[34] James Fogarty, Desney Tan, Ashish Kapoor, and Simon Winder. 2008. CueFlik:Interactive Concept Learning in Image Search. In Proceedings of the SIGCHIConference on Human Factors in Computing Systems (Florence, Italy) (CHI ’08).Association for Computing Machinery, New York, NY, USA, 29–...
continual learning; selective amnesia; machine unlearning; generative model1. Introduction The rapid advances in deep learning technology have enabled the development of various models for different applications [1,2,3]. These models often equal or exceed human capabilities, particularly in the fields ...
Some practitioners view hallucinations as an unavoidable consequence of balancing a model’s accuracy and its creative capabilities. But developers may implement preventative measures, calledguardrails, that restrict the model to relevant or trusted data sources.Continual evaluation and tuning can also help...
I hope that you have found useful this fast overview of the Generative AI course provided by Google Cloud. If you don’t know where to start in understanding the core concepts of Generative AI, this path covers every aspect. In case you have already a machine learning background, there are...
Federated Learning (FL) aims at unburdening the training of deep models by distributing computation across multiple devices (clients) while safeguarding data privacy. On top of that, Federated Continual Learning (FCL) also accounts for data distribution evolving over time, mirroring the dynamic nature...
Doing so might also allow the machine learning community to make further progress on problems even harder than generative modeling, such as the problem of learning from sparse reward signals (active inference54,55) and continual temporal prediction2....
Fine-tuning Llama 2 70B using this approach yields a model that surpasses existing systems on the AlpacaEval 2.0 leaderboard, showcasing potential for continual improvement in both performance axes. Prompt Engineering 16 Jan 2024 Code Generation with AlphaCodium: From Prompt Engineering to Flow ...
the model not only improves its instruction-following ability but also enhances its capacity to generate high-quality rewards. Fine-tuning Llama 2 70B using this approach yields a model that surpasses existing systems on the AlpacaEval 2.0 leaderboard, showcasing potential for continual improvement in...
(between top–down prediction and bottom–up recognition), potentially allowing learning of concepts and exceptions at all levels of description. Fourth, considering consolidation as a continual lifelong process rather than during encoding of a single dataset introduces new complexities; these include the...
03/05 - Interactive Continual Learning: Fast and Slow Thinking (❌), (📖), (📎), (📙), (🏠), (HTML), (SL), (SP), (GS), (SS), (✳️) 03/05 - InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents (❌), (📖), (📎...