Inside OpenAI's decision to abandon Sora AI video app
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Image, video, audio, and text generation
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MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...
Abstract page for arXiv paper 2603.12057: Coarse-Guided Visual Generation via Weighted h-Transform Sampling
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The paper discusses how cognitive models and AI algorithms can serve as templates for designing modular language agents, addressing limit...
This paper introduces Space Syntax-guided Post-training (SSPT) for enhancing residential floor plan generation by integrating architectur...
The paper presents Metacognitive Behavioral Tuning (MBT), a framework designed to enhance large reasoning models by incorporating human-l...
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The paper presents Reinforcement-aware Knowledge Distillation (RLAD) for enhancing reasoning in large language models (LLMs) by addressin...
This paper introduces a method for calibrated test-time guidance in Bayesian inference, addressing issues with existing approaches that m...
ArchAgent is an AI-driven system that automates computer architecture discovery, achieving significant performance improvements in cache ...
This paper explores the potential of AI agents to replace or augment social scientists by introducing the concept of 'vibe researching,' ...
This paper explores the reliability and efficiency of large language models (LLMs) using Random Matrix Theory. It introduces EigenTrack f...
This paper introduces GYWI, a system that enhances scientific idea generation by integrating co-author knowledge graphs with retrieval-au...
The paper presents UpSkill, a method that enhances response diversity in large language models (LLMs) through Mutual Information Skill Le...
BrepCoder is a unified multimodal large language model designed for multi-task reasoning in Computer-Aided Design (CAD), specifically uti...
The paper presents AutoQRA, a framework that optimizes mixed-precision quantization and low-rank adapters for efficient fine-tuning of la...
The paper introduces Entropy-Controlled Flow Matching (ECFM), a method that optimizes flow matching in machine learning by controlling in...
The paper presents a context-aware model switching approach for large language models (LLMs) to enhance energy efficiency during inferenc...
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