MCP & A2A FAIL - not for the reasons you think #ai

How is new knowledge integrated in your neural network interconnect of your transformer architecture? Strange phenomenons happen. We explore all of them. Data efficient learning for AI.

All rights authors:

How new data permeates LLM knowledge and

how to dilute it

Chen Sun1, Renat Aksitov1, Andrey Zhmoginov1, Nolan Andrew Miller1, Max Vladymyrov1, Ulrich Rueckert1,

Been Kim1 and Mark Sandler1

1 Google DeepMind

Identifying and Mitigating the Influence of the Prior

Distribution in Large Language Models

Liyi Zhang

Department of Computer Science

Princeton University

Princeton, NJ 08540, USA

[email protected]

Veniamin Veselovsky

Department of Computer Science

Princeton University

Princeton, NJ 08540, USA

[email protected]

R. Thomas McCoy

Department of Linguistics

Yale University

New Haven, CT 06511, USA

[email protected]

Thomas L. Griffiths

Department of Psychology and Computer Science

Princeton University

Princeton, NJ 08540, USA

[email protected]

Memorization vs. Reasoning: Updating LLMs with New Knowledge

Aochong Oliver Li

Computer Science, Cornell University

[email protected]

Tanya Goyal

Computer Science, Cornell University

[email protected]

Recommended:

-------------------------

SYNTHETIC CONTINUED PRETRAINING

Zitong Yang∗

Department of Statistics

Stanford University

Neil Band∗

Department of Computer Science

Stanford University

Shuangping Li

Department of Statistics

Stanford University

Emmanuel Cand`es

Department of Statistics

Stanford University

Tatsunori Hashimoto

Department of Computer Science

Stanford University

Multi‑Agent Reinforcement Learning

MCP - Model Context Protocol

A2A Agent 2 Agent

Latency Drift

MARL Tutorial

RL Failure Modes

AI Research

Distributed Systems

Agent Coordination

AI data pipeline