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

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

Author: Allen Institute for Artificial Intelligence August 21, 2021 Duration: 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.

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: 50

NLP Highlights
Podcast Episodes
129 - Transformers and Hierarchical Structure, with Shunyu Yao [not-audio_url] [/not-audio_url]

Duration: 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 language…
128 - Dynamic Benchmarking, with Douwe Kiela [not-audio_url] [/not-audio_url]

Duration: 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 Dynaben…
126 - Optimizing Continuous Prompts for Generation, with Lisa Li [not-audio_url] [/not-audio_url]

Duration: 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-sp…
125 - VQA for Real Users, with Danna Gurari [not-audio_url] [/not-audio_url]

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…