Generative Ai
Inside OpenAI's decision to abandon Sora AI video app
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Reddit - Artificial Intelligence
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1 min
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Generative AI
Image, video, audio, and text generation
Top This Week
Machine Learning
Accelerating science with AI and simulations
MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...
AI News - General
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10 min
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![[2603.12057] Coarse-Guided Visual Generation via Weighted h-Transform Sampling](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Machine Learning
[2603.12057] Coarse-Guided Visual Generation via Weighted h-Transform Sampling
Abstract page for arXiv paper 2603.12057: Coarse-Guided Visual Generation via Weighted h-Transform Sampling
arXiv - AI
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4 min
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All Content
Llms
Is Claude Down? Outage Reports Briefly Spike For Anthropic’s AI
Anthropic's AI chatbot, Claude, experienced a brief outage affecting thousands of users. The company reported a fix was deployed shortly ...
AI Tools & Products
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2 min
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Llms
Responsible Scaling Policy Version 3.0
Anthropic releases Version 3.0 of its Responsible Scaling Policy, aimed at addressing evolving AI risks and enhancing transparency and ac...
AI Tools & Products
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12 min
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Llms
[D] Mobile-MCP: Letting LLMs autonomously discover Android app capabilities (no pre-coordination required)
The article discusses Mobile-MCP, a framework allowing LLMs to autonomously discover Android app capabilities without pre-coordination, e...
Reddit - Machine Learning
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1 min
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Llms
[2510.22049] Massive Memorization with Hundreds of Trillions of Parameters for Sequential Transducer Generative Recommenders
This paper presents VISTA, a novel two-stage modeling framework for generative recommenders that enhances scalability by summarizing user...
arXiv - Machine Learning
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4 min
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Machine Learning
[2510.21686] Multimodal Datasets with Controllable Mutual Information
This paper presents a framework for generating multimodal datasets with controllable mutual information, enhancing the study of mutual in...
arXiv - Machine Learning
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3 min
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Machine Learning
[2506.19881] Blameless Users in a Clean Room: Defining Copyright Protection for Generative Models
This paper explores the concept of copyright protection for generative models, introducing a framework that defines conditions under whic...
arXiv - Machine Learning
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4 min
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Llms
[2505.22811] Highly Efficient and Effective LLMs with Multi-Boolean Architectures
The paper presents a novel framework for large language models (LLMs) using multi-kernel Boolean parameters, enhancing efficiency and eff...
arXiv - Machine Learning
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3 min
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Nlp
[2505.04382] Discrete Optimal Transport and Voice Conversion
This paper introduces kDOT, a discrete optimal transport framework for voice conversion, demonstrating improved performance over traditio...
arXiv - Machine Learning
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4 min
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Machine Learning
[2504.17203] High-Fidelity And Complex Test Data Generation For Google SQL Code Generation Services
This paper presents a method for generating high-fidelity test data for SQL code generation services, addressing limitations of tradition...
arXiv - Machine Learning
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4 min
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Llms
[2304.14347] The Dark Side of ChatGPT: Legal and Ethical Challenges from Stochastic Parrots and Hallucination
The article discusses the legal and ethical challenges posed by Large Language Models (LLMs) like ChatGPT, highlighting issues such as st...
arXiv - Machine Learning
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3 min
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Machine Learning
[2601.13780] Principled Latent Diffusion for Graphs via Laplacian Autoencoders
This paper presents LG-Flow, a novel latent graph diffusion framework that enhances graph generation efficiency by compressing graphs int...
arXiv - Machine Learning
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4 min
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Llms
[2512.16762] NRGPT: An Energy-based Alternative for GPT
The paper presents NRGPT, an energy-based alternative to GPT, proposing a novel approach that integrates energy-based modeling with langu...
arXiv - Machine Learning
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3 min
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Llms
[2509.21865] Beyond RAG vs. Long-Context: Learning Distraction-Aware Retrieval for Efficient Knowledge Grounding
This paper introduces LDAR, a new retrieval method that enhances the efficiency of knowledge grounding in Large Language Models (LLMs) by...
arXiv - Machine Learning
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4 min
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Machine Learning
[2508.21438] Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
This article presents a novel framework using quantum-enhanced ensemble GANs for unsupervised anomaly detection in continuous biomanufact...
arXiv - Machine Learning
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4 min
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Machine Learning
[2508.04605] Multitask Learning with Stochastic Interpolants
This article presents a new framework for multitask learning using stochastic interpolants, enhancing generative models' capabilities acr...
arXiv - Machine Learning
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3 min
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Machine Learning
[2506.21427] Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning
The paper presents the Single-Step Completion Policy (SSCP), a novel approach in reinforcement learning that enhances efficiency and expr...
arXiv - Machine Learning
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4 min
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Nlp
[2506.22685] Mitigating Semantic Collapse in Generative Personalization with Test-Time Embedding Adjustment
This paper addresses the issue of semantic collapse in generative personalization, proposing a method to adjust embeddings at inference t...
arXiv - Machine Learning
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4 min
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Machine Learning
[2502.12981] Riemannian Variational Flow Matching for Material and Protein Design
The paper presents Riemannian Gaussian Variational Flow Matching (RG-VFM), a novel approach for generative modeling on curved manifolds, ...
arXiv - Machine Learning
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4 min
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Llms
[2602.22157] Dynamic Personality Adaptation in Large Language Models via State Machines
This paper presents a model-agnostic framework for dynamic personality adaptation in Large Language Models (LLMs) using state machines, e...
arXiv - Machine Learning
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4 min
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Machine Learning
[2602.22122] Probing the Geometry of Diffusion Models with the String Method
This article presents a novel framework using the string method to explore the geometry of diffusion models, enhancing understanding and ...
arXiv - Machine Learning
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4 min
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