Introduces 2WikiMultiHopQA, a multi-hop QA dataset with explicit evidence chains generated via templates and Wikidata logical rules to force and evaluate multi-hop reasoning.
ArXiv, abs/2004.07347
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TaNOS decouples table semantics from numerical structure via anonymization, sketches, and program-first self-supervision, yielding 80.13% FinQA accuracy with 10% data and near-zero cross-domain gap versus over 10pp for standard fine-tuning.
RELOOP unifies retrieval across text, tables, and KGs via hierarchical sequences and dual-agent guided iteration, reporting EM/F1 gains over baselines on HotpotQA, HybridQA/TAT-QA, and MetaQA.
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Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning
TaNOS decouples table semantics from numerical structure via anonymization, sketches, and program-first self-supervision, yielding 80.13% FinQA accuracy with 10% data and near-zero cross-domain gap versus over 10pp for standard fine-tuning.