Latest Articles for Human-Computer Interaction

Developing machines that respond based on emotions for improved human-computer interaction.

New approaches to develop embodied agents for mental health support using context-sensitive smiles.

Learn how data-to-text generation makes complex information easier to understand.

A new system reduces false activations in myoelectric control using simple gestures.

Researching how AI can understand human thoughts and feelings.

An analysis of the qualities and challenges of language model explanations.

This article examines bias in language models and their emotional alignment with different social groups.

Research reveals significant biases in human and LLM evaluations of responses.

A new method enhances data gathering for better language model alignment.

A study reveals gaps in LLMs' understanding of logic rules compared to humans.

A look at the potential and challenges of neuromorphic sensors for face analysis.

A new method improves alignment of LLMs with minimal human feedback.

A new benchmark, EmoBench, tests emotional intelligence in language models.

The AEA dataset provides insights into daily activities for improving AI and AR technologies.

Introducing Video ReCap, a system for creating detailed captions for long videos.

New dataset aims to enhance machine understanding of touch through vision and language.

Discover how SER enhances human-machine interactions through emotion detection.

A new framework aims to improve AI's empathetic responses in conversations.

A method to help AI adapt while retaining past knowledge.

Introducing BeTAIL, a new method for improving robot racing through imitation learning.

A new method enhances how language models select and use tools effectively.

BEE-NET enhances emotion recognition by considering body language and environmental context.

Coco-Nut offers diverse Japanese voice samples for advanced text-to-speech applications.

Improving precision in hand-object tracking with GeneOH Diffusion.

New methods promise better AI model performance through simplified reinforcement learning.

Research reveals how gestures can enhance safety for pedestrians and self-driving cars.

An overview of ethical processes in the Cat Royale research project.

Examining synchronization, communication, and sensory cues in human-robot collaboration.

AffectToolbox simplifies emotion analysis for researchers and users alike.

New methods enhance how agents learn to cooperate and communicate effectively.

Analyzing the effects of reasoning methods on large language models' performance.

An adaptive agent improves teamwork in Codenames using multiple language models.

Combining RGB and Depth data improves action recognition in robotic systems.

A system that enhances AI-generated navigation instructions by detecting errors and offering corrections.

A study comparing GPT-4 and crowdsourcing in data labeling tasks.

New benchmark assesses LLMs' skills in interacting with multiple agents.

Research reveals broader ways to deliver directions using spatial knowledge.

This survey reviews recent developments in multi-turn dialogue systems leveraging large language models.

Study reveals challenges and progress in chatbot memory during lengthy dialogues.

New dataset enhances computer agents' ability to perform various tasks.