framework

NVIDIA has introduced an open-source framework that applies object-oriented programming to AI agents, treating agents as Python classes where fields are state, methods are tools, and docstrings are prompts.

Guillermo Rauch announces eve, a durable AI agent framework from Vercel Labs that runs natively with React and Next.js, featuring built-in sandboxing, human-in-the-loop, and evaluation capabilities.

Prime RL now supports expressing and training multi-agent systems, enabling use cases like agentic judge, self-play, user simulation, and complex agent collaboration.

Guillermo Rauch quips that Next.js is the Next.js for SPAs, highlighting that Next.js 16.3 makes navigations roughly 3.5× faster in v0, with an agent-driven optimization loop.

SEAM is a generator-agnostic framework that audits global consistency of explanations in scientific machine learning, detecting incompatible local explanations even when predictions are locally accurate and attributing failures to specific channels and overlaps. The paper presents theory and experiments across PDE systems, neural operators, and four open datasets.

VideoSDK AI Agents is an open-source Python framework for building production-ready real-time voice and multimodal AI agents that join VideoSDK rooms as participants, with unified pipeline configuration and multiple execution modes.

Microsoft Research's Atlas Playbook provides frameworks and tools for designing, deploying, and evaluating human-centered AI systems across diverse cultural contexts, based on fieldwork in Kenya and India.

This paper introduces STRIVE, an LLM-based framework for jointly generating and evaluating controlled event sets for psycholinguistic plausibility judgments. Experiments show that adding a global reasoning scratchpad and evaluator-guided refinement substantially improves generation quality, though near-boundary events remain challenging.

This paper introduces RAG-Stack, a framework that co-optimizes RAG serving performance and answer quality by efficiently exploring the joint algorithm-system configuration space. It finds Pareto frontiers that cover significantly more quality-performance space than existing configuration-search methods.

Introduces AutoProteinEngine (AutoPE), an LLM-driven agent framework that enables biologists without deep learning expertise to perform multimodal AutoML for protein engineering via natural language, showing improvements over zero-shot and manual fine-tuning approaches.

JudgeArena is an open-source framework that unifies major LLM-judge benchmarks under a single interface, enabling systematic study of judge choices and offering open-model judges that match or outperform closed models, with the ability to simulate LMArena Elo scores.

CastFSR is a Fast–Slow–Reflect agentic reasoning framework that leverages LLMs for context-aware time series forecasting, combining fast lightweight forecasters, slow deliberative reasoning, and reflective evaluation to improve forecasting accuracy and consistency.

Taipy is an open-source Python framework positioned as a production-ready alternative to Streamlit for building data and AI web apps, with built-in pipeline orchestration and scenario management.

DSPy 3.3.0 is released, featuring dspy.Flex for GEPA-optimized code and prompts, and dspy.ReActV2 with native parallel tool calling, with praise for lead maintainer Isaac Miller.

Microsoft's Orchard is an open-source framework for agentic modeling, providing a Kubernetes-native environment substrate, RL training stack, and datasets for software engineering, GUI, and computer use agents.

Microsoft Research introduces Orchard, an open-source framework for scalable and cost-effective agentic AI research, with reusable infrastructure supporting software-engineering, web-navigation, and personal-assistant agents across domains.

The University of Hong Kong open-sourced the AutoAgent framework, which automatically builds and evolves multi-agent workflows via natural language with no code required, and includes a built-in deep research mode supporting multiple mainstream large models.

Microsoft Research's AutoGen enables multi-agent LLM conversations, allowing AI system engineers to build conversable agents with hierarchical execution for complex tasks that single LLMs struggle with.

Octane is a compiled frontend framework that brings React's programming model—hooks, Suspense, and actions—with ahead-of-time compilation, no virtual DOM, and no rules of hooks.

Quantinuum and NVIDIA, with a pharmaceutical partner, validated a proof-of-principle Generative Quantum AI (GenQAI) framework that combines HPC, AI, and quantum computing to generate and execute quantum circuits for pharmaceutical R&D.