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cs.AI2026
Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
Yue Xu, Qian Chen, Zizhan Ma +5
Large language models have enabled agentic systems that reason, plan, and interact with tools and environments to accomplish complex tasks. As these agents operate over extended in…
cs.AI2025
Flash-Searcher: Fast and Effective Web Agents via DAG-Based Parallel Execution
Tianrui Qin, Qianben Chen, Sinuo Wang +10
Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks when equipped with external tools. However, current frameworks predominantly rely…
cs.AI2025
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Weizhen Li, Jianbo Lin, Zhuosong Jiang +27
Recent advances in large language models (LLMs) and multi-agent systems have demonstrated remarkable capabilities in complex problem-solving tasks such as deep research, vibe codin…