Reinforcement Learning: How Machines Learn to Make Smart Choices Like You Do
dev.to·1h·
Discuss: DEV
📱Edge AI
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Information Gain-based Policy Optimization: A Simple and Effective Approach forMulti-Turn LLM Agents
paperium.net·1d·
Discuss: DEV
💬Prompt Engineering
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Neural Green's Functions
arxiv.org·11h
🧮Embeddings
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Beyond Standard LLMs
magazine.sebastianraschka.com·1d·
Discuss: Hacker News, r/LLM
🤖Transformers
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Optimizing Thin-Film Deposition via Adaptive Q-Learning for E-Beam Evaporation
dev.to·19h·
Discuss: DEV
💬Prompt Engineering
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Post-training methods for language models
developers.redhat.com·1d
💬Prompt Engineering
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Adaptive Neighborhood-Constrained Q Learning for Offline Reinforcement Learning
arxiv.org·11h
📊Dynamic Programming
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Enhancing Diffusion-based Restoration Models via Difficulty-Adaptive Reinforcement Learning with IQA Reward
arxiv.org·1d
📱Edge AI
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Logic-informed reinforcement learning for cross-domain optimization of large-scale cyber-physical systems
arxiv.org·1d
💬Prompt Engineering
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The Next Frontier in NLP: Smarter Agents, Not Just Bigger Models
pub.towardsai.net·11h
💬Prompt Engineering
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Reinforcement Learning: Why It's Quietly Powering the AI Revolution
dev.to·1h·
Discuss: DEV
🛡️AI Security
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Topographical sparse mapping: A training framework for deep learning models
sciencedirect.com·19h·
Discuss: Hacker News
👁️Computer Vision
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Algorithmic Alchemy: Transmuting Dynamic Programming with Gradients by Arvind Sundararajan
dev.to·23h·
Discuss: DEV
📊Dynamic Programming
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Augmenting learning in neuro-embodied systems through neurobiological first principles
arxiv.org·1d
🔲Cellular Automata
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Dynamic Model Selection for Trajectory Prediction via Pairwise Ranking and Meta-Features
arxiv.org·1d
🧠Machine Learning
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SAIL-RL: Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning
arxiv.org·11h
💬Prompt Engineering
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
towardsdatascience.com·21h
Incremental Computation
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A brief guide for those who slept (on AI) the last two years
github.com·1h·
Discuss: DEV
💬Prompt Engineering
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[D] Trajectory Distillation for Foundation Models
reddit.com·6h·
💬Prompt Engineering
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