Author

Amit Kumar Saha

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Preprint Aug 2026

AgentJudgeBench: A Multi-Difficulty Benchmark for Evaluating LLM Judges on Agentic Tool-Calling

The first benchmark to systematically study LLM-as-a-judge reliability for agentic tool-calling over workflow DAGs, as distinct from the broader LLM-as-a-judge task of open-ended text or preference evaluation, exposes fundamental limitations of current LLM judges and yields practical guidelines for reliable evaluation...

Abhigya Verma, Amit Kumar Saha, Seganrasan Subramanian et al. · 1 citation · ⚡1

Preprint Jul 2026

SynthDocBench: Controlled Benchmark for Long-Context Visual Document Understanding

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