This study analyzes ClinicalTrials.gov records to track the rising trend of AI in clinical trials and demonstrates that a hybrid human-AI screening approach is viable but requires clearer reporting of…

This paper proposes an efficient human intervention mechanism, Deep Interaction, for correcting reasoning errors in large language models, achieving over 25% improvement in correction success rate and…

This paper proposes a taxonomy of interaction requirements for human-AI interaction in public sector ICT procurement to ensure ethical compliance and sustainable value realization.

This study investigates human-AI collaboration in question answering, finding that while collaboration is beneficial, humans make suboptimal decisions by both under-relying on correct AI suggestions a…

This paper proposes shifting the focus of AI research from isolated computational outputs to interaction dynamics, establishing 'Interaction-Centered Intelligence' as the primary framework for underst…

This paper identifies and validates eight core UX principles for human-AI agent interaction in the workplace using a multi-method approach.

This paper introduces a human-AI collaborative decision-making framework, called Human-Centric Reflective Architecture (HCRA), to enhance effectiveness and align AI agents with human preferences using…

This study compared LLM-based conversational interfaces and traditional dashboards for industrial decision tasks, finding that while conversational agents reduce interactional effort, dashboards remai…

The paper introduces Rationalize, a role-pair framework that facilitates shared semantic reasoning between humans and AI models to achieve deep alignment of intent and action.

The XAIxArts workshop explores the operationalisation of Explainable AI in the Arts, focusing on diversity, ideation, and resource development.

A study evaluating a Retrieval-Augmented Generation system for making Quebec automobile insurance contracts more understandable, showing it improves satisfaction, trust, and clarity, especially for in…

The paper introduces Clover, a code completion tool that logs students' interactions and offers attention checks to promote reflective engagement during programming tasks.

This paper introduces a controlled, two-player extension of the Alternate Uses Test (AUT) for comparing human-human and human-AI co-creation under matched conditions, demonstrating equivalent original…

This paper discusses the misalignment between current AI goals and the needs of creators in fields like structural design, and proposes a conversational, multimodal, and responsive AI system for const…

Two student cohorts designed cognitively accessible GenAI interfaces, leading to structural and experiential scaffolding concepts.

This paper proposes conversational AI review assistants for code review, systems that engage in conversation with developers instead of just generating comments.

The paper introduces an ontology-driven framework, From Prompts to Context, to explicitly model and structure the often-opaque context of human-Generative AI collaborations, thereby improving traceabi…

The paper proposes Agentic ASR, a closed-loop framework that treats ASR as a multi-turn refinement task, significantly improving semantic accuracy over traditional token-level metrics.

The paper introduces DigitalCoach, a dataset of human expert-novice computer use coaching sessions, and evaluates the ability of state-of-the-art models to teach humans how to use computers.

This paper investigates how the final prompt in conversational AI-search evaluations differs from the conversation history, using two corpora of commercial and PRISM conversations.