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Record W2913646321

Proceedings of the 15th international conference on Intelligent user interfaces

2010· article· en· W2913646321 on OpenAlexaboutno aff
Charles Rich, Qiang Yang, Marc Cavazza, Michelle X. Zhou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech and dialogue systems
Canadian institutionsnot available
Fundersnot available
KeywordsRebuttalComputer scienceTransparency (behavior)Relevance (law)Presentation (obstetrics)User interfaceWorld Wide WebPolitical science
DOInot available

Abstract

fetched live from OpenAlex

IUI has successfully established itself as a unique, interdisciplinary conference, at the intersection of Artificial Intelligence and Human-Computer Interaction. The Conference receives contributions from many traditional as well as hot topics in the field, ranging from Multimodal Interfaces and Recommender Systems, to Affective Computing and Brain-Computing Interfaces. Because of this ever-increasing diversity of topics, this edition has seen further changes to our reviewing process. We have introduced a rebuttal phase for Long Papers, following a trend adopted by several high-quality conferences. The objective of the rebuttal is to ensure greater transparency and fairness, as the authors' responses should influence the discussion phase moderated by a Senior Program Committee (SPC) member. In order to ensure that all topics were adequately covered over 200 reviewers have contributed to the selection of this year's program and we trust that this had a very positive impact on the relevance and quality of individual reviews. We have retained the successful format of the conference with Long Papers, Short Papers and Demonstrations. In addition, we have addressed the issue of conversion of Long Papers into Short Papers by explicitly requesting authors' approval at submission time. The accepted submissions cover a wide range of topics, including personalized information systems, intelligent user interaction for information search and browsing, affective computing, gesture-based systems, and multimodal user interfaces. Geographically, the accepted work also represents researchers and institutions in many countries across four continents, including China, Japan, Korea, Singapore, Canada, Netherlands, Ireland, France, Germany, Australia, New Zealand, United Kingdom, and the United States of America. As always, the selection process has been the object of careful consideration and multiple discussions. We have asked the SPC moderators to formulate recommendations for acceptance and in the vast majority of cases it has been straightforward for us to endorse their choice. It is always down to the Program Chairs to make final decisions, sometimes difficult ones, on the total number of papers to be accepted. We have adopted a continuity policy from previous editions (around 22% for Long Papers), this year's overall acceptance rate achieves the right balance between selectivity and openness to innovative papers. The conference program highlights two invited talks: Paul Sajda, from Columbia University and Kazuo Yano, from Hitachi's Advanced Research Laboratory. This year's Conference will also feature five full-day and one half-day workshops, covering several hot topics in the area of IUI, with strong emphasis on semantics, social aspects and multimodality of interfaces, including: Social Recommender Systems Intelligent Visual Interfaces for Text Analysis Multimodal Interfaces for Automotive Applications Interoperability and Interaction on the Social and Semantic Web Eye Gaze in Intelligent Human Machine Interaction Semantic Models for Adaptive Interactive Systems The demonstration program accepted fifteen regular submissions. We would like to thank Tyler Baldwin and Brian Romanowski for their help in organizing the demo session.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.258
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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