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Aditya G. Parameswaran

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#natural language process... Preprint Oct 2026

DuoDiscover: Scaling Autonomous Discovery Beyond the Evaluation Bottleneck

Evaluation has been central to advances in AI, and it is equally critical to autonomous discovery. Yet scaling autonomous discovery to real-world engineering challenges faces a fundamental bottleneck: the cost of evaluating progress. In real settings, a single true evaluation, such as a full benchmark or serving trace,...

Shubham Agarwal, Akshat Gupta, M. Heddes et al. · 0 citations
#small language model Open access Jul 2026

Bolt-on, Verifiable Provenance for LLM-Powered Data Processing

BLIP is presented, a bolt-on framework for efficiently inferring a small-sized verifiable provenance for any LLM-powered data processing task, with any LLM, and eight strategies, each guaranteed to find a minimal verifiable provenance are introduced.

Yi-Ming Lin, Sepanta Zeighami, Aditya G. Parameswaran · 0 citations

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