From the 2 of 11 linked papers with an AI index.
11 papers
TIEM: Temporal Integration of Hypergraph Evidence and Skill Memory for Event-Driven Financial Forecasting
Wenjin Liu, Shen Pang, Chenxi Wang +5
Event-driven catalyst-outcome forecasting increasingly uses retrieval- and memory-augmented large language model agents for prediction. However, training-data contamination and tem…
PowerAtlas: Towards Electricity-Computing Co-Scheduling for Power Systems
Kaiwen Jiang, Siya Xu, Ziyue Zhu +3
PowerAtlas is an LLM‑agent framework that jointly schedules electricity supply and computing workloads in data centers, ensuring grid operational constraints and computing service…
SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning
Jinyang Wu, Shuo Yang, Zhengxi Lu +8
The paper introduces SEED, a framework that extracts reusable natural-language skills from on-policy trajectories and distills them back into the policy to provide dense token-leve…
OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning
Shuo Yang, Jinyang Wu, Zhengxi Lu +8
Outcome-based reinforcement learning provides a stable optimization backbone for language agents, but its sparse trajectory-level rewards provide little guidance on which intermedi…
OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions
Hang Yan, Fangzhi Xu, Qiushi Sun +14
The rapid advancement of Large Language Models (LLMs) has catalyzed the development of autonomous agents capable of navigating complex environments. However, existing evaluations p…
Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles
Jinyang Wu, Guocheng Zhai, Ruihan Jin +7
The proliferation of large language models (LLMs) and modular skills has endowed autonomous agents with increasingly powerful capabilities. Existing frameworks typically rely on mo…