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Domain-specific scientific models, previously siloed from LLM agent systems, can now be orchestrated for complex reasoning tasks via the Eywa framework, unlocking performance gains on structured data.
Looping language models isn't just for single agents anymore: Recursive Multi-Agent Systems (RecursiveMAS) show that agent collaboration itself can be scaled through recursion, yielding faster and more efficient problem-solving.
Ramen achieves robust test-time adaptation of VLMs in mixed-domain scenarios by selecting the right samples to adapt to, sidestepping the common pitfall of performance degradation when faced with diverse and inconsistent test data.
