Multimodal reinforcement learning with agentic verifier for AI agents
Argos improves multimodal RL by evaluating whether an agent’s reasoning aligns with what it observes over time. The approach reduces visual hallucinations and produces more reliable, data-efficient agents for real-world applications.
The post Multimodal reinforcement learning with agentic verifier f...
OptiMind: A small language model with optimization expertise
OptiMind is a small language model that converts business operation challenges, described naturally, into mathematical formulations that optimization software can solve. It reduces formulation time & errors & enables fast, privacy-preserving local use.
The post OptiMind: A small language model with ...
Agent Lightning: Adding reinforcement learning to AI agents without code rewrites
By decoupling how agents work from how they’re trained, Agent Lightning turns each step an agent takes into data for reinforcement learning. This makes it easy for developers to improve agent performance with almost zero code changes.
The post Agent Lightning: Adding reinforcement learning to AI age...
Promptions helps make AI prompting more precise with dynamic UI controls
Promptions helps developers add dynamic, context-aware controls to chat interfaces so users can guide generative AI responses. It lets users shape outputs quickly without writing long instructions.
The post Promptions helps make AI prompting more precise with dynamic UI controls appeared first on Mi...
GigaTIME: Scaling tumor microenvironment modeling using virtual population generated by multimodal AI
Using AI-generated virtual populations, Microsoft researchers uncovered hidden cellular patterns that could reshape how we understand and treat cancer.
The post GigaTIME: Scaling tumor microenvironment modeling using virtual population generated by multimodal AI appeared first on Microsoft Research...
Ideas: Community building, machine learning, and the future of AI
As the Women in Machine Learning Workshop (WiML) marks its 20th annual gathering, cofounders, friends, and collaborators Jenn Wortman Vaughan and Hanna Wallach reflect on WiML’s evolution, navigating the field of ML, and their work in responsible AI.
The post Ideas: Community building, machine learn...
Reducing Privacy leaks in AI: Two approaches to contextual integrity
New research explores two ways to give AI agents stronger privacy safeguards grounded in contextual integrity. One adds lightweight, inference-time checks; the other builds contextual awareness directly into models through reasoning and RL.
The post Reducing Privacy leaks in AI: Two approaches to co...