Electron microscopy shows ‘mouse bite’ defects in semiconductors | Cornell Chronicle

A Cornell-led collaboration used high-resolution 3D imaging to detect, for the first time, the atomic-scale defects in computer chips that can sabotage their performance.

Electron microscopy shows ‘mouse bite’ defects in semiconductors | Cornell Chronicle

A Cornell-led collaboration used high-resolution 3D imaging to detect, for the first time, the atomic-scale defects in computer chips that can sabotage their performance.

ICCV 2025 Open Access Repository

[Financial Awards] Korea Investment & Securities Expands Its Reach with AI Foresight—Innovation Reflected in 7,000 Annual Reports

Korea Investment & Securities Co. has been recognized for research innovation, leveraging AI and exclusive U.S. resources to publish over 7,000 annual reports, expanding coverage and accessibility for investors, especially amid a KOSDAQ bull market.

Scaling Latent Reasoning via Looped Language Models

Modern LLMs are trained to "think" primarily via explicit text generation, such as chain-of-thought (CoT), which defers reasoning to post-training and under-leverages pre-training data. We present and open-source Ouro, named after the recursive Ouroboros, a family of pre-trained Looped Language Models (LoopLM) that instead build reasoning into the pre-training phase through (i) iterative computation in latent space, (ii) an entropy-regularized objective for learned depth allocation, and (iii) scaling to 7.7T tokens. Ouro 1.4B and 2.6B models enjoy superior performance that match the results of up to 12B SOTA LLMs across a wide range of benchmarks. Through controlled experiments, we show this advantage stems not from increased knowledge capacity, but from superior knowledge manipulation capabilities. We also show that LoopLM yields reasoning traces more aligned with final outputs than explicit CoT. We hope our results show the potential of LoopLM as a novel scaling direction in the reasoning era. Our model is available here: http://ouro-llm.github.io.