Latest Articles for Human-Computer Interaction

TEMPO enhances pose estimation by tracking and predicting movements in real-time.

A new framework aims to clarify AI decision-making for humans.

A new method improves accuracy in head pose estimation across diverse orientations.

O-1 improves speech recognition by optimizing self-training methods.

Machines learn from experts to adapt to unpredictable environments.

A look into the challenges and opportunities of LLMs in healthcare language tasks.

New model enables robots to communicate more naturally using gestures.

RenderIH dataset improves accuracy in understanding human hand interactions.

A new system aligns gestures with speech for enhanced communication.

New methods improve alignment of language models with human values.

This study evaluates methods to enhance parsing of contextual utterances using limited data.

Study reveals insights on emotional perception in robots and their digital counterparts.

AffectEcho model enhances emotional expression in AI-generated speech.

A study on how LLMs make decisions in social dilemmas.

Discover the evolution of AI handling multiple data types.

Syndicom enhances dialogue responses using commonsense reasoning and natural language feedback.

A new method improves how tech detects human behavior in group settings.

A new dataset enhances 3D modeling of hands holding objects from videos.

A new framework aims to enhance response quality in dialogue systems.

New methods for retrieving UI designs and ensuring consistency across mobile apps.

AVMIT offers researchers insights into how sound and vision relate in action recognition.

This study tests new methods for assessing image descriptions against human opinions.

Examining the separation of pose and appearance in recent techniques.

This study connects presence and reaction time in Mixed Reality.

A new method improves image creation of groups without per-scene adjustments.

This article discusses using natural language to aid computer learning in complex tasks.

Exploring the need for safety and trust in AI systems.

Examining the reasoning abilities of instruction-tuned language models.

New methods improve machines' ability to recognize emotions in dialogues.

A new method enhances language models' understanding of conversations.

This paper examines the limitations of in-context learning in language models.

A new approach enhances text generation by focusing on harmful patterns.

This study advances how language models identify visual references in dialogue.

Examining the role of AI in qualitative coding and its impact on user trust.

Study reveals the connection between eye movements and visual attention in primates and humans.

Examining the Winograd Schema Challenge and its implications for AI understanding.

A new dataset to enhance understanding of human-object interactions in industrial settings.

Research on a manager agent for effective task delegation among humans and AI.

An overview of how machines process text, images, and audio.

HuntGPT improves threat detection with a user-friendly interface and explainable AI.