Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability
Samuel Lewis-Lim, Xingwei Tan, Mario Sanger +2
Chain-of-thought (CoT) reasoning allows humans to inspect how large language models reach their answers, and oversee model behaviour. This reasoning comes at an increased inference…
cs.AI2026
BusMA: A Bus Communication Substrate for Multi-Agent Systems
Yanwen Peng, Delvin Ce Zhang, Xi Wang +1
Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Existing systems typically adop…
cs.AI2026
StateBridge: Training-free Hidden-state Alignment for Latent Communication in LLM Multi-Agent Systems
Yanwen Peng, Delvin Ce Zhang, Xi Wang +1
Large language model based multi-agent systems usually communicate in text, i.e., using discrete tokens. However, text introduces a discrete bottleneck. Converting the sender's con…