Sam Blouir
26 posts
@SamBlouir_NLP
Intern @ Amazon AGI Foundations Thanks for coming to our AAAI 2025 Foundation Models for Biology workshop!
Introducing LFM2-VL — our new generation of efficient vision-language models for real-world deployment, from smartphones and laptops to wearables and embedded systems. 🧵
🚀 Introducing NSA: A Hardware-Aligned and Natively Trainable Sparse Attention mechanism for ultra-fast long-context training & inference! Core components of NSA: • Dynamic hierarchical sparse strategy • Coarse-grained token compression • Fine-grained token selection 💡 With optimized design for modern hardware, NSA speeds up inference while reducing pre-training costs—without compromising performance. It matches or outperforms Full Attention models on general benchmarks, long-context tasks, and instruction-based reasoning. 📖 For more details, check out our paper here: arxiv.org/abs/2502.11089
Meta presents Improving Factuality with Explicit Working Memory Presents EWE, a novel approach that enhances factuality in long-form text generation by integrating a working memory that receives real-time feedback from external resources EWE outperforms strong baselines on four fact-seeking long-form generation datasets, increasing the factuality metric, VeriScore, by 2 to 10 points absolute without sacrificing the helpfulness of the responses. arxiv.org/abs/2412.18069
