Selected Talks

2023

• Panel Discussion: AI’s Impact on Technology, Research and Education May 16 2023: Panelist at the Workshop on AI’s impact on Society and Advancements in Technology, Microsoft Research
• Training data for Large Language Models: how can we collect it ethically and study it?
  May 2 2023: Invited talk at the Linguistic Circle of Copenhagen
• “Writing Assistance or PlagAIrism? How Language Models Are Changing Our View of Knowledge
  April 29 2023: Invited talk at the Complexity of Knowledge symposium (Santa Fe Institute)
• Machine Reading, Fast and Slow: When Do Models “Understand” Language?
  April 24 2023: Invited talk at the AI and the Barrier of Meaning seminar (Santa Fe Institute)
• Data governance and transparency for Large Language Models: lessons from 🌸 BigScience Workshop
  March 30 2023: Invited talk at the AI UK Fringe (Queen’s University Belfast, online)
• Data governance and transparency for Large Language Models: lessons from 🌸 BigScience Workshop
  February 16 2023: Invited talk at the Institute for Advanced Sociology (Linköping Uni), [SLIDES]

2022

• When does a machine “understand” what it “reads”? September 9 2022: Keynote at the 25th International Conference on Text, Speech and Dialogue (TSD), [SLIDES]
• What kinds of questions have we been asking? A taxonomy for QA/RC benchmarks July 14 2022: invited talk at the The First Workshop on Dynamic Adversarial Data Collection (DADC), [SLIDES]
• Defining and testing reading comprehension “skills”
  July 4 2022: invited talk at the Workshop on Ten Years of BabelNet and Multilingual Neurosymbolic Natural Language Understanding, [SLIDES]
• When does a machine “understand” what it “reads”?
  June 17 2022: keynote at CLIN 2022, Tilburg, Netherlands
• When does a machine “understand” what it “reads”?
  April 29 2022: invited talk at the University of Edinburgh
• Challenges in defining and testing machine verbal reasoning skills
  11 April 2022: invited talk at AMORE Mini-workshop on Referential Information in Deep Learning Models (Universistat Pompeu Fabra, Barcelona)
• Challenges in defining and testing machine verbal reasoning skills
  31 March 2022: invited talk at Stanford NLP Group, [SLIDES]
• Case Studies in BERTology: shallow heuristics or verbal reasoning?
  14 February 2022: invited talk at Oslo Language Technology Group, [SLIDES]

2021

• BERTology nuggets
  15 December 2021: invited talk at London Machine Learning Meetup, [SLIDES]
• The Peer Review Process and Widening NLP
  11 November 2021: Panel with Bahar Mehmani and Cecilia Superchi at Widening NLP (co-located with EMNLP 2021)
• Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics
  10 November 2021: presentation at Workshop on Insights from Negative Results co-located with EMNLP 2021
• Just what do you think you’re doing, Dave?
  10 November 2021: presentation at NLLP workshop co-located with EMNLP 2021
• Changing the world by changing the data
  09 November 2021: invited talk at Data-centric AI Day (France is AI) [SLIDES]
• What we know about how BERT works
  
• 27 October 2021: invited talk at Technical University of Denmark, [SLIDES]
• Panel Discussion on Trustworthy NLP (Google)
  13 October 2021: Panel with Kellie Webster and Hannach Wallach at Google’s Trustworthy NLP Workshop
• Changing the world by changing the data
  21 September 2021: invited talk at Machine Learning for NLP (Toronto ML Series) [SLIDES]
• Changing the world by changing the data
  3 August 2021: oral talk at ACL 2021 [SLIDES]
• Reviewing Natural Language Processing research.
  29 June 2021: tutorial at TALN 2021 (with Kevin Cohen, Karën Fort, Margot Mieskes and Aurélie Névéol)
• A primer in BERTology: what we know about how BERT works
  June 17 2021: invited talk at L3-AI [SLIDES]
• A primer in BERTology: what we know about how BERT works
  June 8 2021: presentation at NAACL 2021 [SLIDES]
• The quest for difficult benchmarks in question answering and reading comprehension.
  7 May 2021: invited talk at LTI Colloquium at Carnegie Mellon University [URL] [SLIDES]
• Reviewing Natural Language Processing research.
  20 April 2021: tutorial at EACL 2021 (with Kevin Cohen, Karën Fort, Margot Mieskes and Aurélie Névéol)

2020

• A guide to the dataset explosion in QA, NLI, and commonsense reasoning.
  13 Dec 2020: Tutorial at COLING 2020 (online). [URL] [SLIDES]
• When BERT plays the lottery, all tickets are winning.
  20 Nov 2020: invited talk at BlackBox NLP (online). [URL]
• How Much Should Conversational AI Developers know about ML and Linguistics?
  16 Jun 2020: The Level 3 AI Assistant Conference, panel discussion with Emily M. Bender, Thomas Wolf, and Vladimir Vlasov (online). [URL]
• The questions that the current AI can’t answer
  8 Feb 2020: Evaluating Evaluation of AI Systems (Workshop co-located with AAAI 2020, New York, USA). [SLIDES]

2019

• Towards AI Complete Question Answering: Combining Text-based, Unanswerable and World Knowledge Questions
  11 December 2019: Allen Institute for Aritficial Intelligence (Seattle, USA).
• Text Representations Learning and Compositional Semantic (ACML 2019 tutorial)
  November 17 2019: Nagoya, Japan [URL]
• The dark secrets of BERT
  11 November 2019: RIKEN Center for Computational Science (Tokyo, Japan).
• Word embeddings: 6 years later
  22 May 2019: UMass Amherst (USA). [SLIDES]

2018

• What’s in your embedding, and how it predicts task performance.
  27 September 2018: UMass Amherst (USA). [SLIDES], [VIDEO].
  A version of this talk was also presented on August 30 2018 at IT University of Copenhagen (Denmark).
• Distributional compositional semantics in the age of word embeddings.
  7 May 2018: Tutorial at LREC 2018, Miyazaki, Japan. [URL]
• Detecting linguistic relations with analogies: what works and what doesn’t.
  July 15 2016: Google Tokyo seminar, Tokyo, Japan. [SLIDES]