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Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe

Paper recorded by Signals 4 on 2026-09-04 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.AI · 人工智能 · first seen 2026-09-07

Abstract

Data-sovereignty regulations increasingly require public institutions to deploy open-source, on-premise LLM agents that chain multiple tool-calls across live government APIs. However, open-source models consistently underperform in this multi-step setting, and no existing benchmark measures the gap. We introduce the Korean Open Public API Benchmark (KOPA-Bench), comprising 145 real-world tasks. To

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#164 most recent of 300 cs.AI papers we have recorded · ↑ newer: A Deep Generative Model for Synthesizing Labeled Wireless Signals · ↓ older: Necessary or Sufficient? Evaluating LLM Explanations With Behavioural
Cite this page: Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe: the #164 most recent of 300 cs.AI papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/multi-step-tool-calling-over-korean-open-public-apis-a-benchmark-and-a-data-synt.html
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