Papers by Eugen Ruppert

3 papers
Modeling Referential Gaze in Task-oriented Settings of Varying Referential Complexity (2022.findings-aacl)

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Challenge: Referential gaze is a fundamental phenomenon for psycholinguistics and human-human communication.
Approach: They propose a multimodal NLP task to predict when the gaze is referential . they train a sequential attention-based LSTM model and a transformer encoder architecture to model referential gaze and transfer gaze features to unseen situated settings .
Outcome: The proposed model can be applied to situations with different referential complexities . the proposed model is based on an attention-based LSTM model and a multivariate transformer encoder architecture .
Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl (L18-1)

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Challenge: DepCC is the largest-to-date linguistically analyzed corpus in English . large corpora are essential for the modern data-driven approaches to natural language processing .
Approach: They present a large-to-date linguistically analyzed corpus in English with 365 million documents . they build an index of all sentences and their linguistic meta-data enabling quick search across the corpus .
Outcome: The proposed model outperforms state-of-the-art models on smaller corpora on the SimVerb3500 dataset.
Eye4Ref: A Multimodal Eye Movement Dataset of Referentially Complex Situations (2020.lrec-1)

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Challenge: Eye4Ref is a rich multimodal dataset of eye-movement recordings from referentially complex situated settings.
Approach: They present a rich multimodal dataset of eye-movement recordings from situated settings . they use linguistic labels, saccadic movement parameters and symbolic knowledge representations .
Outcome: The Eye4Ref dataset is an annotated multimodal dataset from three eyetracking studies on reference resolution and disambiguation tasks in situated settings.

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