NLP Highlights podcast

134 - PhD Application Series: PhDs in Europe versus the US

0:00
38:29
Recuar 15 segundos
Avançar 15 segundos
This episode is the second in our current series on PhD applications. How do PhD programs in Europe differ from PhD programs in the US, and how should people decide between them? In this episode, we invite Barbara Plank (Professor at ITU, IT University of Copenhagen) and Gonçalo Correia (ELLIS PhD student at University of Lisbon and University of Amsterdam) to share their perspectives on this question. We start by talking about the main differences between pursuing a PhD in Europe and the US. We then talk about the application requirements for European PhD programs and factors to consider when deciding whether to apply in Europe or the US. We conclude by talking about the ELLIS PhD program, a relatively new program for PhD students that facilitates collaborations across Europe. ELLIS PhD program: https://ellis.eu/phd-postdoc (Application Deadline: November 15, 2021) Homepages: - Barbara Plank: https://bplank.github.io/ - Gonçalo Correia: https://goncalomcorreia.github.io/

Mais episódios de "NLP Highlights"

  • NLP Highlights podcast

    134 - PhD Application Series: PhDs in Europe versus the US

    38:29

    This episode is the second in our current series on PhD applications. How do PhD programs in Europe differ from PhD programs in the US, and how should people decide between them? In this episode, we invite Barbara Plank (Professor at ITU, IT University of Copenhagen) and Gonçalo Correia (ELLIS PhD student at University of Lisbon and University of Amsterdam) to share their perspectives on this question. We start by talking about the main differences between pursuing a PhD in Europe and the US. We then talk about the application requirements for European PhD programs and factors to consider when deciding whether to apply in Europe or the US. We conclude by talking about the ELLIS PhD program, a relatively new program for PhD students that facilitates collaborations across Europe. ELLIS PhD program: https://ellis.eu/phd-postdoc (Application Deadline: November 15, 2021) Homepages: - Barbara Plank: https://bplank.github.io/ - Gonçalo Correia: https://goncalomcorreia.github.io/
  • NLP Highlights podcast

    133 - PhD Application Series: Preparing Application Materials, with Nathan Schneider and Roma Patel

    43:54

    This episode is the first in our current series on PhD applications. How should people prepare their applications to PhD programs in NLP? In this episode, we invite Nathan Schneider (Professor of Linguistics and Computer Science at Georgetown University) and Roma Patel (PhD student in Computer Science at Brown University) to share their perspectives on preparing application materials. We start by talking about what factors should go into the decision to apply for PhD programs and how to gain relevant experience. We then talk about the most important parts of an application, focusing particularly on how to write a strong statement of purpose and choose recommendation letter writers. Blog posts mentioned in this episode: - Nathan Schneider’s Advice on Statements of Purpose: https://nschneid.medium.com/inside-ph-d-admissions-what-readers-look-for-in-a-statement-of-purpose-3db4e6081f80 - Student Perspectives on Applying to NLP PhD Programs: https://blog.nelsonliu.me/2019/10/24/student-perspectives-on-applying-to-nlp-phd-programs/ Homepages: - Nathan Schneider: https://people.cs.georgetown.edu/nschneid/ - Roma Patel: http://cs.brown.edu/people/rpatel59/ The hosts for this episode are Alexis Ross and Nishant Subramani.
  • NLP Highlights podcast

    Não percas um episódio de NLP Highlights e subscrevê-lo na aplicação GetPodcast.

    iOS buttonAndroid button
  • NLP Highlights podcast

    132 - Alexa Prize Socialbot Grand Challenge and Alquist 4.0, with Petr Marek

    41:43

    In this episode, we discussed the Alexa Prize Socialbot Grand Challenge and this year's winning submission, Alquist 4.0, with Petr Marek, a member of the winning team. Petr gave us an overview of their submission, the design choices that led to them winning the competition, including combining a hardcoded dialog tree and a neural generator model and extracting implicit personal information about users from their responses, and some outstanding challenges. Petr Marek is a PhD student at the Czech Technical University in Prague. More about the Alexa Prize challenges: https://developer.amazon.com/alexaprize Technical report on Alquist 4.0: https://arxiv.org/abs/2109.07968
  • NLP Highlights podcast

    131 - Opportunities and Barriers between HCI and NLP, with Nanna Inie and Leon Derczynski

    46:54

    What can NLP researchers learn from Human Computer Interaction (HCI) research? We chatted with Nanna Inie and Leon Derczynski to find out. We discussed HCI's research processes including methods of inquiry, the data annotation processes used in HCI, and how they are different from NLP, and the cognitive methods used in HCI for qualitative error analyses. We also briefly talked about the opportunities the field of HCI presents for NLP researchers. This discussion is based on the following paper: https://aclanthology.org/2021.hcinlp-1.16/ Nanna Inie is a postdoctoral researcher and Leon Derczynski is an associate professor in CS at the IT University of Copenhagen. The hosts for this episode are Ana Marasović and Pradeep Dasigi.
  • NLP Highlights podcast

    130 - Linking human cognitive patterns to NLP Models, with Lisa Beinborn

    44:02

    In this episode, we talk with Lisa Beinborn, an assistant professor at Vrije Universiteit Amsterdam, about how to use human cognitive signals to improve and analyze NLP models. We start by discussing different kinds of cognitive signals—eye-tracking, EEG, MEG, and fMRI—and challenges associated with using them. We then turn to Lisa’s recent work connecting interpretability measures with eye-tracking data, which reflect the relative importance measures of different tokens in human reading comprehension. We discuss empirical results suggesting that eye-tracking signals correlate strongly with gradient-based saliency measures, but not attention, in NLP methods. We conclude with discussion of the implications of these findings, as well as avenues for future work. Papers discussed in this episode: Towards best practices for leveraging human language processing signals for natural language processing: https://api.semanticscholar.org/CorpusID:219309655 Relative Importance in Sentence Processing: https://api.semanticscholar.org/CorpusID:235358922 Lisa Beinborn’s webpage: https://beinborn.eu/ The hosts for this episode are Alexis Ross and Pradeep Dasigi.
  • NLP Highlights podcast

    129 - Transformers and Hierarchical Structure, with Shunyu Yao

    35:43

    In this episode, we talk to Shunyu Yao about recent insights into how transformers can represent hierarchical structure in language. Bounded-depth hierarchical structure is thought to be a key feature of natural languages, motivating Shunyu and his coauthors to show that transformers can efficiently represent bounded-depth Dyck languages, which can be thought of as a formal model of the structure of natural languages. We went on to discuss some of the intuitive ideas that emerge from the proofs, connections to RNNs, and insights about positional encodings that may have practical implications. More broadly, we also touched on the role of formal languages and other theoretical tools in modern NLP. Papers discussed in this episode: - Self-Attention Networks Can Process Bounded Hierarchical Languages (https://arxiv.org/abs/2105.11115) - Theoretical Limitations of Self-Attention in Neural Sequence Models (https://arxiv.org/abs/1906.06755) - RNNs can generate bounded hierarchical languages with optimal memory (https://arxiv.org/abs/2010.07515) - On the Practical Computational Power of Finite Precision RNNs for Language Recognition (https://arxiv.org/abs/1805.04908) Shunyu Yao's webpage: https://ysymyth.github.io/ The hosts for this episode are William Merrill and Matt Gardner.
  • NLP Highlights podcast

    128 - Dynamic Benchmarking, with Douwe Kiela

    47:00

    We discussed adversarial dataset construction and dynamic benchmarking in this episode with Douwe Kiela, a research scientist at Facebook AI Research who has been working on a dynamic benchmarking platform called Dynabench. Dynamic benchmarking tries to address the issue of many recent datasets getting solved with little progress being made towards solving the corresponding tasks. The idea is to involve models in the data collection loop to encourage humans to provide data points that are hard for those models, thereby continuously collecting harder datasets. We discussed the details of this approach, and some potential caveats. We also discussed dynamic leaderboards, a recent addition to Dynabench that rank systems based on their utility given specific use cases. Papers discussed in this episode: 1. Dynabench: Rethinking Benchmarking in NLP (https://www.semanticscholar.org/paper/Dynabench%3A-Rethinking-Benchmarking-in-NLP-Kiela-Bartolo/77a096d80eb4dd4ccd103d1660c5a5498f7d026b) 2. Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking (https://www.semanticscholar.org/paper/Dynaboard%3A-An-Evaluation-As-A-Service-Platform-for-Ma-Ethayarajh/d25bb256e5b69f769a429750217b0d9ec1cf4d86) 3. Adversarial NLI: A New Benchmark for Natural Language Understanding (https://www.semanticscholar.org/paper/Adversarial-NLI%3A-A-New-Benchmark-for-Natural-Nie-Williams/9d87300892911275520a4f7a5e5abf4f1c002fec) 4. DynaSent: A Dynamic Benchmark for Sentiment Analysis (https://www.semanticscholar.org/paper/DynaSent%3A-A-Dynamic-Benchmark-for-Sentiment-Potts-Wu/284dfcf7f25ca87b2db235c6cdc848b4143d3923) Douwe Kiela's webpage: https://douwekiela.github.io/ The hosts for this episode are Pradeep Dasigi and Alexis Ross.
  • NLP Highlights podcast

    127 - Masakhane and Participatory Research for African Languages, with Tosin Adewumi and Perez Ogayo

    47:17

    We invited members of Masakhane, Tosin Adewumi and Perez Ogayo, to talk about their EMNLP Findings paper that discusses why typical research is limited for low-resourced NLP and how participatory research can help.   As a result of participatory research, Masakhane has many, many success stories: first datasets and benchmarks in African languages, first research on human evaluation specifically for MT for low-resource languages, etc. In this episode, we talked about one of them—MasakhaNER—in more detail. The hosts for this episode are Pradeep Dasigi and Ana Marasović. -------------------------- Tosin Adewumi is a PhD student at the Luleå University of Technology in Sweden. His Twitter handle: @tosintwit Perez Ogayo is an undergrad student at the African Leadership University in Rwanda. Her Twitter handle: @a_ogayo Masakhane is a grassroots organization whose mission is to strengthen and spur NLP research in African languages, for Africans, by Africans: https://www.masakhane.io/ Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages (Findings of EMNLP 2020): https://arxiv.org/abs/2010.02353 MasakhaNER: Named Entity Recognition for African languages (AfricaNLP Workshop @ EACL 2021): https://arxiv.org/abs/2103.11811
  • NLP Highlights podcast

    126 - Optimizing Continuous Prompts for Generation, with Lisa Li

    47:38

    We invited Lisa Li to talk about her recent work, Prefix-Tuning: Optimizing Continuous Prompts for Generation. Prefix tuning is a lightweight alternative to finetuning, and the idea is to tune only a fixed-length task-specific continuous vector, and to keep the pretrained transformer parameters frozen. We discussed how prefix tuning compares with finetuning and other efficient alternatives on two tasks in various experimental settings, and in what scenarios prefix tuning is preferable. Lisa is a Phd student at Stanford University. Lisa's webpage: https://xiangli1999.github.io/ The hosts for this episode are Pradeep Dasigi and Ana Marasović.
  • NLP Highlights podcast

    125 - VQA for Real Users, with Danna Gurari

    42:10

    How can we build Visual Question Answering systems for real users? For this episode, we chatted with Danna Gurari, about her work in building datasets and models towards VQA for people who are blind. We talked about the differences between the existing datasets, and Vizwiz, a dataset built by Gurari et al., and the resulting algorithmic changes. We also discussed the unsolved challenges in this field, and the new tasks they result in. Danna Gurari is an Assistant Professor as well as Founding Director of the Image and Video Computing group in the School of Information at University of Texas at Austin (UT-Austin). Vizwiz project page: https://vizwiz.org/ The hosts for this episode are Ana Marasović and Pradeep Dasigi.

Descobre o mundo dos podcasts com a app gratuita GetPodcast.

Subscreve os teus podcasts preferidos, ouve episódios offline e obtém recomendações fantásticas.

iOS buttonAndroid button