[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models

The Thesis Review

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Unlocking Your Hidden Genius: How to Harness Your Innate Talents with Betsy Wills & Alex Ellison | Ep. 289 32:08

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Did you know there’s an actual science to uncovering your hidden genius? It’s not about filling out a “dream job” worksheet—it’s about understanding how your brain is wired, identifying your natural aptitudes, and using them to thrive. This isn’t just a self-discovery exercise. It’s a game-changer for your career, your relationships, and how you show up in the world. Betsy Wills and Alex Ellison are redefining how we approach career discovery, proving that finding the right path isn’t just about landing a job—it’s about creating a life that aligns with who you actually are. ✅ Betsy Wills – Cofounder of YouScience, a groundbreaking psychometric assessment platform reshaping how we understand our talents. She’s also the Director of Marketing & Branding at Diversified Trust and a frequent lecturer at Vanderbilt University and NYU’s Stern School of Business. ✅ Alex Ellison – Founder of Throughline Guidance, a global college and career counseling practice. She’s a sought-after writer, speaker, and expert in college readiness and career development. ✅ Together, they co-authored Your Hidden Genius: The Science-Backed Strategy to Uncovering and Harnessing Your Innate Talents. Discovering your hidden genius isn’t just about career success—it’s about tapping into what makes you, you . Connect with Betsy & Alex: Website (Free Downloads): www.yourhiddengenius.com Book: https://www.harpercollins.com/products/your-hidden-genius-elizabeth-m-willsalexandra-ellison Related Podcast Episodes: How To Be You, But Better with Olga Khazan | 288 Finding Purpose Through Human Design with Emma Dunwoody | 228 195 / Finding (And Using) Your Voice with Amy Green Smith Share the Love: If you found this episode insightful, please share it with a friend, tag us on social media, and leave a review on your favorite podcast platform! 🔗 Subscribe & Review: Apple Podcasts | Spotify | Amazon Music…

cách đây khoảng một năm trước 1:17:06

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Niloofar Mireshghallah is a postdoctoral scholar at the University of Washington. Her research focuses on privacy, natural language processing, and the societal implications of machine learning. Niloofar completed her PhD in 2023 at UC San Diego, where she was advised by Taylor Berg-Kirkpatrick. Her PhD thesis is titled "Auditing and Mitigating Safety Risks in Large Language Models." We discuss her journey into research and her work on privacy and LLMs, including how privacy is defined, common attacks and mitigations, differential privacy, and the balance between memorization and generalization. - Episode notes: www.wellecks.com/thesisreview/episode47.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview

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#Science #Thesis Review #Sean Welleck

The Thesis Review

[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models

The Thesis Review

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The Thesis Review

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[48] Tianqi Chen - Scalable and Intelligent Learning Systems 46:29

cách đây 23 weeks trước46:29

46:29

Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems. Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI. - Episode notes: www.wellecks.com/thesisreview/episode48.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Follow Tianqi Chen on Twitter (@tqchenml) - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models 1:17:06

cách đây 25 weeks trước1:17:06

1:17:06

The Thesis Review

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[46] Yulia Tsvetkov - Linguistic Knowledge in Data-Driven NLP 59:53

cách đây 2 years trước59:53

59:53

Yulia Tsvetkov is a Professor in the Allen School of Computer Science & Engineering at the University of Washington. Her research focuses on multilingual NLP, NLP for social good, and language generation. Yulia's PhD thesis is titled "Linguistic Knowledge in Data-Driven Natural Language Processing", which she completed in 2016 at CMU. We discuss getting started in research, then move to Yulia's work in the thesis that combines ideas from linguistics and natural language processing. We discuss low-resource and multilingual NLP, large language models, and great advice about research and beyond. - Episode notes: www.wellecks.com/thesisreview/episode46.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form 59:35

cách đây 2 years trước59:35

59:35

Luke Zettlemoyer is a Professor at the University of Washington and Research Scientist at Meta. His work spans machine learning and NLP, including foundational work in large-scale self-supervised pretraining of language models. Luke's PhD thesis is titled "Learning to Map Sentences to Logical Form", which he completed in 2009 at MIT. We talk about his PhD work, the path to the foundational Elmo paper, and various topics related to large language models. - Episode notes: www.wellecks.com/thesisreview/episode45.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[44] Hady Elsahar - NLG from Structured Knowledge Bases (& Controlling LMs) 1:05:56

cách đây 3 years trước1:05:56

1:05:56

Hady Elsahar is a Research Scientist at Naver Labs Europe. His research focuses on Neural Language Generation under constrained and controlled conditions. Hady's PhD was on interactions between Natural Language and Structured Knowledge bases for Data2Text Generation and Relation Extraction & Discovery, which he completed in 2019 at the Université de Lyon. We talk about his phd work and how it led to interests in multilingual and low-resource in NLP, as well as controlled generation. We dive deeper in controlling language models, including his interesting work on distributional control and energy-based models. - Episode notes: www.wellecks.com/thesisreview/episode44.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[43] Swarat Chaudhuri - Logics and Algorithms for Software Model Checking 1:06:18

cách đây 3 years trước1:06:18

1:06:18

Swarat Chaudhuri is an Associate Professor at the University of Texas. His lab studies problems at the interface of programming languages, logic and formal methods, and machine learning. Swarat's PhD thesis is titled "Logics and Algorithms for Software Model Checking", which he completed in 2007 at the University of Pennsylvania. We discuss reasoning about programs, formal methods & safer machine learning systems, and the future of program synthesis & neurosymbolic programming. - Episode notes: www.wellecks.com/thesisreview/episode43.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[42] Charles Sutton - Efficient Training Methods for Conditional Random Fields 1:18:01

cách đây 3 years trước1:18:01

1:18:01

Charles Sutton is a Research Scientist at Google Brain and an Associate Professor at the University of Edinburgh. His research focuses on deep learning for generating code and helping people write better programs. Charles' PhD thesis is titled "Efficient Training Methods for Conditional Random Fields", which he completed in 2008 at UMass Amherst. We start with his work in the thesis on structured models for text, and compare/contrast with today's large language models. From there, we discuss machine learning for code & the future of language models in program synthesis. - Episode notes: https://cs.nyu.edu/~welleck/episode42.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[41] Talia Ringer - Proof Repair 1:19:02

cách đây 3 years trước1:19:02

1:19:02

Talia Ringer is an Assistant Professor with the Programming Languages, Formal Methods, and Software Engineering group at University of Illinois Urbana-Champaign. Her research focuses on formal verification and proof engineering technologies. Talia's PhD thesis is titled "Proof Repair", which she completed in 2021 at the University of Washington. We discuss software verification and her PhD work on proof repair for maintaining verified systems, and discuss the intersection of machine learning with her work. - Episode notes: https://cs.nyu.edu/~welleck/episode41.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[40] Lisa Lee - Learning Embodied Agents with Scalably-Supervised RL 46:59

cách đây 3 years trước46:59

46:59

Lisa Lee is a Research Scientist at Google Brain. Her research focuses on building AI agents that can learn and adapt like humans and animals do. Lisa's PhD thesis is titled "Learning Embodied Agents with Scalably-Supervised Reinforcement Learning", which she completed in 2021 at Carnegie Mellon University. We talk about her work in the thesis on reinforcement learning, including exploration, learning with weak supervision, and embodied agents, and cover various topics related to trends in reinforcement learning. - Episode notes: https://cs.nyu.edu/~welleck/episode40.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[39] Burr Settles - Curious Machines: Active Learning with Structured Instances 1:06:33

cách đây 3 years trước1:06:33

1:06:33

Burr Settles leads the research group at Duolingo, a language-learning website and mobile app whose mission is to make language education free and accessible to everyone. Burr’s PhD thesis is titled "Curious Machines: Active Learning with Structured Instances", which he completed in 2008 at the University of Wisconsin-Madison. We talk about his work in the thesis on active learning, then chart the path to Burr’s role at DuoLingo. We discuss machine learning for education and language learning, including content, assessment, and the exciting possibilities opened by recent advancements. - Episode notes: https://cs.nyu.edu/~welleck/episode39.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[38] Andrew Lampinen - A Computational Framework for Learning and Transforming Task Representations 1:04:47

cách đây 3 years trước1:04:47

1:04:47

Andrew Lampinen is a research scientist at DeepMind. His research focuses on cognitive flexibility and generalization. Andrew’s PhD thesis is titled "A Computational Framework for Learning and Transforming Task Representations", which he completed in 2020 at Stanford University. We talk about cognitive flexibility in brains and machines, centered around his work in the thesis on meta-mapping. We cover a lot of interesting ground, including complementary learning systems and memory, compositionality and systematicity, and the role of symbols in machine learning. - Episode notes: https://cs.nyu.edu/~welleck/episode38.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

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[37] Joonkoo Park - Neural Substrates of Visual Word and Number Processing 1:09:28

cách đây 3 years trước1:09:28

1:09:28

Joonkoo Park is an Associate Professor and Honors Faculty in the Department of Psychological and Brain Sciences at UMass Amherst. He leads the Cognitive and Developmental Neuroscience Lab, focusing on understanding the developmental mechanisms and neurocognitive underpinnings of our knowledge about number and mathematics. Joonkoo’s PhD thesis is titled "Experiential Effects on the Neural Substrates of Visual Word and Number Processing", which he completed in 2011 at the University of Michigan. We talk about numerical processing in the brain, starting with nature vs. nurture, including the learned versus built-in aspects of neural architectures. We talk about the difference between word and number processing, types of numerical thinking, and symbolic vs. non-symbolic numerical processing. - Episode notes: https://cs.nyu.edu/~welleck/episode37.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[36] Dieuwke Hupkes - Hierarchy and Interpretability in Neural Models of Language Processing 1:02:26

cách đây 3 years trước1:02:26

1:02:26

Dieuwke Hupkes is a Research Scientist at Facebook AI Research and the scientific manager of the Amsterdam unit of ELLIS. Dieuwke's PhD thesis is titled, "Hierarchy and Interpretability in Neural Models of Language Processing", which she completed in 2020 at the University of Amsterdam. We discuss her work on which aspects of hierarchical compositionality and syntactic structure can be learned by recurrent neural networks, how these models can serve as explanatory models of human language processing, what compositionality actually means, and a lot more. - Episode notes: https://cs.nyu.edu/~welleck/episode36.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[35] Armando Solar-Lezama - Program Synthesis by Sketching 1:15:56

cách đây 3 years trước1:15:56

1:15:56

Armando Solar-Lezama is a Professor at MIT, and the Associate Director & COO of CSAIL. He leads the Computer Assisted Programming Group, focused on program synthesis. Armando’s PhD thesis is titled, "Program Synthesis by Sketching", which he completed in 2008 at UC Berkeley. We talk about program synthesis & his work on Sketch, how machine learning's role in program synthesis has evolved over time, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode35.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[34] Sasha Rush - Lagrangian Relaxation for Natural Language Decoding 1:08:12

cách đây 3 years trước1:08:12

1:08:12

Sasha Rush is an Associate Professor at Cornell Tech and researcher at Hugging Face. His research focuses on building NLP systems that are safe, fast, and controllable. Sasha's PhD thesis is titled, "Lagrangian Relaxation for Natural Language Decoding", which he completed in 2014 at MIT. We talk about his work in the thesis on decoding in NLP, how it connects with today, and many interesting topics along the way such as the role of engineering in machine learning, breadth vs. depth, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode34.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

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[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models