Proceedings of the 21st International Conference on Intelligent User Interfaces
Bibliographic record
Abstract
It is with great pleasure that we welcome you to beautiful Sonoma, California and the 21st edition of ACM International Conference on Intelligent User Interfaces -- ACM IUI 2016. ACM IUI is HCI meets AI, or where the academic research communities of Human-Computer Interaction (HCI) and Artificial Intelligence (AI) intersect. As the premier international forum for reporting outstanding research and development on intelligent user interfaces, the conference welcomes submissions describing work at the cross-section of these two fields and other related fields, such as psychology, behavioral science, cognitive science, computer graphics, design, the arts, and many others. Members of the ACM IUI community are interested in improving the symbiosis between humans and computers, increasing the intelligence of both in the process. The call for papers attracted 194 long and short paper submissions, 31 poster paper submissions, 11 demo paper submissions, and 17 student consortium submissions. The final program of the conference includes 2 keynotes, 49 long and short papers (25.3% acceptance rate), 15 posters, 6 demos, 2 workshops, 1 tutorial, and 12 student consortium papers. We are particularly excited for the keynotes by two distinguished speakers that will open the first and third days of the conference. The opening keynote will be given by Xavier Amatriain, VP of Engineering at Quora, on the topic of the Past, Present, and Future of Recommender Systems: An Industry Perspective. The closing keynote will be given by Professor Elisabeth Andre, from Augsburg University and a long-time member of the ACM IUI community, on the topic of Socially-Sensitive Interfaces: From Offline Studies to Interactive Experiences. The conference could not be organized without the help of a large number of individuals who generously volunteered much of their own time. Their names can be found on the following pages. All of the members of the organizing committee have done a fantastic job of coordinating the many moving parts that go into putting on a great conference. We must also particularly thank our 34 senior program committee members for coordinating the papers review process and the 91 members of the program committee for providing high quality reviews. And, most important, we must thank the authors for their diligent work that resulted in so many great submissions. These have allowed us to develop the excellent program that is the enduring heart of the conference. Another key for any great conference is a collection of strong sponsor organizations and generous corporate supporters. Our sponsors ACM, SIGAI, and SIGCHI are instrumental in making the conference happen year in and year out. This year, SIGCHI and SIGAI were particularly generous in providing financial support for our student travel grants, which have enabled 19 students to attend the conference that might not have otherwise. Our corporate supporters, Microsoft, IBM, Google, and Tableau have been supremely generous and the conference would be weaker without their contributions. We hope you will find the program engaging and the mix of academic disciplines broadens your perspective on computing. We also hope the conference will provide you with a valuable opportunity to share ideas with other researchers and practitioners from around the world, whether through presenting your own work formally or through informal discussions during the banquet or coffee breaks. With luck, those shared ideas will manifest themselves in exciting papers at next year's conference and ultimately have impact far beyond the conference! If you have any suggestions for how to improve the conference either this year or in the future, please do not hesitate to let us know.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.134 | 0.068 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".