Deep Reinforcement Learning Book
deepreinforcementlearningbook.org·5d·
Discuss: Hacker News
🔀Transformers
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Logic Theorist: The program that rewrote the foundations of mathematics
bigthink.com·20h
🤖AI
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'Building a sandcastle at high tide': What one fund manager thinks needs to happen for the AI rally to endure
businessinsider.com·2h
🤖AI
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The Advent Of ‘Thinking Tokens’ Causes Unforeseen Inflationary Impact On Generative AI
forbes.com·4h
🔀Transformers
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It Doesn’t Need to Be a Chatbot
towardsdatascience.com·1d
🔀Transformers
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Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
arxiv.org·1d
📈Time Series
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A generative AI teaching assistant for personalized learning in medical education
nature.com·1d
🔀Transformers
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Artificial intelligence: Nirvana or apocalypse?
mathscholar.org·14h
🤖AI
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Investigating Search Among Physical and Virtual Objects Under Different Lighting Conditions
arxiv.org·1d
🔀Transformers
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On Improvisation and Open-Endedness: Insights for Experiential AI
arxiv.org·1d
🤖AI
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Enhancing Hierarchical Reinforcement Learning through Change Point Detection in Time Series
arxiv.org·6d
📈Time Series
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Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning (Paper Review)
pub.towardsai.net·3d
🔀Transformers
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I Want to Break Free! Persuasion and Anti-Social Behavior of LLMs in Multi-Agent Settings with Social Hierarchy
arxiv.org·7h
🔀Transformers
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QuantumScape: A Convex Long On The Future Of Solid-State Energy
seekingalpha.com·4h
🏗️Data Engineering
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Visual Backdoor Attacks on MLLM Embodied Decision Making via Contrastive Trigger Learning
arxiv.org·2d
🤖AI
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Online Energy Storage Arbitrage under Imperfect Predictions: A Conformal Risk-Aware Approach
arxiv.org·1d
🌐Distributed Systems
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KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
arxiv.org·7h
🧭Vector Databases
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Hydra: Dual Exponentiated Memory for Multivariate Time Series Analysis
arxiv.org·1d
📈Time Series
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Explore More, Learn Better: Parallel MLLM Embeddings under Mutual Information Minimization
arxiv.org·1d
🤖ML
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Physics-Informed Neural Network Frameworks for the Analysis of Engineering and Biological Dynamical Systems Governed by Ordinary Differential Equations
arxiv.org·1d
🔧Feature Engineering
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