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Inside OpenAI's decision to abandon Sora AI video app

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Reddit - Artificial Intelligence · 1 min ·
Accelerating science with AI and simulations
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 · 10 min ·
[2603.12057] Coarse-Guided Visual Generation via Weighted h-Transform Sampling
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 · 4 min ·

All Content

[2602.22586] TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
Llms

[2602.22586] TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion

The paper presents TabDLM, a novel framework for generating free-form tabular data using joint numerical-language diffusion, addressing c...

arXiv - AI · 4 min ·
[2602.22743] Generative Data Transformation: From Mixed to Unified Data
Machine Learning

[2602.22743] Generative Data Transformation: From Mixed to Unified Data

The paper presents Taesar, a data-centric framework designed to enhance recommendation model performance by addressing data sparsity and ...

arXiv - AI · 4 min ·
[2602.22575] S2O: Early Stopping for Sparse Attention via Online Permutation
Machine Learning

[2602.22575] S2O: Early Stopping for Sparse Attention via Online Permutation

The paper presents S2O, a novel approach for early stopping in sparse attention mechanisms, enhancing efficiency in long-context inferenc...

arXiv - AI · 4 min ·
[2602.22680] Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
Llms

[2602.22680] Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions

This survey paper explores the development of personalized LLM-powered agents, focusing on their foundations, evaluation metrics, and fut...

arXiv - AI · 4 min ·
[2602.22538] RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format
Machine Learning

[2602.22538] RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format

The paper presents RAIN-Merging, a gradient-free method designed to enhance instruction adherence in large reasoning models while preserv...

arXiv - Machine Learning · 4 min ·
[2602.22523] Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents
Llms

[2602.22523] Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents

The paper discusses how cognitive models and AI algorithms can serve as templates for designing modular language agents, addressing limit...

arXiv - AI · 3 min ·
[2602.22507] Space Syntax-guided Post-training for Residential Floor Plan Generation
Machine Learning

[2602.22507] Space Syntax-guided Post-training for Residential Floor Plan Generation

This paper introduces Space Syntax-guided Post-training (SSPT) for enhancing residential floor plan generation by integrating architectur...

arXiv - Machine Learning · 4 min ·
[2602.22508] Mirroring the Mind: Distilling Human-Like Metacognitive Strategies into Large Language Models
Llms

[2602.22508] Mirroring the Mind: Distilling Human-Like Metacognitive Strategies into Large Language Models

The paper presents Metacognitive Behavioral Tuning (MBT), a framework designed to enhance large reasoning models by incorporating human-l...

arXiv - AI · 3 min ·
[2602.22505] Sharp Convergence Rates for Masked Diffusion Models
Machine Learning

[2602.22505] Sharp Convergence Rates for Masked Diffusion Models

This paper presents a comprehensive analysis of masked diffusion models, focusing on their convergence rates and theoretical underpinning...

arXiv - Machine Learning · 4 min ·
[2602.22495] Reinforcement-aware Knowledge Distillation for LLM Reasoning
Llms

[2602.22495] Reinforcement-aware Knowledge Distillation for LLM Reasoning

The paper presents Reinforcement-aware Knowledge Distillation (RLAD) for enhancing reasoning in large language models (LLMs) by addressin...

arXiv - AI · 4 min ·
[2602.22428] Calibrated Test-Time Guidance for Bayesian Inference
Machine Learning

[2602.22428] Calibrated Test-Time Guidance for Bayesian Inference

This paper introduces a method for calibrated test-time guidance in Bayesian inference, addressing issues with existing approaches that m...

arXiv - AI · 3 min ·
[2602.22425] ArchAgent: Agentic AI-driven Computer Architecture Discovery
Generative Ai

[2602.22425] ArchAgent: Agentic AI-driven Computer Architecture Discovery

ArchAgent is an AI-driven system that automates computer architecture discovery, achieving significant performance improvements in cache ...

arXiv - AI · 4 min ·
[2602.22401] Vibe Researching as Wolf Coming: Can AI Agents with Skills Replace or Augment Social Scientists?
Robotics

[2602.22401] Vibe Researching as Wolf Coming: Can AI Agents with Skills Replace or Augment Social Scientists?

This paper explores the potential of AI agents to replace or augment social scientists by introducing the concept of 'vibe researching,' ...

arXiv - AI · 4 min ·
[2602.22345] Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory
Llms

[2602.22345] Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory

This paper explores the reliability and efficiency of large language models (LLMs) using Random Matrix Theory. It introduces EigenTrack f...

arXiv - AI · 4 min ·
[2602.22215] Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation
Llms

[2602.22215] Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation

This paper introduces GYWI, a system that enhances scientific idea generation by integrating co-author knowledge graphs with retrieval-au...

arXiv - AI · 4 min ·
[2602.22296] UpSkill: Mutual Information Skill Learning for Structured Response Diversity in LLMs
Llms

[2602.22296] UpSkill: Mutual Information Skill Learning for Structured Response Diversity in LLMs

The paper presents UpSkill, a method that enhances response diversity in large language models (LLMs) through Mutual Information Skill Le...

arXiv - AI · 3 min ·
[2602.22284] BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning
Llms

[2602.22284] BrepCoder: A Unified Multimodal Large Language Model for Multi-task B-rep Reasoning

BrepCoder is a unified multimodal large language model designed for multi-task reasoning in Computer-Aided Design (CAD), specifically uti...

arXiv - Machine Learning · 3 min ·
[2602.22268] AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
Llms

[2602.22268] AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning

The paper presents AutoQRA, a framework that optimizes mixed-precision quantization and low-rank adapters for efficient fine-tuning of la...

arXiv - Machine Learning · 4 min ·
[2602.22265] Entropy-Controlled Flow Matching
Generative Ai

[2602.22265] Entropy-Controlled Flow Matching

The paper introduces Entropy-Controlled Flow Matching (ECFM), a method that optimizes flow matching in machine learning by controlling in...

arXiv - Machine Learning · 3 min ·
[2602.22261] Sustainable LLM Inference using Context-Aware Model Switching
Llms

[2602.22261] Sustainable LLM Inference using Context-Aware Model Switching

The paper presents a context-aware model switching approach for large language models (LLMs) to enhance energy efficiency during inferenc...

arXiv - Machine Learning · 4 min ·
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