Search Results for author:
Found 2 papers, 1 papers with code
Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Models
As foundation models (FMs) continue to shape the landscape of AI, the in-context learning (ICL) paradigm thrives but also encounters issues such as toxicity, hallucination, disparity, adversarial vulnerability, and inconsistency.
Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey
Transformer-based Large Language Models (LLMs) have been applied in diverse areas such as knowledge bases, human interfaces, and dynamic agents, and marking a stride towards achieving Artificial General Intelligence (AGI).
Cannot find the paper you are looking for? You can
Submit a new open access paper.
