Latest Articles for Human-Computer Interaction

New strategies improve learning efficiency without frequent resets.

This paper examines how LLMs express confidence in their answers.

Soda-Eval sets new standards for chatbot evaluation methods.

Examining the partnership between humans and robots in challenging environments.

Research shows people prefer larger bounding boxes in object detection.

A look into shared control systems for improved robot-user interaction.

This framework enhances forecasting accuracy using language models and real-time data.

Preference-based learning improves decision-making by using expert feedback.

StyleSpeech advances TTS systems by capturing natural speech nuances.

EMO-LLaMA improves emotional AI by enhancing facial expression recognition.

A new AR system enhances teamwork between humans and robots through gaze control.

A new method improves how robots learn from human preferences.

A new method automates concept generation to improve AI decision transparency.

AI is reshaping how music is composed and experienced.

Research aims to improve models of finger movement for enhanced robotic design.

A new method improves emotion recognition in conversations using multiple data sources.

A novel approach to track interactions without templates.

This research enhances hand gesture recognition using electromyography for better accessibility.

New methods improve the quality of speech synthesis in TTS systems.

This study examines how users' mental models affect their interactions with task-oriented dialog systems.

This study presents a model to analyze emotional reactions to video content.

Researchers enhance gesture recognition using innovative learning techniques.

This article discusses the benefits of merging voice and facial recognition systems.

A new method streamlines aligning language models with human preferences.

A new model enhances speech recognition by combining audio and visual inputs effectively.

Evaluating how multimodal LLMs can control Atari video games.

A new method enhances 3D pose estimation in complex environments.

This study enhances action recognition by merging depth maps with RGB video frames.

A new framework to enhance language models using real-time user interactions.

A new approach improves action detection in videos by tackling attention collapse.

Study reveals the impact of verbal and nonverbal cues in user interactions with VAs.

A new benchmark aids in assessing speech tokenizers for better performance.

Improving how machines assist users through better interaction and response measures.

New methods improve facial expression recognition using one-frame calibration techniques.

TIM offers new methods for generating realistic human interactions in motion.

A novel approach improves gaze estimation accuracy using multiple datasets.

This article presents a new method for realistic dialogue systems using user-specific traits.

A new method integrates human input to enhance OOD learning for machine learning models.

Exploring the intersection of human feedback and multi-agent systems for better collaboration.

This study evaluates how well VLMs can understand visual perspectives.