139 - Coherent Long Story Generation, with Kevin Yang

139 - Coherent Long Story Generation, with Kevin Yang

Author: Allen Institute for Artificial Intelligence March 24, 2023 Duration: 45:18
How can we generate coherent long stories from language models? Ensuring that the generated story has long range consistency and that it conforms to a high level plan is typically challenging. In this episode, Kevin Yang describes their system that prompts language models to first generate an outline, and iteratively generate the story while following the outline and reranking and editing the outputs for coherence. We also discussed the challenges involved in evaluating long generated texts. Kevin Yang is a PhD student at UC Berkeley. Kevin's webpage: https://people.eecs.berkeley.edu/~yangk/ Papers discussed in this episode: 1. Re3: Generating Longer Stories With Recursive Reprompting and Revision (https://www.semanticscholar.org/paper/Re3%3A-Generating-Longer-Stories-With-Recursive-and-Yang-Peng/2aab6ca1a8dae3f3db6d248231ac3fa4e222b30a) 2. DOC: Improving Long Story Coherence With Detailed Outline Control (https://www.semanticscholar.org/paper/DOC%3A-Improving-Long-Story-Coherence-With-Detailed-Yang-Klein/ef6c768f23f86c4aa59f7e859ca6ffc1392966ca)

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
103 - Processing Language in Social Media, with Brendan O'Connor [not-audio_url] [/not-audio_url]

Duration: 43:12
We talked to Brendan O’Connor for this episode about processing language in social media. Brendan started off by telling us about his projects that studied the linguistic and geographical patterns of African American Eng…
101 - The lottery ticket hypothesis, with Jonathan Frankle [not-audio_url] [/not-audio_url]

Duration: 41:16
In this episode, Jonathan Frankle describes the lottery ticket hypothesis, a popular explanation of how over-parameterization helps in training neural networks. We discuss pruning methods used to uncover subnetworks (win…
100 - NLP Startups, with Oren Etzioni [not-audio_url] [/not-audio_url]

Duration: 30:55
For our 100th episode, we invite AI2 CEO Oren Etzioni to talk to us about NLP startups. Oren has founded several successful startups, is himself an investor in startups, and helps with AI2's startup incubator. Some of ou…
98 - Analyzing Information Flow In Transformers, With Elena Voita [not-audio_url] [/not-audio_url]

Duration: 37:05
What function do the different attention heads serve in multi-headed attention models? In this episode, Lena describes how to use attribution methods to assess the importance and contribution of different heads in severa…
95 - Common sense reasoning, with Yejin Choi [not-audio_url] [/not-audio_url]

Duration: 35:29
In this episode, we invite Yejin Choi to talk about common sense knowledge and reasoning, a growing area in NLP. We start by discussing a working definition of “common sense” and the practical utility of studying it. We…