---
res:
  bibo_abstract:
  - How information is created, shared and consumed has changed rapidly in recent
    decades, in part thanks to new social platforms and technologies on the web. With
    ever-larger amounts of unstructured and limited labels, organizing and reconciling
    information from different sources and modalities is a central challenge in machine
    learning. This cutting-edge tutorial aims to introduce the multimodal entailment
    task, which can be useful for detecting semantic alignments when a single modality
    alone does not suffice for a whole content understanding. Starting with a brief
    overview of natural language processing, computer vision, structured data and
    neural graph learning, we lay the foundations for the multimodal sections to follow.
    We then discuss recent multimodal learning literature covering visual, audio and
    language streams, and explore case studies focusing on tasks which require fine-grained
    understanding of visual and linguistic semantics question answering, veracity
    and hatred classification. Finally, we introduce a new dataset for recognizing
    multimodal entailment, exploring it in a hands-on collaborative section. Overall,
    this tutorial gives an overview of multimodal learning, introduces a multimodal
    entailment dataset, and encourages future research in the topic.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Cesar
      foaf_name: Ilharco, Cesar
      foaf_surname: Ilharco
  - foaf_Person:
      foaf_givenName: Afsaneh
      foaf_name: Shirazi, Afsaneh
      foaf_surname: Shirazi
  - foaf_Person:
      foaf_givenName: Arjun
      foaf_name: Gopalan, Arjun
      foaf_surname: Gopalan
  - foaf_Person:
      foaf_givenName: Arsha
      foaf_name: Nagrani, Arsha
      foaf_surname: Nagrani
  - foaf_Person:
      foaf_givenName: Blaž
      foaf_name: Bratanič, Blaž
      foaf_surname: Bratanič
  - foaf_Person:
      foaf_givenName: Chris
      foaf_name: Bregler, Chris
      foaf_surname: Bregler
  - foaf_Person:
      foaf_givenName: Christina
      foaf_name: Liu, Christina
      foaf_surname: Liu
  - foaf_Person:
      foaf_givenName: Felipe
      foaf_name: Ferreira, Felipe
      foaf_surname: Ferreira
  - foaf_Person:
      foaf_givenName: Gabriek
      foaf_name: Barcik, Gabriek
      foaf_surname: Barcik
  - foaf_Person:
      foaf_givenName: Gabriel
      foaf_name: Ilharco, Gabriel
      foaf_surname: Ilharco
  - foaf_Person:
      foaf_givenName: Georg F
      foaf_name: Osang, Georg F
      foaf_surname: Osang
      foaf_workInfoHomepage: http://www.librecat.org/personId=464B40D6-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Jannis
      foaf_name: Bulian, Jannis
      foaf_surname: Bulian
  - foaf_Person:
      foaf_givenName: Jared
      foaf_name: Frank, Jared
      foaf_surname: Frank
  - foaf_Person:
      foaf_givenName: Lucas
      foaf_name: Smaira, Lucas
      foaf_surname: Smaira
  - foaf_Person:
      foaf_givenName: Qin
      foaf_name: Cao, Qin
      foaf_surname: Cao
  - foaf_Person:
      foaf_givenName: Ricardo
      foaf_name: Marino, Ricardo
      foaf_surname: Marino
  - foaf_Person:
      foaf_givenName: Roma
      foaf_name: Patel, Roma
      foaf_surname: Patel
  - foaf_Person:
      foaf_givenName: Thomas
      foaf_name: Leung, Thomas
      foaf_surname: Leung
  - foaf_Person:
      foaf_givenName: Vaiva
      foaf_name: Imbrasaite, Vaiva
      foaf_surname: Imbrasaite
  bibo_doi: 10.18653/v1/2021.acl-tutorials.6
  dct_date: 2021^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/9-781-9540-8557-2
  dct_language: eng
  dct_publisher: Association for Computational Linguistics@
  dct_title: Recognizing multimodal entailment@
...