Attention Residuals: A Comprehensive Understanding
This paper addresses a fundamental problem in training deep transformer models: uncontrolled hidden-state magnitude growth as model depth increases. The auth...
This paper addresses a fundamental problem in training deep transformer models: uncontrolled hidden-state magnitude growth as model depth increases. The auth...
Browser agents are getting better fast, but the web is full of things that try to steer behavior. If that already works on humans, why would agents be immune?
How ads ranking systems went from aggregated feature counts to retrieve-and-compress architectures that handle 10,000+ user events under millisecond latency ...
From specification gaming in classical RL to deceptive alignment and jailbreaks in LLMs—a survey of how reward hacking has become a central challenge in AI s...
Reasoning in Large Language Models: A Research-Centric Overview