125 - VQA for Real Users, with Danna Gurari

125 - VQA for Real Users, with Danna Gurari

Author: Allen Institute for Artificial Intelligence May 4, 2021 Duration: 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.

While NLP Highlights is currently on hiatus, its archive remains a compelling snapshot of conversations from the front lines of computational linguistics. Produced by the Allen Institute for Artificial Intelligence, this science podcast carved out a space for deep, researcher-led discussions about natural language processing. Each episode functions as an informal seminar, where the people actively designing algorithms and pushing the field forward explain their work in their own words. You'll hear about the nuanced challenges behind making machines understand, generate, and reason with human language, from foundational theories to unexpected applications. The dialogue in this podcast often delves into the "why" behind the research, not just the results, offering clarity on complex topics like machine translation, sentiment analysis, or large language models. It’s a chance to listen as experts articulate their thought processes, debates, and moments of insight, with all the candidness that comes from a conversation between peers. The views shared are personal perspectives from the hosts and their guests, independent of their affiliated institutions. For anyone curious about how machines learn to parse meaning, the archived episodes of NLP Highlights provide a thoughtful and accessible entry point.
Author: Language: English Episodes: 100

NLP Highlights
Podcast Episodes
113 - Managing Industry Research Teams, with Fernando Pereira [not-audio_url] [/not-audio_url]

Duration: 42:22
We invited Fernando Pereira, a VP and Distinguished Engineer at Google, where he leads NLU and ML research, to talk about managing NLP research teams in industry. Topics we discussed include prioritizing research against…
110 - Natural Questions, with Tom Kwiatkowski and Michael Collins [not-audio_url] [/not-audio_url]

Duration: 43:30
In this episode, Tom Kwiatkowski and Michael Collins talk about Natural Questions, a benchmark for question answering research. We discuss how the dataset was collected to reflect naturally-occurring questions, the crite…
109 - What Does Your Model Know About Language, with Ellie Pavlick [not-audio_url] [/not-audio_url]

Duration: 46:58
How do we know, in a concrete quantitative sense, what a deep learning model knows about language? In this episode, Ellie Pavlick talks about two broad directions to address this question: structural and behavioral analy…
107 - Multi-Modal Transformers, with Hao Tan and Mohit Bansal [not-audio_url] [/not-audio_url]

Duration: 37:34
In this episode, we invite Hao Tan and Mohit Bansal to talk about multi-modal training of transformers, focusing in particular on their EMNLP 2019 paper that introduced LXMERT, a vision+language transformer. We spend the…
106 - Ethical Considerations In NLP Research, with Emily Bender [not-audio_url] [/not-audio_url]

Duration: 39:18
In this episode, we talked to Emily Bender about the ethical considerations in developing NLP models and putting them in production. Emily cited specific examples of ethical issues, and talked about the kinds of potentia…
105 - Question Generation, with Sudha Rao [not-audio_url] [/not-audio_url]

Duration: 42:59
In this episode we invite Sudha Rao to talk about question generation. We talk about different settings where you might want to generate questions: for human testing scenarios (rare), for data augmentation (has been done…
104 - Model Distillation, with Victor Sanh and Thomas Wolf [not-audio_url] [/not-audio_url]

Duration: 31:22
In this episode we talked with Victor Sanh and Thomas Wolf from HuggingFace about model distillation, and DistilBERT as one example of distillation. The idea behind model distillation is compressing a large model by buil…