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
Generative Ai
[2602.22226] SEGB: Self-Evolved Generative Bidding with Local Autoregressive Diffusion
The paper presents Self-Evolved Generative Bidding (SEGB), a novel framework for automated online advertising that enhances bidding strat...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.22263] CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints
CryoNet.Refine introduces a one-step diffusion model for efficiently refining structural models using cryo-EM density maps, offering a si...
arXiv - AI
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4 min
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Llms
[2602.22242] Analysis of LLMs Against Prompt Injection and Jailbreak Attacks
This paper analyzes the vulnerabilities of Large Language Models (LLMs) to prompt injection and jailbreak attacks, evaluating various def...
arXiv - AI
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3 min
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Llms
[2602.22240] From Prompts to Performance: Evaluating LLMs for Task-based Parallel Code Generation
This paper evaluates the performance of Large Language Models (LLMs) in generating task-based parallel code using various input prompts a...
arXiv - AI
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3 min
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Machine Learning
[2602.22235] Unsupervised Denoising of Diffusion-Weighted Images with Bias and Variance Corrected Noise Modeling
This article presents a novel approach for unsupervised denoising of diffusion-weighted images (dMRI) by addressing noise bias and varian...
arXiv - AI
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4 min
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Llms
[2602.22219] Comparative Analysis of Neural Retriever-Reranker Pipelines for Retrieval-Augmented Generation over Knowledge Graphs in E-commerce Applications
This article presents a comparative analysis of neural retriever-reranker pipelines for retrieval-augmented generation (RAG) in e-commerc...
arXiv - AI
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4 min
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Nlp
[2602.22220] What Makes an Ideal Quote? Recommending "Unexpected yet Rational" Quotations via Novelty
This article presents a novel framework for recommending quotations that are both unexpected and rational, enhancing the writing experien...
arXiv - AI
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4 min
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Llms
[2602.22217] RAGdb: A Zero-Dependency, Embeddable Architecture for Multimodal Retrieval-Augmented Generation on the Edge
The paper presents RAGdb, a novel architecture for Retrieval-Augmented Generation (RAG) that simplifies multimodal data processing by eli...
arXiv - AI
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4 min
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Machine Learning
[2602.23142] Prediction of Diffusion Coefficients in Mixtures with Tensor Completion
This paper presents a hybrid tensor completion method for predicting temperature-dependent diffusion coefficients in binary mixtures, enh...
arXiv - Machine Learning
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4 min
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Nlp
[2602.22216] Retrieval-Augmented Generation Assistant for Anatomical Pathology Laboratories
This article discusses a Retrieval-Augmented Generation (RAG) assistant designed for Anatomical Pathology laboratories, enhancing access ...
arXiv - AI
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4 min
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Llms
[2602.23193] ESAA: Event Sourcing for Autonomous Agents in LLM-Based Software Engineering
The paper presents ESAA, an architecture for autonomous agents using event sourcing to enhance state management and execution in LLM-base...
arXiv - AI
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4 min
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Machine Learning
[2602.23152] The Trinity of Consistency as a Defining Principle for General World Models
This paper proposes the 'Trinity of Consistency' as a foundational principle for developing General World Models in AI, emphasizing modal...
arXiv - AI
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4 min
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Llms
[2602.22983] Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search
This paper explores the vulnerabilities of Large Language Models (LLMs) to jailbreak attacks using classical Chinese prompts, proposing a...
arXiv - AI
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4 min
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Llms
[2602.22681] Accelerating LLM Pre-Training through Flat-Direction Dynamics Enhancement
This paper introduces LITE, a new strategy for accelerating the pre-training of large language models (LLMs) by optimizing training dynam...
arXiv - Machine Learning
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4 min
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Llms
[2602.22897] OmniGAIA: Towards Native Omni-Modal AI Agents
The paper introduces OmniGAIA, a benchmark for evaluating omni-modal AI agents that integrate vision, audio, and language for complex rea...
arXiv - Machine Learning
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3 min
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Ai Agents
[2602.22842] The AI Research Assistant: Promise, Peril, and a Proof of Concept
This article explores the role of AI in mathematical research, highlighting both its capabilities and limitations through a case study on...
arXiv - AI
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3 min
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Ai Agents
[2602.22839] DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation
DeepPresenter introduces an innovative framework for generating presentations that adapts to user needs and incorporates environmental fe...
arXiv - AI
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3 min
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Llms
[2602.22617] Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
The paper introduces Semantic Tube Prediction (STP), a method that enhances data efficiency in large language models (LLMs) by constraini...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.22610] DP-aware AdaLN-Zero: Taming Conditioning-Induced Heavy-Tailed Gradients in Differentially Private Diffusion
The paper introduces DP-aware AdaLN-Zero, a novel mechanism to mitigate heavy-tailed gradients in differentially private diffusion models...
arXiv - Machine Learning
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4 min
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Machine Learning
[2602.22601] $ϕ$-DPO: Fairness Direct Preference Optimization Approach to Continual Learning in Large Multimodal Models
The paper presents the $ϕ$-DPO framework, addressing fairness in continual learning for large multimodal models by optimizing preference ...
arXiv - Machine Learning
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4 min
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