How Hugging Face Accelerated Development of Witty Works Writing Assistant

Playful AI in Professional Email: A Field Experiment on Tone and Recipient Engagement

arXiv:2607. 11749v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly reshaping workplace communication, yet whether AI-assisted writing changes how recipients actually behave, and through what channel, remains unknown.

Interaction Techniques that Encourage Longer Prompts Can Improve Psychological Ownership when Writing with AI

arXiv:2507. 03670v2 Announce Type: replace-cross Abstract: Writing longer prompts for an AI assistant to generate a story increases psychological ownership, a user's feeling that the writing belongs to them.

Designing Proactive Thought Partners for Writing

Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promises to provide the right support at the right time,...

Nonslop: A Gamified Experiment in Human-AI Collaborative Writing

arXiv:2606. 12350v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) raises critical questions about human creativity and individual expression in an era of AI-assisted creation.

Sentence Transformers in the Hugging Face Hub

Towards Cognitive Process-Aware Proactive Writing Support

The paper proposes a proactive writing support system that infers users’ needs from their writing interactions, using Flower and Hayes’ cognitive process theory as a framework. By mapping six cognitive processes to 14 specific support types and associated interaction behaviors, the authors develop AToM CoWriter, which offers context-aware suggestions without requiring explicit prompts. Two within-subjects studies with 21 participants show that this approach improves expressiveness, idea exploration, and engagement with proactive suggestions.