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A small number of samples can poison LLMs of any size Anthropic

by Postshift | Oct 13, 2025

Anthropic research on data-poisoning attacks in large language models In a joint study with the UK AI Security Institute and the Alan Turing Institute, we found that as few as 250 malicious documents can produce a "backdoor" vulnerability in a large language...

New memory framework builds AI agents that can handle the real world’s unpredictability | VentureBeat

by Postshift | Oct 13, 2025

Researchers at the University of Illinois Urbana-Champaign and Google Cloud AI Research have developed a framework that enables large language model (LLM) agents to organize their experiences into a memory bank, helping them get better at complex tasks over time. Go...

Less is More : Recursive Reasoning with Tiny Networks paper explained | by Mehul Gupta | Data Science in Your Pocket | Oct, 2025 | Medium

by Postshift | Oct 12, 2025

The paper introduces Tiny Recursive Model (TRM) a 7M-parameter network that outperforms LLMs like Gemini 2.5 Pro, DeepSeek R1, and even the so-called “reasoning” variants on tasks like Sudoku-Extreme, Maze-Hard, and ARC-AGI (the benchmark designed to measure general...

Meta Superintelligence’s surprising first paper

by Postshift | Oct 12, 2025

Long awaited first paper from Meta Superintelligence Labs is not a model layer innovation. What does this mean? Go to Source

[2506.22988] (World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments

by Postshift | Oct 12, 2025

Abstract page for arXiv paper 2506.22988: (World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments Go to Source
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