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News Wire / technology

Embodied Chain-of-Thought For Robot Manipulation Studied

Modernity/arxiv 1h1h Impact 5
Researchers have developed a new method for language models to self-modify and consolidate memories. This approach aims to improve machine learning algorithms by enabling models to learn from past data and adapt over time.

Topics

AI machine learning language models

Developing

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Sources · 7 independent

Modernity/arxiv

“Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories. Authors: Ali Behrouz, Farnoosh Hashemi, Vahab Mirrokni Abstract: The past few decades have witnessed significant advances in the design of machine learning algorithms, from early studies on task-spec...”

Modernity/arxiv

“Large language models improve final-answer accuracy through extended chain-of-thought reasoning...”

Modernity/arxiv

“Reasoning Structure of Large Language Models. Authors: Frédéric Berdoz, Luca A. Lanzendörfer, Fabian Farestam, Roger Wattenhofer Abstract: Large reasoning models (LRMs) are often evaluated using metrics such as final-answer accuracy or token cou...”

Modernity/arxiv

“Triple exceptional point with unitary paths of unfolding in a three-site fermionic Swanson-like model.”

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