arXiv 2609.29167 · cs.AI · 2026-09-24
IndicBankBench: Evaluating Safety and Reliability of Language Model Assistants in Indian Retail Banking
Suvradip Paul, Chandra Bhushan, Harsh Sharma, Nitin Kukreja, Yatharth Dedhia, Keyur Doshi, Prashant Devadiga
National Payments Corporation of India
在最新榜 #300 本站收录于 2026-10-21
一句话要点
IndicBankBench 用 799 个印度零售银行案例，分阶段评估银行助手的安全、工具调用和回答质量。
IndicBankBench evaluates Indian retail-banking assistants on 799 cases across safety, tool use and answer quality.
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主题与学科
同主题：安全与可解释
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- Lexical Reference Frames: Interpreting LM Residual Streams in Native Semantics ▲55
- U-Space: Uncovering When and Why Uncertainty Arises in Language Models ▲54
- Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failures ▲29
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-22。
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