Multi-agent Integration
3 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
SMASH: a Semantic-enabled Multi-agent Approach for Self-adaptation of Human-centered IoT
Nowadays, IoT devices have an enlarging scope of activities spanning from sensing, computing to acting and even more, learning, reasoning and planning.
One Agent To Rule Them All: Towards Multi-agent Conversational AI
To address these problems, we introduce a new task BBAI: Black-Box Agent Integration, focusing on combining the capabilities of multiple black-box CAs at scale.
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
Through conducting extensive experiments on a large scale of harmful and safe prompts, we validate the effectiveness of the proposed AutoDefense in improving the robustness against jailbreak attacks, while maintaining the performance at normal user request.