How to generate text: using different decoding methods for language generation with Transformers
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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New AI “copilot” helps engineers design better structures
The system asks humans for feedback to increase trust in machine-generated designs for buildings and bridges.
LLMON: An LLM-Native Markup Language, now in Granite 4.1 3B and 8B
A Blog post by IBM Granite on Hugging Face
New research could lead to faster, trustworthy AI models for climate prediction
MIT scientists developed a training method to generate models that simulate the effects of human activities on climate much more quickly than other approaches.
The Definitive Fine-Tuning Guide for 3D Generation Models
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Bridging Humans and LLMs: Investigating Human-AI Collaboration in Multi-agent Requirements Analysis for Organizational AI Adoption
LLM-based multi-agent systems can support strategic AI planning by enabling iterative refinement with human experts by supporting structured and collaborative Requirements Engineering processes for AI adoption planning.
Constitutional Midtraining: Content Presence Drives Alignment Gains
Post-training alignment is often shallow, eroding under fine-tuning. It remains untested as to whether constitutional midtraining interventions can produce durable alignment when cleanly isolated from post-training. We build a 394M-token constitutional corpus from Anthropic's Constitution and apply constitutional midtr...
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This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.