Search Results for author: Hadas Kotek

Found 4 papers, 0 papers with code

Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out

no code implementations17 Mar 2023 Zidi Xiu, Kai-Chen Cheng, David Q. Sun, Jiannan Lu, Hadas Kotek, Yuhan Zhang, Paul McCarthy, Christopher Klein, Stephen Pulman, Jason D. Williams

Next, we expand the time horizon to examine behavior changes and show that as users discover the limitations of the IA's understanding and functional capabilities, they learn to adjust the scope and wording of their requests to increase the likelihood of receiving a helpful response from the IA.

MMIU: Dataset for Visual Intent Understanding in Multimodal Assistants

no code implementations13 Oct 2021 Alkesh Patel, Joel Ruben Antony Moniz, Roman Nguyen, Nick Tzou, Hadas Kotek, Vincent Renkens

In multimodal assistant, where vision is also one of the input modalities, the identification of user intent becomes a challenging task as visual input can influence the outcome.

intent-classification Intent Classification +4

Improving Human-Labeled Data through Dynamic Automatic Conflict Resolution

no code implementations COLING 2020 David Q. Sun, Hadas Kotek, Christopher Klein, Mayank Gupta, William Li, Jason D. Williams

This paper develops and implements a scalable methodology for (a) estimating the noisiness of labels produced by a typical crowdsourcing semantic annotation task, and (b) reducing the resulting error of the labeling process by as much as 20-30% in comparison to other common labeling strategies.

text-classification Text Classification

Generating Natural Questions from Images for Multimodal Assistants

no code implementations17 Nov 2020 Alkesh Patel, Akanksha Bindal, Hadas Kotek, Christopher Klein, Jason Williams

We evaluate our approach using standard evaluation metrics such as BLEU, METEOR, ROUGE, and CIDEr to show the relevance of generated questions with human-provided questions.

Common Sense Reasoning Natural Questions +4

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