arXiv:2606. 09198v1 Announce Type: new Abstract: Deep Research agents powered by Large Language Models (LLMs) have exhibited extraordinary potential in automated paper writing tasks.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the...
arXiv:2606. 01199v1 Announce Type: new Abstract: Large language agents are increasingly used for social simulation, yet it remains unclear whether they can sustain coherent behavior in structured organizations, where goals must propagate through hierarchy, tasks depend on prior execution, and artifacts accumulate over long horizons.
arXiv:2608. 00007v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with human-like personas is crucial for agentic applications, such as role-play and user simulation.
arXiv:2606. 06787v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise as tool-using agents but remain limited in long-horizon tasks that require remembering, organizing, and reusing knowledge.
arXiv:2609.24911v1 Announce Type: new Abstract: Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by...
Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by acting as silicon samples that unite agent-based...