Consilium: When Multiple LLMs Collaborate
Related stories
Judge Arena: Benchmarking LLMs as Evaluators
Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention
From Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs
How good are LLMs at fixing their mistakes? A chatbot arena experiment with Keras and TPUs
Mastering Long Contexts in LLMs with KVPress
SyGra: The One-Stop Framework for Building Data for LLMs and SLMs
Beyond Memory: A Templated Substrate for Heterogeneous Collaborative Knowledge Work with LLM Agents
arXiv:2607. 24759v1 Announce Type: new Abstract: Research projects, educational efforts, and adjacent knowledge work accumulate findings, decisions, and reasoning that future collaborators rarely recover.
Toward an Organizational Science of Multi-Agent LLM Systems: Decoupling Who, How, and Which Algorithm
arXiv:2607. 25446v1 Announce Type: new Abstract: Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol).
Synapse: Federated Tool Routing via Typed Compendium Artifacts
arXiv:2602. 00911v2 Announce Type: replace Abstract: The unit of collaboration in federated learning determines what guarantees are even expressible.
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
arXiv:2605. 15207v2 Announce Type: replace Abstract: Multi-agent LLM systems have shown promise for complex reasoning, yet recent evaluations reveal they often underperform single-model baselines.
Doing What They Say, Not What They Reason: Locating the Faithfulness Gap in LLM Agents
arXiv:2606. 00476v1 Announce Type: new Abstract: Do LLM agents act on the reasoning they state?
Flout at Your Own Risk: LLMs Struggle with Pragmatic Cooperativity Under Epistemic Asymmetry
arXiv:2607. 11053v1 Announce Type: cross Abstract: Fruitful collaborations rely on cooperative communications, including of contextual cues to incorporate into reasoning.
