Latest Articles for User Interaction

PMixED improves privacy without sacrificing performance in large language models.

A new method shows language models can ask better questions for clearer responses.

Research shows multiple queries enhance systems for better information retrieval.

SPHINX-V enhances AI's ability to interpret images through user interaction.

A new method enhances avatar speech through natural movements and expressions.

Examining tactile methods for simulating weight in virtual spaces.

A study on the effectiveness of ULTR techniques for search ranking improvements.

Exploring the need for explainable AI in generative systems.

A look into how visualizations can respond to user focus.

A new method simplifies AI model explanations using expert-driven concepts.

Connecting users to important information in everyday scenarios through innovative systems.

Strategies to reduce overly cautious behavior in language models.

Addressing contradictions in AI dialogues for better communication.

Examining fairness and ethics of how language models respond to users.

This system provides a scalable environment to test autonomous agents across real-world Android applications.

FocSAM enhances interactive segmentation with improved stability and accuracy.

Explore how large language models enhance creativity through multimedia generation.

A new method improves facial expression recognition by using language models.

Learn how MOFA-Video transforms still images into engaging animations.

A tool that creates images from user conversations through multiple agents.

A look at uncertainty types and their importance in language models.

Exploring the self-correction processes in language models and their effects.

LLplace simplifies 3D layout design using natural language input.

Examining the risks and safety measures in fine-tuning language models.

This study examines how gestures affect learning from virtual agents.

Introducing RePrompt for better language model performance through optimized prompts.

User traits influence the responses of language models and their safety.

Evaluating how language models handle cultural cues in real tasks.

New models offer clear insights for text predictions without extensive labeling.

Enhancing user engagement in large vision-language models through proactive communication.

TraceNet improves mobile image segmentation with user-friendly, efficient processes.

Crepe empowers researchers to collect mobile screen data easily.

Exploring methods to enhance LLMs for practical applications.

Examining how user movement affects wireless connections in XR applications.

Learn about the importance of safety measures in language models.

Introducing a tool to enhance safety in language model interactions.

Developing chatbots that learn actively during user interactions.

A new method improves user prompts for safer and more effective language model outputs.

Exploring the impact of TTM models on music creation and user experiences.

Examining the trade-off between predicting text and user-driven actions in language models.