Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024
AI Today27 Marras 2024

Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024

Paper: https://arxiv.org/pdf/2408.04498 This research introduces Model-Based Transfer Learning (MBTL), a novel framework for improving the efficiency and robustness of deep reinforcement learning (RL) in contextual Markov Decision Processes (CMDPs). MBTL strategically selects training tasks to maximize generalization performance across a range of tasks by modeling both the performance set point using Gaussian processes and the generalization gap as a function of contextual similarity. Theoretical analysis proves sublinear regret, and experiments on urban traffic and continuous control benchmarks demonstrate significant sample efficiency improvements (up to 50x) compared to traditional methods. The method's effectiveness is shown to be relatively insensitive to the underlying RL algorithm and hyperparameters. ai , model , mit, genai, generativeai, artificialintelligence , arxiv , research , paper , publication, reinforcement learning, rl , ml

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OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

Blog: https://openai.com/12-days/ OpenAI announced two new large language models, o3 and o3-mini, showcasing significantly improved performance on various benchmarks, including coding, mathematics, ...

21 Joulu 202422min

Alignment Faking in Large Language Models | #ai #2024 #genai

Alignment Faking in Large Language Models | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2412.14093 This research paper explores "alignment faking" in large language models (LLMs). The authors designed experiments to provoke LLMs into concealing their true pr...

21 Joulu 202414min

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Blog: https://blog.google/technology/google... Google announced updates to its AI video and image generation models, Veo 2 and Imagen 3, boasting state-of-the-art capabilities in realism and style d...

21 Joulu 202419min

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 This research report introduces Allegro, a novel, open-source text-to-video generation model that surpasses existing open-source and many commercial models in ...

4 Joulu 202419min

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 The paper "DynaSaur: Large Language Agents Beyond Predefined Actions" introduces a novel large language model (LLM) agent framework that dynamically generates ...

4 Joulu 202419min

STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai

STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.17116 The paper introduces Star Attention, a novel two-phase attention mechanism for efficient Large Language Model (LLM) inference on long sequences. It improves co...

4 Joulu 202416min

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2410.18967 The paper introduces Ferret-UI 2, a multimodal large language model (MLLM) that significantly improves upon its predecessor, Ferret-UI, by enabling universal u...

27 Marras 202414min

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Paper: https://arxiv.org/abs/2411.00412 This research introduces a novel two-stage training method to improve Large Language Models' (LLMs) ability to solve complex scientific problems. The method, c...

27 Marras 202414min