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Best Artificial Intelligence Podcasts We Could Find
Best Artificial Intelligence Podcasts We Could Find
With the rise of artificial intelligence in use today including applications like Siri, Alexa, Tesla, Cortana, Cogito, Google Now, and even Netflix, podcasts are a great alternative to keep yourself updated. We've gathered a list of podcasts available for you about this technology where you can get the latest news and trends plus learn more about how AI works and its impact on our lives.
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Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while k ...
 
On the Mind Matters podcast, Discovery Institute’s Walter Bradley Center for Natural and Artificial Intelligence considers the implications and misconceptions, the opportunities and limitations, and the applications and challenges presented by intelligent agents and their algorithms.
 
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, de ...
 
Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational n ...
 
Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.
 
The AI in Business Podcast is for functional business leaders who need to find AI opportunities, align AI capabilities with strategy, and deliver ROI. Each week, Emerj founder Daniel Faggella interviews top AI executives from Fortune 500 firms and unicorn startups - and uncovers trends, use-cases, and best practices for practical AI adoption. Subscribe to Emerj's weekly AI newsletter by downloading our "Beginning with AI" PDF guide: https://emerj.com/beg1
 
AI has been described as “Thor’s Hammer“ and “the new electricity.” But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. This podcast is produced by NVIDIA, the AI computing company. Multiple episodes are released every month.
 
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NLP Highlights

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NLP Highlights

Allen Institute for Artificial Intelligence

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Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. The hosts are the members of the AllenNLP team at Allen Institute for AI. All views expressed belong to the hosts and guests and do not represent their employers.
 
AI with AI explores the latest breakthroughs in artificial intelligence and autonomy, and discusses the technological and military implications. Join Andy Ilachinski and David Broyles as they explain the latest developments in this rapidly evolving field. The views expressed here are those of the commentators and do not necessarily reflect the views of CNA or any of its sponsors.
 
The team at MMC go 'Beyond the Hype' with the world’s leading AI technologists, entrepreneurs and corporate executives that are transforming today's industries. This podcast is produced by MMC Ventures, the research-led venture capital firm investing in early-stage technology companies. Visit mmc.vc for more details or find us on Twitter @MMC_Ventures.
 
Unlock the business value of AI in financial services with in-depth interviews on trends, use-cases, and cutting-edge best practices. In each episode, Emerj Founder Daniel Faggella interviews leaders at firms like HSBC, Citigroup, and Visa - as well as AI innovators from Silicon Valley and around the world. Subscribe to Emerj's weekly AI newsletter by downloading our "AI in Financial Services Cheat Sheet" PDF guide: https://emerj.com/fin1
 
Roboism is a show mostly about robots. We are exploring how artificial intelligence, machine learning, and digital assistants are affecting our culture. Come explore the humanity behind the bots that are quickly becoming a part of every day life. Hosted by Kathy Campbell and Alex Cox.
 
TalkRL podcast is All Reinforcement Learning, All the Time. In-depth interviews with brilliant people at the forefront of RL research and practice. Guests from places like MILA, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute. Hosted by Robin Ranjit Singh Chauhan. Technical content.
 
David Yakobovitch explores AI for consumers through fireside conversations with industry thought leaders on HumAIn. From Chief Data Scientists and AI Advisors, to Leaders who advance AI for All, the HumAIn Podcast is the channel to release new AI products, to learn about industry trends, and to bridge the gap between humans and machines in the Fourth Industrial Revolution.
 
This is the audio podcast for the ML Street Talk YouTube channel at https://www.youtube.com/c/MachineLearningStreetTalk Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is unabashedly technical and non-commercial, so you will hear no annoying pitches. Corporate- and MBA-speak is banned on street talk, "data product", "digital transformation" a ...
 
Welcome to Data Brew by Databricks with Denny and Brooke! In this series, we explore various topics in the data and AI community and interview subject matter experts in data engineering/data science. So join us with your morning brew in hand and get ready to dive deep into data + AI! For this first season, we will be focusing on lakehouses – combining the key features of data warehouses, such as ACID transactions, with the scalability of data lakes, directly against low-cost object stores.
 
Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.
 
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Learning Machines 101

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Learning Machines 101

Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

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Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that wil ...
 
Every weekday, TED Talks Daily brings you the latest talks in audio. Join host and journalist Elise Hu for thought-provoking ideas on every subject imaginable — from Artificial Intelligence to Zoology, and everything in between — given by the world's leading thinkers and creators. With TED Talks Daily, find some space in your day to change your perspectives, ignite your curiosity, and learn something new.
 
Al: Innovation or Destruction? In this sci-fi podcast based on the groundbreaking interactive series Artificial, our hosts delve into the world of Sophie, an artificial intelligence being on a journey to become human, in attempts to illuminate the dangers and benefits of AI while looking at how to ethically treat and develop our new sentient friends. We invite you to join the conversation and weigh in on the ultimate question: Will Al prove to be good for the world... or will it lead to our ...
 
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
 
In each episode of The Robot Brains podcast, renowned artificial intelligence researcher, professor and entrepreneur Pieter Abbeel meets the brilliant minds attempting to build robots with brains. Pieter is joined by leading experts in AI Robotics from all over the world as he explores how far humanity has come in its mission to create conscious computers, mindful machines and rational robots. Host: Pieter Abbeel | Executive Producers: Ricardo Reyes & Henry Tobias Jones | Audio Production: K ...
 
Every weekday, TED Talks Daily brings you the latest talks in audio. Join host and journalist Elise Hu for thought-provoking ideas on every subject imaginable — from Artificial Intelligence to Zoology, and everything in between — given by the world's leading thinkers and creators. With TED Talks Daily, find some space in your day to change your perspectives, ignite your curiosity, and learn something new.
 
BRIDGEi2i’s signature podcast “AI to Impact” covers everything about Digital and AI. Featuring some remarkable thought leadership, expert points of view, and commentaries from a gamut of industry leaders, this is a definitive guide for Making AI Real. Put on your headphones and join us on this insightful journey of AI-powered Transformation.You can also listen to our podcast on below channels-Spotify link: https://spoti.fi/2TiJLRfApple link: https://apple.co/3cI0pkUGoogle link: https://bit.l ...
 
New episodes come out every Thursday for free, with 1-week early access for Wondery+ subscribers. DNA science. Artificial intelligence. Smartphones and 3D printers. Science and technology have transformed the world we live in. But how did we get here? It wasn’t by accident. Well, sometimes it was. It was also the result of hard work, teamwork, and competition. And incredibly surprising moments. Hosted by bestselling author Steven Johnson (“How We Got To Now”), American Innovations uses immer ...
 
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On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Jessie J. Smith and Dylan Doyle, hosts of the Radical AI podcast. On their podcast they try to probe and advance the field of Arti…
 
Bhargavi Paranjape, Matthew Lamm and Ian TenneyAbstractDeep NLP models have been shown to learn spurious correlations, leaving them brittle to input perturbations. Recent work has shown that counterfactual or contrastive data -- i.e. minimally perturbed inputs -- can reveal these weaknesses, and that data augmentation using counterfactuals can help…
 
Take our survey at twimlai.com/survey21! Today we’re joined by Tim Rocktäschel, a research scientist at Facebook AI Research and an associate professor at University College London (UCL). Tim’s work focuses on training RL agents in simulated environments, with the goal of these agents being able to generalize to novel situations. Typically, this is…
 
Humphrey Chen: How AI Can Revolutionize the Way We Consume Video [Audio] Podcast: Play in new window | Download Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS Humphrey Chen is the CEO and Co-Founder of CLIPr. He has a BS in Management Science from MIT. His work in tech specializes in the use of technology to make people and companie…
 
Andy and Dave discuss the latest in AI news and research, including, the UK government releases its National AI Strategy, a 10-year plan to make the country a global AI superpower [1:28]. Stanford University’s One Hundred Year Study on AI Project releases its second report, Gathering Strength, Gathering Storms, assessing developments in AI between …
 
Skin is one of the most powerful predictors of health, yet nearly half of all new dermatologists admit to feeling uncomfortable identifying health issues on darker skin tones -- resulting in poorer health outcomes for patients of color. In this crucial talk, TED Fellow and dermatologist Jenna C. Lester shares her effort to extend medical training b…
 
Skin is one of the most powerful predictors of health, yet nearly half of all new dermatologists admit to feeling uncomfortable identifying health issues on darker skin tones -- resulting in poorer health outcomes for patients of color. In this crucial talk, TED Fellow and dermatologist Jenna C. Lester shares her effort to extend medical training b…
 
Kelsi Sheren is a veteran, artillery gunner, and founder of Brass and Unity. Please support this podcast by checking out our sponsors: – Shopify: https://shopify.com/lex to get 14-day free trial – Justworks: https://justworks.com – Novo: https://banknovo.com/lex – Indeed: https://indeed.com/lex to get $75 credit – Onnit: https://lexfridman.com/onni…
 
Listen to maverick entrepreneur Peter Thiel’s talk from last year’s COSM conference. Thiel discusses his views of artificial intelligence, Big Tech’s monopoly, China, and the future of technology with legendary tech guru George Gilder. You can register now to hear Peter Thiel and George Gilder at this year’s COSM conference in November. Show Notes …
 
Bla\v{z} \v{S}krlj and Matej Petkovi\v{c}AbstractContemporary natural language processing (NLP) revolves around learning from latent document representations, generated either implicitly by neural language models or explicitly by methods such as doc2vec or similar. One of the key properties of the obtained representations is their dimension. Whilst…
 
Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip IsolaAbstractNeural MMO is a computationally accessible research platform that combines large agent populations, long time horizons, open-ended tasks, and modular game systems. Existing environments feature subsets of these properties, but Neural MMO is the first to combine them all. We pre…
 
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil ShahAbstractGiven the prevalence of large-scale graphs in real-world applications, the storage and time for training neural models have raised increasing concerns. To alleviate the concerns, we propose and study the problem of graph condensation for graph neural networks (GNNs). …
 
Yuning Mao, Lambert Mathias, Rui Hou, Amjad Almahairi, Hao Ma, Jiawei Han, Wen-tau Yih, Madian KhabsaAbstractConventional fine-tuning of pre-trained language models tunes all model parameters and stores a full model copy for each downstream task, which has become increasingly infeasible as the model size grows larger. Recent parameter-efficient lan…
 
Dora Jambor, Dzmitry BahdanauAbstractSemantic parsing is the task of producing a structured meaning representation for natural language utterances or questions. Recent research has pointed out that the commonly-used sequence-to-sequence (seq2seq) semantic parsers struggle to generalize systematically, i.e. to handle examples that require recombinin…
 
Anurag Katakkar, Weiqin Wang, Clay H. Yoo, Zachary C. Lipton, Divyansh KaushikAbstractIn attempts to develop sample-efficient algorithms, researcher have explored myriad mechanisms for collecting and exploiting feature feedback, auxiliary annotations provided for training (but not test) instances that highlight salient evidence. Examples include bo…
 
Igor L. Markov, Hanson Wang, Nitya Kasturi, Shaun Singh, Sze Wai Yuen, Mia Garrard, Sarah Tran, Yin Huang, Zehui Wang, Igor Glotov, Tanvi Gupta, Boshuang Huang, Peng Chen, Xiaowen Xie, Michael Belkin, Sal Uryasev, Sam Howie, Eytan Bakshy, Norm ZhouAbstractModern software systems and products increasingly rely on machine learning models to make data…
 
Grey Kuling, Dr. Belinda Curpen, and Anne L. MartelAbstractRadiology reports are the main form of communication between radiologists and other clinicians, and contain important information for patient care. However in order to use this information for research it is necessary to convert the raw text into structured data suitable for analysis. Domai…
 
Megan Ung, Jing Xu, Y-Lan BoureauAbstractCurrent open-domain conversational models can easily be made to talk in inadequate ways. Online learning from conversational feedback given by the conversation partner is a promising avenue for a model to improve and adapt, so as to generate fewer of these safety failures. However, current state-of-the-art m…
 
Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. KochenderferAbstractAutonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment. The complexity of these systems often precludes the use of formal verification and real-world testing can be …
 
For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics. We interview Junta Nakai in our most unique location yet - Brooklyn Kura - the first non-Japanese sake distillery in New Yor…
 
Sijia Wang, Mo Yu, Shiyu Chang, Lichao Sun, Lifu HuangAbstractEvent extraction is typically modeled as a multi-class classification problem where both event types and argument roles are treated as atomic symbols. These approaches are usually limited to a set of pre-defined types. We propose a novel event extraction framework that takes event types …
 
Mhafuzul Islam, Mashrur Chowdhury, Zadid Khan, Sakib Mahmud KhanAbstractA classical computer works with ones and zeros, whereas a quantum computer uses ones, zeros, and superpositions of ones and zeros, which enables quantum computers to perform a vast number of calculations simultaneously compared to classical computers. In a cloud-supported cyber…
 
Shanghui Yang, Mengxia Zhu, Xuesong LuAbstractKnowledge tracing (KT) has recently been an active research area of computational pedagogy. The task is to model students' mastery level of knowledge concepts based on their responses to the questions in the past, as well as predict the probabilities that they correctly answer subsequent questions in th…
 
Yujia Bao, Shiyu Chang, Regina BarzilayAbstractWhile unbiased machine learning models are essential for many applications, bias is a human-defined concept that can vary across tasks. Given only input-label pairs, algorithms may lack sufficient information to distinguish stable (causal) features from unstable (spurious) features. However, related ta…
 
Junhao Yan, Woonsok LeeAbstractIn recent years, unsupervised domain adaptation (UDA) for semantic segmentation has brought many researchers'attention. Many of them take an approach to design a complex system so as to better align the gap between source and target domain. Instead, we focus on the very basic structure of the deep neural network, Batc…
 
Thanh Nguyen, Tung M. Luu, Thang Vu and Chang D. YooAbstractDeveloping an agent in reinforcement learning (RL) that is capable of performing complex control tasks directly from high-dimensional observation such as raw pixels is yet a challenge as efforts are made towards improving sample efficiency and generalization. This paper considers a learnin…
 
Xin Zhou, Ruotian Ma, Tao Gui, Yiding Tan, Qi Zhang, Xuanjing HuangAbstractPlug-and-play functionality allows deep learning models to adapt well to different tasks without requiring any parameters modified. Recently, prefix-tuning was shown to be a plug-and-play method on various text generation tasks by simply inserting corresponding continuous ve…
 
Anargyros Chatzitofis, Dimitrios Zarpalas, Stefanos Kollias, Petros DarasAbstractIn this paper, a marker-based, single-person optical motion capture method (DeepMoCap) is proposed using multiple spatio-temporally aligned infrared-depth sensors and retro-reflective straps and patches (reflectors). DeepMoCap explores motion capture by automatically l…
 
Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae JeonAbstractContinual Learning (CL) is an emerging machine learning paradigm that aims to learn from a continuous stream of tasks without forgetting knowledge learned from the previous tasks. To avoid performance decrease caused by forgetting, prior studies exploit episo…
 
Fabian Lim, Laura Wynter, Shiau Hong LimAbstractOptimal transport is a framework for comparing measures whereby a cost is incurred for transporting one measure to another. Recent works have aimed to improve optimal transport plans through the introduction of various forms of structure. We introduce novel order constraints into the optimal transport…
 
Zhiwei Xu, Yunpeng Bai, Bin Zhang, Dapeng Li, Guoliang FanAbstractMulti-agent reinforcement learning often suffers from the exponentially larger action space caused by a large number of agents. In this paper, we propose a novel value decomposition framework HAVEN based on hierarchical reinforcement learning for the fully cooperative multi-agent pro…
 
Quan Wang and Songtai Dai and Benfeng Xu and Yajuan Lyu and Yong Zhu and Hua Wu and Haifeng WangAbstractPre-trained language models (PLMs), such as BERT and GPT, have revolutionized the field of NLP, not only in the general domain but also in the biomedical domain. Most prior efforts in building biomedical PLMs have resorted simply to domain adapta…
 
The roadmap to ending pollution from transportation is here, says electrification advocate Monica Araya. In conversation with head of TED Chris Anderson, Araya introduces Drive Electric: a global campaign to retire the polluting internal combustion engine in time to avoid climate disaster. And she shares some exciting news: a breakthrough funding c…
 
The roadmap to ending pollution from transportation is here, says electrification advocate Monica Araya. In conversation with head of TED Chris Anderson, Araya introduces Drive Electric: a global campaign to retire the polluting internal combustion engine in time to avoid climate disaster. And she shares some exciting news: a breakthrough funding c…
 
Michiya Kuramata, Ryota Katsuki, Kazuhide NakataAbstractQuantum annealing (QA) has gained considerable attention because it can be applied to combinatorial optimization problems, which have numerous applications in logistics, scheduling, and finance. In recent years, research on solving practical combinatorial optimization problems using them has a…
 
nargyros Chatzitofis, Leonidas Saroglou, Prodromos Boutis, Petros Drakoulis, Nikolaos Zioulis, Shishir Subramanyam, Bart Kevelham, Caecilia Charbonnier, Pablo Cesar, Dimitrios Zarpalas, Stefanos Kollias, Petros DarasAbstractWe introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by…
 
Shen Liu, Meirong Ma, Hao Yuan, Jianchao Zhu, Yuanbin Wu, Man LanAbstractPun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word. Most previous studies adopt limited word senses obtained by WSD(Word…
 
Yunshi Huang and Emilie Chouzenoux and Jean-Christophe PesquetAbstractIn this paper, we introduce a variational Bayesian algorithm (VBA) for image blind deconvolution. Our generic framework incorporates smoothness priors on the unknown blur/image and possible affine constraints (e.g., sum to one) on the blur kernel. One of our main contributions is…
 
Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem, Mathias KersemansAbstractNowadays, using vibration data in conjunction with pattern recognition methods is one of the most common fault detection strategies for structures. However, their performances depend on the features extracted from vibration data, the features selected to train the classifi…
 
What if you could design a spy plane that could be flown remotely and hover in the sky for hours, providing reconnaissance for troops on the ground? In the early 1980s, the visionary inventor Abe Karem begins building drones out of his L.A. garage. Soon, the Pentagon and the CIA take notice. Though he faces many challenges, Karem is on the forefron…
 
Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang WangAbstractUser profiling has long been an important problem that investigates user interests in many real applications. Some recent works regard users and their interacted objects as entities of a graph and turn the problem into a node classification task. However, they neglect the difference of …
 
Yantian Zha, Yikang Li, Tianshu Yu, Subbarao Kambhampati, Baoxin LiAbstractHuman visual recognition of activities or external agents involves an interplay between high-level plan recognition and low-level perception. Given that, a natural question to ask is: can low-level perception be improved by high-level plan recognition? We formulate the probl…
 
Fanchao Qi, Yangyi Chen, Xurui Zhang, Mukai Li, Zhiyuan Liu, Maosong SunAbstractAdversarial attacks and backdoor attacks are two common security threats that hang over deep learning. Both of them harness task-irrelevant features of data in their implementation. Text style is a feature that is naturally irrelevant to most NLP tasks, and thus suitabl…
 
Gabriel-Claudiu GramaAbstractThe major finding, of this article, is an ensemble method, but more exactly, a novel, better ranked voting system (and other variations of it), that aims to solve the problem of finding the best candidate to represent the voters. We have the source code on GitHub, for making realistic simulations of elections, based on …
 
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincen…
 
Xiangyang Liu, Tianxiang Sun, Junliang He, Lingling Wu, Xinyu Zhang, Hao Jiang, Zhao Cao, Xuanjing Huang, Xipeng QiuAbstractSupersized pre-trained language models have pushed the accuracy of various NLP tasks to a new state-of-the-art (SOTA). Rather than pursuing the reachless SOTA accuracy, most works are pursuing improvement on other dimensions s…
 
Livio Robaldo and Kolawole J. AdebayoAbstractReified Input/Output (I/O) logic[21] has been recently proposed to model real-world norms in terms of the logic in [11]. This is massively grounded on the notion of reification, and it has specifically designed to model meaning of natural language sentences, such as the ones occurring in existing legisla…
 
Kazutoshi Shinoda and Yuki Takezawa and Masahiro Suzuki and Yusuke Iwasawa and Yutaka MatsuoAbstractAn interactive instruction following task has been proposed as a benchmark for learning to map natural language instructions and first-person vision into sequences of actions to interact with objects in a 3D simulated environment. We find that an exi…
 
Eric Lei, Hamed Hassani, Shirin Saeedi BidokhtiAbstractIn recent years, deep neural network (DNN) compression systems have proved to be highly effective for designing source codes for many natural sources. However, like many other machine learning systems, these compressors suffer from vulnerabilities to distribution shifts as well as out-of-distri…
 
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