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Mukul Singh

Microsoft

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#artificial intelligence Preprint Sep 2026

EmailBench: A Benchmark for Evaluating LLM Agents on Enterprise Email and Productivity Tasks

EmailBench is introduced, a benchmark of 206 email and productivity scenarios across 16 task categories that couples a typed email API specification with provider-neutral naming, a deterministic synthetic Enron-inspired corpus, and a scenario suite whose topic selection was informed by aggregate task-intent telemetry f...

Mukul Singh, Mansi Uniyal, Devin Devlin et al. · 0 citations
Open access 2026

Asking language models how to represent data for fine-tuning

It is shown that format choice remains important even after fine-tuning; models learn more efficiently with specific formats rather than adapting to any format; this finding allows format selection to be done via inference alone, avoiding costly trial-and-error fine-tuning runs.

Usneek Singh, Ananya Singha, Abhijeet Awasthi et al. · 0 citations

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