#machineunlearning search results
What if AI didn’t just think - but forgot? 🤯 Imagine models designed to unlearn outdated ideas, bad data, and yesterday’s biases - evolving in real-time like living minds. Not just smarter, but wiser. Just a thought. #AI #MachineUnlearning #FutureTech #EthicalAI #NextGenAI
How Machine Unlearning Revolutionizes AI Integrity bit.ly/4oXpwWi #MachineUnlearning #FairAI #ResponsibleAI #EthicalAI #AIBiasMitigation #TrustworthyAI #AIForGood #ExplainableAI #AIEthics #Smartsystems
(3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning: - It produces calibrated scores without referencing the retrained model; - The signal is orthogonal to model performance & applicable even with similar data. (4/n)
(1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n) #LLM
When a company claims that your personal data has been removed from their model, have you ever wondered whether they've indeed done so? 🤔 If a new paper on arXiv claims that its proposed #MachineUnlearning algorithm can unlearn your personal data from an #LLM, how do we know…
I am happy to share that our paper, "Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models", has been accepted to #ICLR2025! Stay tuned for the camera-ready version and the code release! #MachineUnlearning #LLMs
In the era of Large Language Models (LLMs) like ChatGPT, deleting users' data is a complicated beast. We're designing solutions to help LLMs forget, advancing #machineunlearning techniques to protect the #righttobeforgotten. 🔗 spr.ly/6017P2VoU
"Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI Read the full article…
🎉 Proud to share that Side Effects of Erasing Concepts from Diffusion Models was accepted to EMNLP 2025 (Findings). #EMNLP2025 #MachineUnlearning #ConceptErasure
🚨 Our paper “Side Effects of Erasing Concepts from Diffusion Models” has been accepted to EMNLP 2025 (Findings)! #EMNLP2025 We investigate the vulnerabilities of Concept Erasure Techniques (CETs) Big shoutout to my amazing collaborators @sourajitCS @manasgaur90 @trgokhale 1/n
🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽
A comprehensive look into machine unlearning as a tool for improving AI safety by strategically removing specific data influence. #AISafety #MachineUnlearning #KnowledgeRemoval
Goldfish, an efficient federated unlearning framework, addresses data removal constraints while maintaining performance. #MachineUnlearning #DataPrivacy #FederatedLearning
Q: What techniques can be used for machine unlearning? A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning. @MichaelDell #MachineUnlearning
@juandoming EL MACHINE UNLEARNING EN LA EDUCACIÓN DISRUPTIVA: facebook.com/juandon/posts/… #machineUnlearning #Educaciondisruptiva #educación #algoritmos #IA #desaprendizaje
AI models use machine unlearning to forget specific data while preserving performance, respecting privacy and user preferences. Learn more at ez.works #MachineUnlearning #AIRespectPrivacy
🚨 ACM India Industry Webinar Alert! Join us for an insightful talk on Machine Unlearning & Multimodal Negation in GenAI 🤖🧠 🗓️ June 21, 2025 🕚 11:00 AM IST 🎙️ Prof. Mayank Vatsa, IIT Jodhpur 🔗 Register: lnkd.in/dqNHBBzG #ACMIndia #GenAI #MachineUnlearning #AIethics
How Machine Unlearning Revolutionizes AI Integrity bit.ly/4oXpwWi #MachineUnlearning #FairAI #ResponsibleAI #EthicalAI #AIBiasMitigation #TrustworthyAI #AIForGood #ExplainableAI #AIEthics #Smartsystems
🎉 Proud to share that Side Effects of Erasing Concepts from Diffusion Models was accepted to EMNLP 2025 (Findings). #EMNLP2025 #MachineUnlearning #ConceptErasure
🚨 Our paper “Side Effects of Erasing Concepts from Diffusion Models” has been accepted to EMNLP 2025 (Findings)! #EMNLP2025 We investigate the vulnerabilities of Concept Erasure Techniques (CETs) Big shoutout to my amazing collaborators @sourajitCS @manasgaur90 @trgokhale 1/n
What if AI didn’t just think - but forgot? 🤯 Imagine models designed to unlearn outdated ideas, bad data, and yesterday’s biases - evolving in real-time like living minds. Not just smarter, but wiser. Just a thought. #AI #MachineUnlearning #FutureTech #EthicalAI #NextGenAI
AI text-to-speech could soon 'unlearn' to mimic voices, a game-changer in the fight against audio deepfakes. #MachineUnlearning #AISafety
महत्त्वपूर्ण शब्दावली: मशीन अनलर्निंग (Machine Unlearning) sanskritiias.com/hindi/importan… #MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias
When a company claims that your personal data has been removed from their model, have you ever wondered whether they've indeed done so? 🤔 If a new paper on arXiv claims that its proposed #MachineUnlearning algorithm can unlearn your personal data from an #LLM, how do we know…
A look at how a new framework makes #MachineUnlearning faster, more practical, and privacy-compliant for real-world #AI systems. @helpnetsecurity helpnetsecurity.com/2025/07/17/mac…
AI Voice Models May Forget How to Mimic Specific Voices digitrendz.blog/?p=27215 #AiVoiceModels #MachineUnlearning #VoiceboxModification
Fighting Audio Deepfakes & AI’s Role in Education digitrendz.blog/?p=27213 #AiInEducation #AudioDeepfakes #MachineUnlearning #VoiceCloningScams
Exploring #MachineUnlearning teaching AI to forget on demand. Mapping privacy-first needs across finance, governance, startups & enterprises. Know a use case? Let’s chat and co-create value—open to partnerships that help us all generate leads! #DataPrivacy #GDPR #TrustworthyAI
✨ A heartfelt thank you to our mentor Shaista Tarannum for her constant guidance, insightful feedback, and support throughout this journey. 🙌 Special thanks to my amazing teammates: Varsha D R, Vidya Shree M S, Ananya K #AI #MachineUnlearning #groupaproject
🚨 ACM India Industry Webinar Alert! Join us for an insightful talk on Machine Unlearning & Multimodal Negation in GenAI 🤖🧠 🗓️ June 21, 2025 🕚 11:00 AM IST 🎙️ Prof. Mayank Vatsa, IIT Jodhpur 🔗 Register: lnkd.in/dqNHBBzG #ACMIndia #GenAI #MachineUnlearning #AIethics
(3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning: - It produces calibrated scores without referencing the retrained model; - The signal is orthogonal to model performance & applicable even with similar data. (4/n)
(1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n) #LLM
🤖 #MachineUnlearning: un sogno quasi impossibile di cancellarsi dalla memoria dell'IA. Un viaggio tra privacy e tecnologia. #IAPrivacy tomshw.it/business/cance…
The Revolutionary Shift from Traditional ML to Machine Unlearning: Uncover How This New Approach Guarantees Data Privacy and Compliance in AI Systems medium.com/ai-simplified-… #MachineLearning #MachineUnlearning #ML
7/ Huge thanks to the AAAI committee for the opportunity to present. Excited to keep pushing boundaries in AI + memory + privacy. #AI #MachineLearning #MachineUnlearning #AAAI2025 #NeuroscienceInspiredAI
Machine Unlearning Explained: How This Groundbreaking Approach Revolutionizes Data Privacy in Machine Learning Models medium.com/p/machine-unle… #MachineUnlearning #MachineLearning #ML #Tech #Technology
I am excited to share my recent paper on #MachineUnlearning in classification! Highlighting the limitations of logit-based evaluations with small-scale datasets, the paper introduces a unified evaluation metric that includes rep.-based evaluations. arxiv.org/abs/2503.06991
How Machine Unlearning Revolutionizes AI Integrity bit.ly/4oXpwWi #MachineUnlearning #FairAI #ResponsibleAI #EthicalAI #AIBiasMitigation #TrustworthyAI #AIForGood #ExplainableAI #AIEthics #Smartsystems
bit.ly/2dRw9rj #Cybersecurity via #machineunlearning! bit.ly/2dJmwvs @LehighCSE #compsci #DataSecurity #DataScience
(1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n) #LLM
(3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning: - It produces calibrated scores without referencing the retrained model; - The signal is orthogonal to model performance & applicable even with similar data. (4/n)
Recommendation from @Spotify, of album I've already heard on their service a couple of times. #MachineUnlearning
🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽
I am happy to share that our paper, "Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models", has been accepted to #ICLR2025! Stay tuned for the camera-ready version and the code release! #MachineUnlearning #LLMs
Q: What techniques can be used for machine unlearning? A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning. @MichaelDell #MachineUnlearning
"Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI Read the full article…
The #AISTATS2022 paper of @CYZ798775190 Shizhuo @bryanklow proposes an active task selection algorithm for #MetaLearning with a provable performance guarantee that is based on mutual information and online variational Bayesian #MachineUnlearning.
महत्त्वपूर्ण शब्दावली: मशीन अनलर्निंग (Machine Unlearning) sanskritiias.com/hindi/importan… #MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias
🚨 ACM India Industry Webinar Alert! Join us for an insightful talk on Machine Unlearning & Multimodal Negation in GenAI 🤖🧠 🗓️ June 21, 2025 🕚 11:00 AM IST 🎙️ Prof. Mayank Vatsa, IIT Jodhpur 🔗 Register: lnkd.in/dqNHBBzG #ACMIndia #GenAI #MachineUnlearning #AIethics
Postdoc, RA & Ph.D. positions in Collaborative ML/#FederatedLearning, Data Valuation, Incentive-Aware Mechanism Design, #MachineUnlearning @NUSComputing See groups.google.com/u/3/g/ml-news/… #NeurIPS2021 #ICML2021 #AAAI2021 #IJCAI2021 #UAI2021 #AISTATS2021
As LLMs like ChatGPT evolve, compliance with GDPR's data deletion rules presents complex challenges. Emerging machine unlearning aims to help models forget specific data without full retraining. 🤖 #MachineUnlearning #GDPR #AI_regulation link: ift.tt/V6BxpjH
Q: What challenges are associated with machine unlearning in deep learning models? A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning. #MachineUnlearning #Challenges @pmarca @bhorowitz @elonmusk
A comprehensive look into machine unlearning as a tool for improving AI safety by strategically removing specific data influence. #AISafety #MachineUnlearning #KnowledgeRemoval
Goldfish, an efficient federated unlearning framework, addresses data removal constraints while maintaining performance. #MachineUnlearning #DataPrivacy #FederatedLearning
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