vision (BLV) people use audio descriptions (ADs) to access videos. However, current ADs are unalterable by end users, thus are incapable of supporting BLV individuals' potentially diverse needs and preferences. This research investigates if customizing AD could improve how BLV individuals consume videos. We conducted an interview study (Study 1) with fifteen BLV participants, which revealed desires for customizing properties like length, emphasis, speed, voice, format, tone, and language. At the same time, concerns like interruptions and increased interaction load due to customization emerged. To examine AD customization's effectiveness and tradeoffs, we designed CustomAD, a prototype that enables BLV users to customize AD content and presentation. An evaluation study (Study 2) with twelve BLV participants showed using CustomAD significantly enhanced BLV people's video understanding, immersion, and information navigation efficiency. Our work illustrates the importance of AD customization and offers a design that enhances video accessibility for BLV individuals.

Xiaoyue Zhang, Hanzhang Qin, Mabel C. Chou

We propose a novel algorithm for online resource allocation with non-stationary customer arrivals and unknown click-through rates. We assume multiple types of customers arrive in a nonstationary stochastic fashion, with unknown arrival rates in each period, and that customers' click-through rates are unknown and can only be learned online. By leveraging results from the stochastic contextual bandit with knapsack and online matching with adversarial arrivals, we develop an online scheme to allocate the resources to nonstationary customers. We prove that under mild conditions, our scheme achieves a ``best-of-both-world'' result: the scheme has a sublinear regret when the customer arrivals are near-stationary, and enjoys an optimal competitive ratio under general (non-stationary) customer arrival distributions. Finally, we conduct extensive numerical experiments to show our approach generates near-optimal revenues for all different customer scenarios.

Chengbo Yuan, Chuan Wen, Tong Zhang et al.

We address the challenge of acquiring real-world manipulation skills with a scalable framework. We hold the belief that identifying an appropriate prediction target capable of leveraging large-scale datasets is crucial for achieving efficient and universal learning. Therefore, we propose to utilize 3D flow, which represents the future trajectories of 3D points on objects of interest, as an ideal prediction target. To exploit scalable data resources, we turn our attention to human videos. We develop, for the first time, a language-conditioned 3D flow prediction model directly from large-scale RGBD human video datasets. Our predicted flow offers actionable guidance, thus facilitating zero-shot skill transfer in real-world scenarios. We deploy our method with a policy based on closed-loop flow prediction. Remarkably, without any in-domain finetuning, our method achieves an impressive 81\% success rate in zero-shot human-to-robot skill transfer, covering 18 tasks in 6 scenes. Our framework features the following benefits: (1) scalability: leveraging cross-embodiment data resources; (2) wide application: multiple object categories, including rigid, articulated, and soft bodies; (3) stable skill transfer: providing actionable guidance with a small inference domain-gap. Code, data, and supplementary materials are available https://general-flow.github.io

Xiangyi Li, Jiajia Guo, Chao-Kai Wen et al.

Deep learning has revolutionized the design of the channel state information (CSI) feedback module in wireless communications. However, designing the optimal neural network (NN) architecture for CSI feedback can be a laborious and time-consuming process. Manual design can be prohibitively expensive for customizing NNs to different scenarios. This paper proposes using neural architecture search (NAS) to automate the generation of scenario-customized CSI feedback NN architectures, thereby maximizing the potential of deep learning in exclusive environments. By employing automated machine learning and gradient-descent-based NAS, an efficient and cost-effective architecture design process is achieved. The proposed approach leverages implicit scene knowledge, integrating it into the scenario customization process in a data-driven manner, and fully exploits the potential of deep learning for each specific scenario. To address the issue of excessive search, early stopping and elastic selection mechanisms are employed, enhancing the efficiency of the proposed scheme. The experimental results demonstrate that the automatically generated architecture, known as Auto-CsiNet, outperforms manually-designed models in both reconstruction performance (achieving approximately a 14% improvement) and complexity (reducing it by approximately 50%). Furthermore, the paper analyzes the impact of the scenario on the NN architecture and its capacity.

Vittorio De Falco

The general relativistic Poynting-Robertson (PR) effect is a very important dissipative phenomenon occurring in high-energy astrophysics. Recently, it has been proposed a new model, which upgrades the two-dimensional (2D) description in the three-dimensional (3D) case in Kerr spacetime. The radiation field is considered as constituted by photons emitted from a rigidly rotating spherical source around the compact object. Such dynamical system admits the existence of a critical hypersurface, region where the gravitational and radiation forces balance and the matter reaches it at the end of its motion. Selected test particle orbits are displayed. We show how to prove the stability of these critical hypersurfaces within the Lyapunov theory. Then, we present how to study such effect under the Lagrangian formalism, explaining how to analytically derive the Rayleigh potential for the radiation force. In conclusion, further developments and future projects are discussed.

Erik Brynjolfsson, Danielle Li, Lindsey Raymond

We study the staggered introduction of a generative AI-based conversational assistant using data from 5,172 customer support agents. Access to AI assistance increases worker productivity, as measured by issues resolved per hour, by 15\% on average, with substantial heterogeneity across workers. Less experienced and lower-skilled workers improve both the speed and quality of their output while the most experienced and highest-skilled workers see small gains in speed and small declines in quality. We also find evidence that AI assistance facilitates worker learning and improves English fluency, particularly among international agents. While AI systems improve with more training data, we find that the gains from AI adoption are largest for relatively rare problems, where human agents have less baseline training and experience. Finally, we provide evidence that AI assistance improves the experience of work along two key dimensions: customers are more polite and less likely to ask to speak to a manager.

João Minhoto Marques

Embora Leonel Neves seja sobretudo associado a obras para infância, ele é igualmente autor de um conjunto assinalável de livros de poesia. A atenção ao mundo, ao outro e à poesia são características da sua poética particularmente visíveis nas obras de maturidade, como Memória de Timor-Leste, embora estejam presentes ao longo do seu percurso literário. Este artigo estuda a poesia de Leonel Neves, ocupando-se das referidas características, da coerência da poética e do caso particular do memorial timorense.

Inês Silva de Almeida, Maria João Pereira

Com o objetivo de pensar a presença e o ensino-aprendizagem da língua portuguesa em Timor-Leste, neste artigo foi tomado como objeto de estudo o caso de quatro turmas de formação de professores em língua portuguesa (nível B1) em Timor-Leste, cuja formação se insere no Projeto PRO-Português (cooperação de Portugal, Camões, I.P., e Timor-Leste, INFORDEPE). Partindo de uma recolha de inquéritos e de observação pessoal, serão apresentados alguns desafios e motivações para o nosso trabalho, a perspetiva dos próprios formandos/professores sobre a sua aprendizagem e algumas reflexões sobre este contexto tão especial em que o português é língua oficial, mas não materna.

Cultural General Intelligence Team, Avishkar Bhoopchand, Bethanie Brownfield et al.

Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. In humans, it is the inheritance process that powers cumulative cultural evolution, expanding our skills, tools and knowledge across generations. We provide a method for generating zero-shot, high recall cultural transmission in artificially intelligent agents. Our agents succeed at real-time cultural transmission from humans in novel contexts without using any pre-collected human data. We identify a surprisingly simple set of ingredients sufficient for generating cultural transmission and develop an evaluation methodology for rigorously assessing it. This paves the way for cultural evolution as an algorithm for developing artificial general intelligence.

Inocência Mata, Mário César Lugarinho

O artigo propõe discussão a respeito da formulação de histórias das literaturas africanas de língua portuguesa, tendo em vista a sobreposição temporal e cronológica com a literatura colonial portuguesa. Além disso, destaca obras e autores que são requeridos pelos sistemas literários nacionais africanos e a literatura colonial portuguesa, para tanto, recorre à proposta da teoria do polissistema de Itamar Even-Zohar que oferece subsídios a perspectivas pós-coloniais.

Thomas Conley, Jack St. Clair, Jugal Kalita

Although people have the ability to engage in vapid dialogue without effort, this may not be a uniquely human trait. Since the 1960's researchers have been trying to create agents that can generate artificial conversation. These programs are commonly known as chatbots. With increasing use of neural networks for dialog generation, some conclude that this goal has been achieved. This research joins the quest by creating a dialog generating Recurrent Neural Network (RNN) and by enhancing the ability of this network with auxiliary loss functions and a beam search. Our custom loss functions achieve better cohesion and coherence by including calculations of Maximum Mutual Information (MMI) and entropy. We demonstrate the effectiveness of this system by using a set of custom evaluation metrics inspired by an abundance of previous research and based on tried-and-true principles of Natural Language Processing.

Paul Karaenke, Maximilian Schiffer, Stefan Waldherr

Today's ride-hailing systems experienced significant growth and ride-pooling promises to allow for efficient and sustainable on-demand transportation. However, efficient ride-pooling requires a large pool of participating customers. To increase the customers' willingness for participation, we study a novel customer-centered pooling (CCP) mechanism, accounting for individual customers' pooling benefits. We study the benefit of this mechanism from a customer, fleet operator, and system perspective, and compare it to existing provider-centered pooling (PCP) mechanisms. We prove that it is individually rational and weakly dominant for a customer to participate in CCP, but not for PCP. We substantiate this analysis with complementary numerical studies, implementing a simulation environment based on real-world data that allows us to assess both mechanisms' benefit. To this end, we present results for both pooling mechanisms and show that pooling can benefit all stakeholders in on-demand transportation. Moreover, we analyze in which cases a CCP mechanism Pareto dominates a PCP mechanism and show that a mobility service operator would prefer CCP mechanisms over PCP mechanisms for all price segments. Simultaneously, CCP mechanisms reduce the overall distance driven in the system up to 32% compared to not pooling customers. Our results provide decision support for mobility service operators that want to implement and improve pooling mechanisms as they allow us to analyze the impact of a CCP and a PCP mechanism from a holistic perspective. Among others, we show that CCP mechanisms can lead to a win-win situation for operators and customers while simultaneously improving system performance and reducing emissions.

Aziz Ali Haerulloh, Etty Saringendyanti, Ayu Septiani

Penelitian ini menggunakan metode sejarah yang terdiri dari tahapan heuristik, kritik, interpretasi, dan historiografi, serta menggunakan pendekatan sosial ekonomi untuk menjelaskan secara kronologis pengaruh adanya persebaran industri batik terhadap kesejahteraan masyarakat Bandung, Cirebon, dan Tasikmalaya. Penelitian ini menggunakan sampel dalam mencari dan mengumpulkan data. Berdasarkan hasil penelitian studi pustaka, studi lapangan, observasi, dan wawancara, menunjukkan bahwa penyebaran budaya membatik berpengaruh terhadap munculnya industri batik yang berada di Bandung, Cirebon, dan Tasikmalaya. Ketiga daerah tersebut memiliki peran dalam menciptakan lapangan pekerjaan bagi masyarakat sekitar yang memiiki keahlian dalam membatik, baik tulis maupun cap. Selain itu, industri batik di tiga kota tersebut memiliki skala produksi industri rumah tangga, kecil, dan menengah. Menjadi suatu hal yang menarik melihat persebaran dan dinamika industri batik dengan cara produksi tradisional di Bandung, Cirebon, dan Tasikmalaya berkembang pada saat Indonesia mengalami masa industrialisasi selama Orde Baru. Penelitian ini menunjukkan terjadinya pasang-surut industri batik tradisional di tengah-tengah gempuran modernisasi di bidang industri, tidak terkecuali dalam tekstil lokal. The study used the historical method which included a number of stages, such as heuristics, criticism, interpretation, and historiography and also applied a socio-economic approach to explain chronologically the effect of the distribution of the batik industry on the welfare of the people of Bandung, Cirebon, and Tasikmalaya. The sample is used in this study to find and collect data. The results of literature study, field studies, observations, and interviews have revealed that the spread of batik culture has had a significant effect on the emergence of the batik industries in Bandung, Cirebon, and Tasikmalaya. The batik industries in the three regions has played an important role in creating jobs for local communities who have the expertise in doing the batik work, both the ‘batik tulis' and the ‘batik cap'. In addition, the batik industry in the three cities also has the industrial productions which includes either the household or small to medium scale. It is an interesting fact to see the distribution and the dynamics of the batik industry were produced through traditional production methods in Bandung, Cirebon and Tasikmalaya when Indonesia was experiencing a period of industrialization during the New Order. The research has shown that there have been ups and downs in the traditional batik industry amidst the threat of modernization in the industrial sector, including local textiles.

Fábio Waki

Este artigo propõe uma leitura de O que os cegos estão sonhando? (2014), de Noemi Jaffe, a fim de discutir como uma das principais responsabilidades da crítica literária, à luz da relação entre literatura e direitos humanos, é, para além de colaborar com a eficiência da elaboração e aplicação desses direitos, a de colaborar com uma explicitação de tudo o que pode consistir em uma dimensão da dignidade humana. Ciente de que dignidade é um conceito polêmico no contexto dos direitos humanos, proponho debater aqui menos como a literatura pode nos ajudar a definir o que é dignidade – uma perspectiva recorrente na crítica literária à luz dos direitos humanos –, e mais como ela pode contribuir com a ideia de que na impossibilidade de se definir dignidade há, enfim, uma boa premissa para se defender os direitos humanos.