PLeW-NLG: Interactive Exploration of Human Evaluation Data across NLG Tasks
Published in INLG 2026 (Demo Track), 2026
2nd author. Accepted demo paper.
Note: full author list, exact publication date, and paper URL are not yet public — update this entry once the camera-ready version is released.
Recommended citation: Full author list not yet public as of this writing (INLG 2026 camera-ready due September 7, 2026; conference October 17–21, 2026).
Learning thrives on engagement. Engagement manifests from value recognition. Value is found and evolves through dialogue. In the face of an upswelling AI presence that threatens to bypass genuine engagement, we must reimagine how we connect by crafting dialogues that acknowledge both the possibilities and pitfalls of AI within our learning environments. Len is a chemist-turned-consultant working at the intersection of AI and higher education.
Curriculum vitae →