12 stories tagged Protocol
A critical flaw in the MCP protocol, used for AI agent communication, could allow malicious prompts to spread between agents. This highlights a structural vulnerability in how AI systems interact.
Researchers from the University of Edinburgh and the Alan Turing Institute introduced the Model Context Protocol (MCP), implemented via the Eunomia Agent, to enable LLM agents to interact with governed data spaces for secure, policy-compliant data sharing.
Researchers introduced PlanFence, a dependency-scoped validation protocol that prevents distributed LLM-agent teams from executing actions based on obsolete plans, even when they have access to the latest shared facts.
Researchers propose CaRE (Compute-aware Remasking Evaluation), a new protocol to standardize the evaluation of masked diffusion language models (MDLMs). The framework addresses incompatible settings across seven recent papers, aiming to make model comparisons fair and reliable.
The Model Context Protocol (MCP), a key building block for AI interoperability, is getting a simpler version that reduces the complexity and cost of connecting AI models to external data sources and services. This could lead to more seamless integrations in everyday apps and tools.
Researchers propose a new language to clearly define how AI and humans should work together in software development. This could make teamwork between people and AI more predictable and reliable.
Researchers developed the Argent Signaling Protocol (ASP) to help AI systems distinguish between incomplete and completely wrong answers. This could make AI assistants more reliable and trustworthy.
Researchers propose the Regulatory Context Protocol (RCP), an Agent-to-Agent communication standard that could drastically speed up nuclear reactor approvals. The approach uses AI to handle routine regulatory communication, freeing humans to focus on critical safety decisions.
Researchers created a system where AI models argue like a panel of specialists, turning disagreements into better answers. This could make AI more reliable for complex questions.
Researchers have developed a new protocol to help AI agents work together more effectively. This could make AI systems better at sharing and verifying information, which is crucial as they become more integrated into our daily lives.
Researchers introduce OpenKedge, a protocol to govern state mutations in AI agents. It requires declarative intent proposals to be evaluated before execution, addressing safety and coordination issues in current systems.
QVeris introduces AI agents that can discover, inspect, and call 10,000 capabilities via one protocol. This innovation simplifies interactions with various capabilities.