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Found 5 papers, 1 papers with code
LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Models
This paper presents a comprehensive survey of the current status and opportunities for Large Language Models (LLMs) in strategic reasoning, a sophisticated form of reasoning that necessitates understanding and predicting adversary actions in multi-agent settings while adjusting strategies accordingly.
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting
Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages.
Low-code LLM: Graphical User Interface over Large Language Models
By introducing this framework, we aim to bridge the gap between humans and LLMs, enabling more effective and efficient utilization of LLMs for complex tasks.
TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs
On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well.
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey
Deep learning security matters to autonomous driving system security, and then matters to personal safety, which is an issue that deserves attention and research. This paper provides an summary of the concepts, developments and recent research in deep learning security technologies in autonomous driving.
