4 papers
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale
Ang Li, Ben Liu, Bin Han +215
Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management
Zherui Yang, Fan Liu, Yansong Ning +1
Recent progress in Large Language Model (LLM) agents has enabled promising advances in automated data science. However, existing approaches remain fundamentally limited by their st…
TrafficClaw: A Generalizable LLM Agent in the Unified Physical Environment for Urban Traffic Control
Siqi Lai, Pan Zhang, Yuping Zhou +3
Large language model (LLM) agents have shown strong capabilities in long-horizon reasoning, tool use, and decision-making in digital environments, yet extending them to physically…
AgentBalance: Backbone-then-Topology Design for Cost-Effective Multi-Agent Systems under Budget Constraints
Shuowei Cai, Yansong Ning, Hao Liu
Large Language Model (LLM)-based multi-agent systems (MAS) are becoming indispensable building blocks for web-scale applications such as web search, social network analytics, and o…