SILO-BENCH: A Scalable Environment for Evaluating Distributed Coordination in Multi-Agent LLM Systems (2026 · 2 citations)
Multi-agent LLM setups are often proposed as a way around context-window limits: each agent holds part of the data, and together they should compute a global answer.
DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding (2026)
Large audio language models are mostly autoregressive. They need a lot of data and compute to scale, and their token-by-token decoding slows inference. The earlier DIFFA work showed that a diffusion LLM backbone can help audio understanding, but only at a small, proof-of-concept scale. DIFFA-2 develops this into a…
When 20 Agents Fail to Sort: The Distributed Sorting Benchmark for Scalable Multi-Agent Systems (2026)
The paper examines whether LLM-based agents can coordinate without heavy human scaffolding, such as predefined roles or scripted pipelines.

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Updated 2 November 2026