A Large Language Model (LLM) based multi-agent system that aims to pipeline complex data discovery tasks and comprehensively discusses the challenges of building such an end-to-end data discovery framework and analyze the benefits of LLMs in addressing them.
Public LLM services serve diverse multi-agent applications with varying workflow dependencies and performance requirements. Requests generated by these applications often exhibit commonality and interdependence, yet current systems largely ignore such application-level structure. As a result, at the LLM engine cluster...
Uttam Rao, Ali Zafar Sadiq, Hai-Ying Shen et al.· International Conference on...· 0 citations
EASy is proposed, a trainable agentic framework that jointly optimizes task performance and computational efficiency through reinforcement learning and consistently achieves stronger performance-efficiency trade-offs than strong agentic baselines.
Junnan Liu, Linhao Luo, Thuy-Trang Vu et al.· 0 citations
DataClawEval is introduced, the first comprehensive benchmark designed specifically to evaluate the end-to-end task completion capabilities of autonomous agents in real-world data engineering scenarios, and it comprises 100 rigorous, end-to-end tasks spanning five execution engines.
This survey presents a systematic taxonomy and technical review of dynamic orchestration strategies designed to address communication overhead, KV cache management challenges, and increased token consumption within large Language Model-based Multi-Agent Systems.
Heet Nagoriya, H. Raithatha· International Journal of Kno...· 0 citations
AgentRadio is presented, an asynchronous message-passing layer that equips coding-agent harnesses with three primitives: threads, messages, and waiting for mentions that shows the gain growing with task difficulty, consistent with mid-course correction as the underlying mechanism.
Xinxing Ren, Qianbo Zang, Ziyan Wang et al.· arXiv.org· 0 citations
An innovative paradigm is presented that enables fully decentralized agent and workflow discovery through social relationships among LLM-based agents, as well as the dynamic creation of trusted social LLM-MAS, which will represent a mature generational leap over the two-tier operational/knowledge-based frameworks incre...
Marco Becattini, Emanuele Gaspare Biondino, Enrico Vicario et al.· IEEE Internet of Things Jour...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
