Author

Óscar Romero

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#machine learning Preprint Sep 2026

Discovery-Driven Integration of Disjoint Tables via Text

Comprehensive evaluations on real-world benchmarks demonstrate that LOKI consistently outperforms state-of-the-art multi-modal data discovery approaches, and materializes typed integrated tables with 0.982 macro typed-pair precision while being up to 40 times cheaper in LLM API cost than direct prompting.

Md Ataur Rahman, Dimitris Sacharidis, Óscar Romero et al. · 0 citations

Preprint Aug 2026

CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases

CorporateBench (CB), a human-validated multi-task Q&A benchmark whose scale approaches the conditions LLMs encounter in corporate communication networks, is presented, with evaluation corpora surpassing 230,000 documents.

Sil Hamilton, A. Sun, Óscar Romero et al. · 1 citation