Month: June 2024

Disentangling Latent Representations for Interpretability and Controllability

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision for Language Representation Learning and Generation: Acknowledgements

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Tailoring Textual Resources for Evaluation Tasks: Summary

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Improving Language Representation Learning via Sentence Ordering Prediction

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision: Learning Semantic Knowledge from Wikipedia

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision for Language Representation Learning and Generation: Abstract

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Disentangling Latent Representations for Interpretability and Controllability: Summary

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Learning Discourse-Aware Sentence Representations from Document Structures

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision for Language Representation Learning and Generation: Conclusion

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision: Appendix B – Appendix To Chapter 6

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Learning Semantic Knowledge from Wikipedia: Learning Entity Representations from Hyperlinks

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Disentangling Semantics and Syntax in Sentence Representations

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision: Improving In-Context Few-Shot Learning via Self-Supervised Training

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision for Language Representation Learning and Generation: Bibliography

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

Leveraging Natural Supervision: Appendix A – Appendix to Chapter 3

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:::info Author: (1) Mingda Chen. ::: Table of Links Abstract Acknowledgements 1 INTRODUCTION 1.1 Overview 1.2 Contributions 2 BACKGROUND 2.1 Self-Supervised Language Pretraining 2.2 Naturally-Occurring Data Structures 2.3 Sentence Variational Autoencoder 2.4 Summary 3 IMPROVING SELF-SUPERVISION FOR LANGUAGE PRETRAINING 3.1 Improving Language Representation Learning via Sentence Ordering Prediction 3.2 Improving In-Context Few-Shot Learning via Self-Supervised … Read more

You can no longer use Tumblr’s tipping feature 

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Tumblr officially shut down “Tips,” an opt-in feature where creators could receive one-time payments from their followers.  As of today, the tipping icon has automatically disappeared from all posts and blogs with the feature enabled. Creators that use the feature should note that June 15 is the last day they can withdraw money they received … Read more

The Rising Issue of Zombie APIs and Your Increased Attack Surface

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Offering an API to customers increases your revenue, but it also expands your attack surface. Businesses can offer an API that can be embedded into third-party applications to make development easier. For example, embedding social media into an application lets customers discuss a product without adding extensive overhead to your development team. The social media … Read more

Godzilla Minus One gets a surprise Netflix release

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Image: Toho International Godzilla Minus One is officially streaming worldwide on Netflix as of today, everywhere except Japan and France, according to film distributor Toho International in a release shared with The Verge. You can also buy ($14.99) or rent ($5.99) digital copies, either in color (Apple TV, Amazon, Google Play) or black and white … Read more

Violence Detection in Videos: Experiments and Results

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:::info Authors: (1) Praveen Tirupattur,  University of Central Florida. ::: Table of Links Abstract Acknowledgements Chapter 1: Introduction Chapter 2: Related Work Chapter 3: Proposed Approach Chapter 4: Experiments and Results Chapter 5: Conclusions and Future Work Bibliography 4. Experiments and Results In this chapter, details of the experiments conducted to evaluate the performance of … Read more

Violence Detection in Videos: Bibliography

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:::info Authors: (1) Praveen Tirupattur,  University of Central Florida. ::: Table of Links Abstract Acknowledgements Chapter 1: Introduction Chapter 2: Related Work Chapter 3: Proposed Approach Chapter 4: Experiments and Results Chapter 5: Conclusions and Future Work Bibliography Bibliography [1] E. Acar, S. Spiegel, S. Albayrak, and D. Labor. Mediaeval 2011 affect task: Violent scene … Read more

Violence Detection in Videos: Proposed Approach

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:::info Authors: (1) Praveen Tirupattur,  University of Central Florida. ::: Table of Links Abstract Acknowledgements Chapter 1: Introduction Chapter 2: Related Work Chapter 3: Proposed Approach Chapter 4: Experiments and Results Chapter 5: Conclusions and Future Work Bibliography 3. Proposed Approach This chapter provides a detailed description of the approach followed in this work. The … Read more