Latest Articles for Human-Computer Interaction

Study examines how robotic coaches communicate mental well-being support.

A new approach enhances human experiences in gaming through AI collaboration.

CompAgent improves image creation from text by breaking down complex prompts.

Examining the challenges and opportunities in understanding LLMs.

This research explores how altered feedback enhances sEMG gesture classification learning.

A method for better gesture recognition using muscle signals.

This article discusses training machines to ask for clarification when instructions are unclear.

Exploring new ways to categorize inaccuracies in language models for better understanding.

A method to improve facial expression recognition by focusing on facial movements.

A fresh method for machines to alter speech emotions naturally.

This paper discusses adjusting language models to align with human values and expectations.

A new method focuses on relevance to enhance language model responses.

Discover how agents can improve foundation models for better AI outcomes.

New method preserves emotional tone in voice conversion for better human-computer interaction.

KTO simplifies AI training by focusing on human preferences efficiently.

Research on how prompt reformulation affects user satisfaction with language models.

Examining machine and human reasoning in language processing tasks.

A new framework enhances LLMs' decision-making by leveraging past experiences.

A platform for AI agents to interact with real environments using geospatial data.

DeRa offers a method to adjust language model alignment without retraining.

NORMY framework enhances conversational QA by improving retrieval and understanding of context.

Examining how generative agents can improve emotional understanding.

This study compares human and machine object recognition abilities in unusual poses.

Study reveals how LLMs adapt learning based on feedback during tasks.

This study reveals how to align robot voices with their designs effectively.

A new approach streamlines hand motion adaptation for various applications.

Introducing ScreenAgent, an innovative AI for managing computer tasks effectively.

Examining AI's potential to improve UX practices and the current challenges faced.

A new method to spark creativity in problem-solving through AI support.

Exploring issues in creating decision-making AI models and solutions.

Developing algorithms to improve reinforcement learning using human feedback despite data corruption.

Research highlights the role of uncertainty in asking clarification questions in dialogue systems.

Exploring feedback loops in language models and their unintended consequences.

A new model enhances understanding of emotions during conversations.

New methods enhance how machines learn to follow human commands effectively.

A new approach to align agents with human goals and surroundings.

Using images to clarify user queries enhances search results and user experience.

New methods improve how we assess computer-generated text.

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.