StarHarness offers a practical way to reduce persistent model-environment mismatch in tool-rich enterprise tasks by stratifying tasks according to baseline failure behavior, separating proposer-visible search tasks from proposer-hidden selection tasks, and reserves held-out tasks for evaluating generalization.
Esakkivel Esakkiraja, D. Akhiyarov, Vikas Yadav et al.· 1 citation
ESF-Bench is introduced, a challenging Enterprise Slot Filling benchmark consisting of 810 multi-turn samples and 6530 slots over 8 unique domains and curated using a taxonomy of the 57 most challenging slot-filling scenarios observed during real-world enterprise deployments.
Toby Liang, Gopal Sarda, Sagar Davasam et al.· 0 citations
Vision language models (VLMs) have achieved strong performance on visual document understanding benchmarks such as DocVQA, ChartQA, and MMLongBench-Doc. However, real-world documents combine multiple factors such as length, layout complexity, modality, and question difficulty, which makes it difficult to attribute mode...
Abhigya Verma, Khyati Mahajan, Amit Kumar Saha et al.· 0 citations
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