SOMA-SQL resolves multi-source ambiguity in NL-to-SQL using synthetic query logs and ambiguity-driven execution probing, reporting 13% average execution accuracy gains over baselines on six benchmarks.
Enrichindex: Using llms to enrich retrieval indices offline.arXiv preprint arXiv:2504.03598, 2025
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A survey that categorizes RIR benchmarks by domain and modality, proposes a taxonomy for integrating reasoning into retrieval pipelines, and outlines key challenges.
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Expert interviews demonstrate that context in generative AI workplace use collapses or rots over time, limiting tool effectiveness and revealing pitfalls in computational context approaches.
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SOMA-SQL: Resolving Multi-Source Ambiguity in NL-to-SQL via Synthetic Log and Execution Probing
SOMA-SQL resolves multi-source ambiguity in NL-to-SQL using synthetic query logs and ambiguity-driven execution probing, reporting 13% average execution accuracy gains over baselines on six benchmarks.
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A Survey of Reasoning-Intensive Retrieval: Progress and Challenges
A survey that categorizes RIR benchmarks by domain and modality, proposes a taxonomy for integrating reasoning into retrieval pipelines, and outlines key challenges.
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CAMI: Cost-Aware Agent-Guided Multi-Indexing for Semantic Retrieval
CAMI frames multi-index construction for semantic retrieval as a budgeted multi-objective portfolio problem and uses agent-guided search plus confidence-aware pruning to find high-recall configurations with reduced evaluation cost.
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Context Collapse: Barriers to Adoption for Generative AI in Workplace Settings
Expert interviews demonstrate that context in generative AI workplace use collapses or rots over time, limiting tool effectiveness and revealing pitfalls in computational context approaches.