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
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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
[2602.22732] Generative Recommendation for Large-Scale Advertising
This paper introduces GR4AD, a generative recommendation system designed for large-scale advertising, enhancing ad revenue through innova...
arXiv - Machine Learning
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4 min
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Llms
[2602.22661] dLLM: Simple Diffusion Language Modeling
The paper introduces dLLM, an open-source framework for diffusion language modeling that standardizes core components, facilitating repro...
arXiv - Machine Learning
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3 min
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Machine Learning
[2602.22570] Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation
The paper discusses the evaluation challenges in text-to-image generation, focusing on classifier-free guidance (CFG) and proposing a new...
arXiv - AI
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4 min
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Llms
[2602.22647] Vectorizing the Trie: Efficient Constrained Decoding for LLM-based Generative Retrieval on Accelerators
The paper presents STATIC, a novel approach for efficient constrained decoding in LLM-based generative retrieval, significantly enhancing...
arXiv - Machine Learning
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4 min
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Llms
[2602.22564] Addressing Climate Action Misperceptions with Generative AI
This study explores how a personalized large language model (LLM) can correct climate action misperceptions among climate-concerned indiv...
arXiv - AI
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3 min
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Machine Learning
[2602.22549] DrivePTS: A Progressive Learning Framework with Textual and Structural Enhancement for Driving Scene Generation
DrivePTS introduces a progressive learning framework for generating diverse driving scenes, enhancing fidelity and controllability in aut...
arXiv - AI
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4 min
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Llms
[2602.22529] Generative Agents Navigating Digital Libraries
The paper introduces Agent4DL, a simulator for user search behavior in digital libraries, leveraging large language models to generate re...
arXiv - AI
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3 min
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Llms
[2602.22543] Ruyi2 Technical Report
The Ruyi2 Technical Report presents advancements in adaptive computing strategies for Large Language Models (LLMs), focusing on efficienc...
arXiv - AI
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3 min
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Llms
[2602.22524] Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o
This paper explores an iterative prompt refinement method for creating dyslexia-friendly text summaries using GPT-4o, demonstrating impro...
arXiv - AI
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3 min
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Machine Learning
[2602.22486] Flow Matching is Adaptive to Manifold Structures
The paper explores flow matching as a robust method for generative modeling, particularly in high-dimensional data concentrated near low-...
arXiv - Machine Learning
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4 min
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Llms
[2602.22483] Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models
This paper discusses the significance of prompt optimization in enhancing error detection in medical notes using language models, demonst...
arXiv - AI
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3 min
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Llms
[2602.22481] Sydney Telling Fables on AI and Humans: A Corpus Tracing Memetic Transfer of Persona between LLMs
This article explores the relationship between AI and humans through the lens of large language models (LLMs), focusing on the Sydney per...
arXiv - AI
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4 min
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Llms
[2602.22474] When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
This article presents a framework for uncertainty-aware policy steering in robotics, enabling adaptive robot behavior by addressing task ...
arXiv - Machine Learning
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4 min
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Llms
[2602.22450] Silent Egress: When Implicit Prompt Injection Makes LLM Agents Leak Without a Trace
The paper discusses the security risks posed by implicit prompt injection in large language model (LLM) agents, demonstrating how adversa...
arXiv - AI
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4 min
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Machine Learning
[2602.22431] mmWave Radar Aware Dual-Conditioned GAN for Speech Reconstruction of Signals With Low SNR
This article presents a novel approach using a Dual-Conditioned Generative Adversarial Network (GAN) for reconstructing speech signals ca...
arXiv - Machine Learning
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3 min
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Llms
[2602.22427] HubScan: Detecting Hubness Poisoning in Retrieval-Augmented Generation Systems
The paper presents HubScan, a tool designed to detect hubness poisoning in Retrieval-Augmented Generation systems, addressing a critical ...
arXiv - AI
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4 min
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Llms
[2602.22368] EyeLayer: Integrating Human Attention Patterns into LLM-Based Code Summarization
The paper presents EyeLayer, a novel module that integrates human attention patterns into LLM-based code summarization, enhancing model p...
arXiv - AI
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4 min
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Llms
[2602.22359] Scaling In, Not Up? Testing Thick Citation Context Analysis with GPT-5 and Fragile Prompts
This paper explores the effectiveness of GPT-5 in interpretative citation context analysis (CCA) by employing thick, text-grounded readin...
arXiv - AI
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4 min
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Llms
[2602.22246] Self-Purification Mitigates Backdoors in Multimodal Diffusion Language Models
This article presents a framework called DiSP (Diffusion Self-Purification) to mitigate backdoor attacks in Multimodal Diffusion Language...
arXiv - Machine Learning
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4 min
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Llms
[2602.22299] Decoding the Hook: A Multimodal LLM Framework for Analyzing the Hooking Period of Video Ads
This article presents a framework using multimodal large language models (MLLMs) to analyze the 'hooking period' of video ads, focusing o...
arXiv - Machine Learning
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4 min
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