Design Frameworks

Related topics:

• A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy
  Recent improvements in large language models (LLMs) have led many researchers to focus on building fully autonomous AI agents. This position paper questions whether this approach is the right path for…
• Agent S: An Open Agentic Framework that Uses Computers Like a Human
  We present Agent S, an open agentic framework that enables autonomous interaction with computers through a Graphical User Interface (GUI), aimed at transforming human-computer interaction by automatin…
• An extended framework for characterizing social robots
  1.2 Brief summary of frameworks for characterizing social robots Before outlining the content of our framework, it is useful to first look at existing frameworks for classifying social robots. In part…
• Bridging the gulf of envisioning: Cognitive design challenges in llm interfaces.
  Large language models (LLMs) exhibit dynamic capabilities and appear to comprehend complex and ambiguous natural language prompts. However, calibrating LLM interactions is challenging for interface de…
• Building Machines that Learn and Think with People
  What do we want from machine intelligence? We envision machines that are not just tools for thought, but partners in thought: reasonable, insightful, knowledgeable, reliable, and trustworthy systems t…
• Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm
  The computers are social actors framework (CASA), derived from the media equation, explains how people communicate with media and machines demonstrating social potential. Many studies have challenged …
• ChatGPT Reads Your Tone and Responds Accordingly -- Until It Does Not -- Emotional Framing Induces Bias in LLM Outputs
  Background: Large Language Models (LLMs) like GPT-4 tailor their responses not just to the content but also to the tone of user prompts. Prior work has hinted that emotional phrasing – whether optimis…
• Conceptual Design Generation Using Large Language Models
  The following characteristics of the solutions were explored: 1. Feasibility: rated on an anchored scale from 0 (the technology does not exist to create the solution) to 2 (the solution can be implem…
• Considering the Context to Build Theory in HCI, HRI, and HMC: Explicating Differences in Processes of Communication and Socialization With Social Technologies
  our research can be outpaced by developments in the modern technological landscape. To address this issue, we often focus our inquiries conceptually rather than technically through an affordance-based…
• Conversational DNA: A New Visual Language for Understanding Dialogue Structure in Human and AI
  What if the patterns hidden within dialogue reveal more about communication than the words themselves? We introduce Conversational DNA, a novel visual language that treats any dialogue – whether betwe…
• Conversational Prompt Engineering
  Conversational Prompt Engineering (CPE), a user-friendly tool that helps users create personalized prompts for their specific tasks. CPE uses a chat model to briefly interact with users, helping them …
• Design Principles for Generative AI Applications
  We present six principles for the design of generative AI applications that address unique characteristics of generative AI UX and offer new interpretations and extensions of known issues in the desig…
• Disambiguating Anthropomorphism and Anthropomimesis in Human-Robot Interaction
  Henry Shevlin [[Emotions]] [[Psychology Users]] [[Design Frameworks]] In this preliminary work, we offer an initial disambiguation of the theoretical concepts anthropomorphism and anthropomimesis in…
• Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework with Agent Team Optimization
  strategic team of agents communicating in a dynamic interaction architecture based on the task query. Specifically, we build a framework named Dynamic LLM-Agent Network (DyLAN) for LLM-agent collabora…
• Enhancing Pipeline-Based Conversational Agents with Large Language Model
  “This paper proposes a hybrid approach that leverages LLMs, in particular GPT-4, to enhance pipeline-based CAs. Using this approach, maintainers of existing CAs can adopt new domains and overcome the …
• Expedient Assistance and Consequential Misunderstanding: Envisioning an Operationalized Mutual Theory of Mind
  Design fictions allow us to prototype the future. They enable us to interrogate emerging or non-existent technologies and examine their implications. We present three design fictions that probe the po…
• Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering
  Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the model to recover in…
• Flows: Building Blocks of Reasoning and Collaborating AI
  “In this work, we argue that everything is a (control) flow defining potentially complex interactions between many diverse tools, where agents are just one type of tool. This induces a paradigm shift …
• Foundations of Large Language Models
  The main part of BERT models is a multi-layer Transformer network. A Transformer layer consists of a self-attention sub-layer and an FFN sub-layer. Both of them follow the post-norm architecture: outp…
• From speaking like a person to being personal: The effects of personalized, regular interactions with conversational agents
  human-AI interactions (Sundar, 2020). Interactions with these agents may have a shorter-term, transactional nature, for example checking the status of an order with a customer service chatbot, or a lo…
• Generative Agent Simulations of 1,000 People
  We present a novel agent architecture that simulates the attitudes and behaviors of 1,052 real individuals—applying large language models to qualitative interviews about their lives, then measuring ho…
• Generative Interfaces for Language Models
  Large language models (LLMs) are increasingly seen as assistants, copilots, and consultants, capable of supporting a wide range of tasks through natural conversation. However, most systems remain cons…
• How well can large language models explain business processes?
  One such system’s functionality is Situation-Aware eXplainability (SAX), which relates to generating causally sound and yet human-interpretable explanations that take into account the process context …
• Large Language Models for User Interest Journeys
  “Large language models (LLMs) have shown impressive capabilities in natural language understanding and generation. Their potential for deeper user understanding and improved personalized user experien…
• Learning Human-Object Interaction as Groups
  Human-Object Interaction Detection (HOI-DET) aims to localize human-object pairs and identify their interactive relationships. To aggregate contextual cues, existing methods typically propagate inform…
• Machine ex machina: A Framework Decentering  the Human in AI Design Praxis
  we propose a framework for decentering the human in AI design. The theoretical principles of HMC and the work of feminist STS scholars are influenced by Bruno Latour’s “actor-network theory” or ANT. …
• Magentic-UI: Towards Human-in-the-loop Agentic Systems
  AI agents powered by large language models are increasingly capable of autonomously completing complex, multi-step tasks using external tools. Yet, they still fall short of humanlevel performance in m…
• Opportunities for large language models and discourse in engineering design
  In this paper, we argue that foundation models such as LLMs can be used for creative reasoning tasks in the engineering design process, complementing and integrating existing computational methods suc…
• Personalization of Large Language Models: A Survey
  Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on persona…
• PosterMate: Audience-driven Collaborative Persona Agents for Poster Design
  PosterMate gathers feedback from each persona agent regarding poster components, and stimulates discussion with the help of a moderator to reach a conclusion. These agreed-upon edits can then be direc…
• Proactive behavior in voice assistants: A systematic review and conceptual model
  Yet, there is a lack of review studies synthesizing the current knowledge on how proactive behavior has been implemented in VAs and under what conditions proactivity has been found more or less suitab…
• ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs
  We hypothesize that cross-domain generalization arises from shared abstract reasoning prototypes — fundamental reasoning patterns that capture the essence of problems across domains. These prototypes …
• Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot
  identity of a conversation partner, as a human or computer, matters. Previous work has found that the mere perceived identity of the partner as computer or human has profound effects, even when actual…
• Rise of Machine Agency: A Framework for Studying the Psychology of Human–AI Interaction (HAII)
  Communication scholars began studying our interactions with the technologies themselves. Several studies documented our tendency to treat computers as if they are autonomous social actors (Reeves & Na…
• See you soon again, chatbot? A design taxonomy to characterize user-chatbot relationships with different time horizons
  Users interact with chatbots for various purposes and motivations – and for different periods of time. However, since chatbots are considered social actors and given that time is an essential componen…
• Simulating Society Requires Simulating Thought
  Simulating society with large language models (LLMs), we argue, requires more than generating plausible behavior; it demands cognitively grounded reasoning that is structured, revisable, and traceable…
• Social Responses to Media Technologies in the 21st Century: The Media are Social Actors Paradigm
  we propose the **Media are Social Actors** (MASA) paradigm as a structured extension of the CASA paradigm. We suggest that an enhanced framework that builds on the CASA paradigm, expounds the effects …
• Social Robots for Long-Term Interaction: A Survey
  Two Paro robots were placed in common living rooms of a care house where elderly residents could interact with the robot over 9 hours a day. The interactions of the residents with PARO were video-reco…
• Systematic synthesis of design prompts for large language models in conceptual design
  Conceptual design can be modeled as a proposition making process, where designers make logical propositions to communicate and construct intangible concepts. Not only can LLMs interpret designers’ pro…
• The Digital Therapeutic Alliance and Human-Computer Interaction
  This conceptual paper explores one such instrument that has been proposed in the literature, the Mobile Agnew Relationship Measure, and examines it through a human-computer interaction (HCI) lens. Thr…
• The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
  Large Language Models (LLMs) have shown promise in accelerating the scientific research pipeline. A key capability for this process is the ability to generate novel research ideas, and prior studies h…
• Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
  Research on LLM agents [68, 69, 82], which are LLM systems capable of exhibiting complex, human-like behaviors to solve tasks, shows these agents2 can yield distinct, believable cognitive and social b…
• Toward Reasonable Parrots: Why Large Language Models Should Argue with Us by Design
  we advocate for the development of conversational technology that is inherently designed to support and facilitate argumentative processes. We argue that, at present, large language models (LLMs) are …
• Towards Algorithmic Experience
  Using a Research through Design methodology supported by interface analysis, document analysis and user design workshops, the present paper provides results grouped in five different areas: algorithmi…
• Towards Human-centered Proactive Conversational Agents
  Recent research on proactive conversational agents (PCAs) mainly focuses on improving the system’s capabilities in anticipating and planning action sequences to accomplish tasks and achieve goals befo…
• Trust in Human-AI Interaction: Scoping Out Models, Measures, and Methods
  Trust has emerged as a key factor in people’s interactions with AI-infused systems. Yet, little is known about what models of trust have been used and for what systems: robots, virtual characters, sma…
• UserBench: An Interactive Gym Environment for User-Centric Agents
  Large Language Models (LLMs)-based agents have made impressive progress in reasoning and tool use, enabling them to solve complex tasks. However, their ability to proactively collaborate with users, e…
• Using Large Language Models to Create AI Personas for Replication and Prediction of Media Effects: An Empirical Test of 133 Published Experimental Research Findings
  Our LLM replications successfully reproduced 76% of the original main effects (84 out of 111), demonstrating strong potential for AI-assisted replication of studies in which people respond to media st…
• Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies
  Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data is not easy, especia…
• Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties
  Human values are crucial to human decision-making. Value pluralism is the view that multiple correct values may be held in tension with one another (e.g., when considering lying to a friend to protect…
• Virtual Assistance in Any Context
  Abstract Several domain-specific assistants in the form of chatbots have conquered many commercial and private areas. However, there is still a limited level of systematic knowledge of the distinctive…
• WHEN TO ACT, WHEN TO WAIT: Modeling Structural Trajectories for Intent Triggerability in Task-Oriented Dialogue
  Task-oriented dialogue systems often face difficulties when user utterances seem semantically complete but lack necessary structural information for appropriate system action. This arises because user…
• What Makes a Good Natural Language Prompt?
  Despite the importance of understanding natural language prompts, there remains limited consensus on how to quantify them. Current approaches rely predominantly on outcome-centric measurements, such a…
• Workplace Everyday-Creativity through a Highly-Conversational UI to Large Language Models
  We explore everyday co-creativity for collaborative human-AI teams in workplaces via a conversational user interface to a large language model. Previous short papers explored human-AI team-creativity …
• Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task
  limitations. This study focuses on finding out the cognitive cost of using an LLM in the educational context of writing an essay. We assigned participants to three groups: LLM group, Search Engine gr…