5 papers
TokenCast: Forecasting Token Consumption During LLM Agent Execution
Chaoqian Ouyang, Ling Yue, Libin Zheng +8
When a large language model (LLM) agent executes the same task, token consumption can vary by over an order of magnitude across runs. The agent chooses its next steps based on tool…
FlowEvo: Self-Evolving Agents through the Co-Evolution of Workflows and Executable Skills
Zeyu Ren, Ling Yue, Ran Li +5
Large language model agents can adapt to complex tasks by constructing workflows at inference time, but procedures discovered in one episode are usually discarded after execution.…
DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution
Hanghui Guo, Weijie Shi, Zhangze Chen +6
Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort. Therefore, recent research has i…
Learning to Compose for Cross-domain Agentic Workflow Generation
Jialiang Wang, Shengxiang Xu, Hanmo Liu +5
Automatically generating agentic workflows -- executable operator graphs or codes that orchestrate reasoning, verification, and repair -- has become a practical way to solve comple…
AtomBridge: Agentic VLA Inference Plugin for Long-Horizon Tasks in Scientific Experiments
Yiwen Pang, Bo Zhou, Changjin Li +7
Robotic laboratories play a critical role in autonomous scientific discovery by enabling scalable, continuous experimental execution. Recent vision-language-action (VLA) models off…