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cs.LG2026
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…
cs.LG2024
Cross-domain-aware Worker Selection with Training for Crowdsourced Annotation
Yushi Sun, Jiachuan Wang, Peng Cheng +3
Annotation through crowdsourcing draws incremental attention, which relies on an effective selection scheme given a pool of workers. Existing methods propose to select workers base…