Research Hub

Advancing the frontiers of artificial intelligence through cutting-edge research, open datasets, and collaborative innovation in machine learning.

Research Areas

NLP

Large Language Models

Advanced research in transformer architectures, attention mechanisms, and scaling laws

15 Papers8 Datasets

Computer Vision

Multimodal AI

Vision-language models, cross-modal understanding, and unified architectures

12 Papers6 Datasets

ML Systems

Training Optimization

Efficient training methods, distributed computing, and resource optimization

18 Papers4 Datasets

AI Ethics

AI Safety & Alignment

Responsible AI development, bias mitigation, and ethical considerations

10 Papers3 Datasets

Open Datasets

XylarChat-100M

Conversational

Curated conversational dataset for training chat models

Size: 100M tokensDownloads: 50K+

MultiModal-Vision-Text

Multimodal

Paired image-text dataset for multimodal training

Size: 2.5M pairsDownloads: 25K+

Code-Instruction-Dataset

Code

Programming instruction dataset for code generation models

Size: 75M tokensDownloads: 40K+

Scientific-Papers-Corpus

Scientific

Academic papers dataset for scientific AI training

Size: 500M tokensDownloads: 30K+

Latest Publications

Scaling Laws for Next-Generation Language Models

LLM

Xylar Research Team

NeurIPS 2024

Comprehensive analysis of scaling behaviors in modern transformer architectures...

Efficient Multimodal Training with Cross-Attention Mechanisms

Multimodal

Vision Team, Xylar Labs

ICML 2024

Novel approaches to training vision-language models with improved efficiency...

Distributed Training Optimization for Large-Scale Models

Systems

Systems Team, Xylar Labs

MLSys 2024

Advanced techniques for distributed training of billion-parameter models...

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