Daphne O. Martschenko and Sam Trejo both want to make the world a better, fairer, more equitable place. But they disagree on ...

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Optimizing Your LinkedIn Profile for Element Materials Technology So, you’re looking to make a splash at Element ...

Google finds nation-state hackers abusing Gemini AI for target profiling, phishing kits, malware staging, and model ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Abstract: Test-time adaptation (TTA) seeks to tackle potential distribution shifts between training and testing data by adapting a given model w.r.t. any testing sample. This task is particularly ...

Threat actors are exploiting misconfigured web applications used for security training and internal penetration testing, such as DVWA, OWASP Juice Shop, Hackazon, and bWAPP, to gain access to cloud ...

Google Ads is running a limited test that allows some advertisers to A/B test different product titles and images within Shopping Ads. The feature appears as “product data experiments” and promises ...

With electronics increasingly facing the challenges of high speed and more complex designs, test and measurement vendors an avalanche of test data to process. In response, they are increasingly ...

To test the models, it is important to input the same number of time steps used during training. The sampling routine can be different, and additionally the test_type argument can be used to specify ...

On the surface, it seems obvious that training an LLM with “high quality” data will lead to better performance than feeding it any old “low quality” junk you can find. Now, a group of researchers is ...