Image, video, audio, and text generation
There’s been a lot of discussion recently about how expensive AI video generation is compared to text, and it feels like this is more tha...
MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...
![[2603.10202] Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Approach with Jump-Diffusion](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.10202: Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Ap...
This paper explores how Discrete Diffusion Models (NAR) outperform Autoregressive models (AR) in lookahead planning tasks by leveraging a...
BiMotion introduces a novel approach to dynamic 3D character generation using B-spline curves, enhancing motion quality and alignment wit...
DUET-VLM introduces a dual-stage token reduction framework for vision-language models, enhancing efficiency without sacrificing accuracy ...
This article explores the use of diffusion models to enhance adversarial training for robust image classifiers, demonstrating improved pe...
The paper presents DSDR, a novel reinforcement learning framework aimed at enhancing exploration in large language model (LLM) reasoning ...
The paper presents MANATEE, a novel defense mechanism for large language models (LLMs) against adversarial attacks, utilizing a lightweig...
The paper presents a novel pipeline for synthesizing multimodal geometry datasets, introducing the GeoCode dataset which enhances visual-...
This paper proposes a novel framework called Cooperative Retrieval-Augmented Generation (CoRAG), which reformulates retrieval-augmented g...
PerturbDiff introduces a novel approach to modeling single-cell responses to perturbations by utilizing a diffusion-based generative proc...
The EDU-MATRIX paper presents a novel generative cognitive digital twin architecture aimed at enhancing secondary education through a soc...
This paper introduces Semantic Substrate Theory, an operator-theoretic framework that formalizes various signals of semantic drift, integ...
This study investigates the experiences of blind users with DIY manuals and AI-generated instructions for assembling and troubleshooting ...
This article evaluates the accuracy of discrete diffusion language models (dLLMs) through a sampler-centric framework, revealing signific...
This study evaluates the effectiveness of AI and accessibility forums for blind users, highlighting user experiences and identifying supp...
The paper presents DM4CT, a benchmark for evaluating diffusion models in computed tomography (CT) reconstruction, addressing practical ch...
The paper introduces 1D-Bench, a benchmark for evaluating iterative UI code generation with visual feedback, aimed at improving design-to...
This paper presents a variational framework for optimizing anisotropic diffusion schedules in machine learning, enhancing performance acr...
This article presents a case study on the security implications of Indirect Prompt Injection (IPI) in Large Language Models (LLMs) used i...
The article examines red teaming as a socio-technical practice in evaluating large language models (LLMs), highlighting the importance of...
The paper presents ZUNA, a 380M-parameter masked diffusion autoencoder designed for EEG signal superresolution and channel infilling, dem...
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