United States

2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics.

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NAACL 2021

To effectively apply robots in working environments and assist humans, it is essential to develop and evaluate how visual grounding (VG) can affect machine performance

OCID-Ref: A 3D Robotic Dataset With Embodied Language For Clutter Scene Grounding

technical paper

Limitations of Autoregressive Models and Their Alternatives

On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies

Nutribullets Hybrid: Multi-document Health Summarization

AVA: an Automatic eValuation Approach for Question Answering Systems

SpanPredict: Extraction of Predictive Document Spans with Neural Attention

Text Editing by Command

A Deep Metric Learning Approach to Account Linking

Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation

MIMOQA: Multimodal Input Multimodal Output Question Answering

Multimodal End-to-End Sparse Model for Emotion Recognition

https://d3smihljt9218e.cloudfront.net/transcript/13372/subtitle/8215b9088a3e965d662908dc842cbc42.vtt

English (automatic)

OCID-Ref: A 3D Robotic Dataset With Embodied Language For Clutter Scene Grounding

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Next from NAACL 2021

Limitations of Autoregressive Models and Their Alternatives

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