arXiv:2310. 06555v3 Announce Type: replace-cross Abstract: Emergent communication enables agents to develop bespoke languages that improve communication efficiency.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 12191v1 Announce Type: cross Abstract: Environments serve as interactive systems for large language model (LLM) based agents across diverse scenarios and play a crucial role in driving the continual evolution of model capabilities.
arXiv:2606. 14314v1 Announce Type: new Abstract: LLM agents have rapidly evolved into autonomous systems, yet a persistent information gap remains between users and agents: communication is costly, while users' identical preferences further limit information exchange.
arXiv:2404. 02039v5 Announce Type: replace Abstract: Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity.
arXiv:2607. 00233v1 Announce Type: new Abstract: How do two agents invent a shared language from scratch?
arXiv:2606. 04555v1 Announce Type: cross Abstract: Long-horizon conversational agents need to interact with users through evolving events, tasks, and goals.
arXiv:2606. 06380v1 Announce Type: cross Abstract: The question of whether artificial systems can be conscious remains open, in part because existing approaches either evaluate systems against theory-derived checklists (discriminative) or engineer consciousness-inspired modules directly (architectural); both leave open whether observed structures are artifacts of human language priors.