most citedStrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

2 papers · 1 filter

cs.CL2024

CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion

Qibing Ren, Chang Gao, Jing Shao +4

The rapid advancement of Large Language Models (LLMs) has brought about remarkable generative capabilities but also raised concerns about their potential misuse. While strategies l…

cs.CL2023★ 1 cited

StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving

Chang Gao, Haiyun Jiang, Deng Cai +2

Most existing prompting methods suffer from the issues of generalizability and consistency, as they often rely on instance-specific solutions that may not be applicable to other in…