MOSAIC combines frozen-LLM semantic embeddings with hierarchical consistency objectives to report up to 3.4% AUC gains on knowledge-tracing benchmarks including a new MOOC dataset.
In: 2026 9th International Symposium on Big Data and Applied Statistics (ISBDAS)
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces failure-aware observability framework for diagnosing wasted computation in multi-agent LLM systems and evaluates it on 165 GAIA traces showing common operational failures.
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Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability
Introduces failure-aware observability framework for diagnosing wasted computation in multi-agent LLM systems and evaluates it on 165 GAIA traces showing common operational failures.