SEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting

arXiv:2610.04109 · cs.LG, cs.AI, cs.CL · Submitted 2026-10-02 · Read on arXiv

cs.LG, cs.AI, cs.CL

Submitted: 2026-10-02

Updated: 2026-10-02

Comments: 39 pages, 19 figures

Code: https://github.com/BennyTMT/SEER

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Time Series Forecasting — 1× in this paper · explained in 3 episodes

Sources

• GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
• Chronos: Learning the Language of Time Series
• MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
• AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets
• A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
• Foundation Models for Clean Energy Forecasting: A Comprehensive Review
• GenEnv: Difficulty-Aligned Co-Evolution Between LLM Agents and Environment Simulators
• SEAL: Synergistic Co-Evolution of Agents and Learning Environments
• MemGPT: Towards LLMs as Operating Systems
• Training Software Engineering Agents and Verifiers with SWE-Gym
• LEAF: A Living Benchmark for Event-Augmented Forecasting
• Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning
• TradingAgents: Multi-Agents LLM Financial Trading Framework
• Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecasting
• EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents
• SWE-bench Goes Live!
• Qwen-AgentWorld: Language World Models for General Agents

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