Author

Shreya Shankar

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Preprint Aug 2026

Scout: Scalable Document Extraction via Data Similarity

Extracting values from large document collections powers data analysis across many domains. Frontier LLMs extract such values accurately, but processing an entire collection with one is prohibitively costly. Yet this cost is largely avoidable: real-world collections exhibit rich similarity, so for the same query over s...

Yi-Ming Lin, Chiyu Hao, Shreya Shankar et al. · 0 citations

Preprint Aug 2026

Who's Keeping Score? Interactive Steering of LLM-Powered Scoring with Attune

Attune is presented, a mixed-initiative system for steerable LLM-powered scoring that performs pairwise comparisons across records to develop a global understanding first, and then resolves these comparisons into consistent score assignments-deriving scoring criteria and rules bottom-up in the process.

Bhavya Chopra, Meng Chen, Rebecca Dang et al. · 0 citations

What Do Users Actually Do with LLM-Powered Data Systems?

How users actually use LLM-powered data systems is examined: how they struggle to specify and validate queries, how they iterate extensively to converge on bespoke operators specific to their documents and domains, and what these patterns imply for the systems and benchmarks their community should be building.

Shreya Shankar, Aditya G. Parameswaran, U. Berkeley · 0 citations