HAKARI-Bench reconstructs 35 benchmarks into 551 tasks across 43 languages, reproducing full MTEB, MMTEB, and BEIR rankings with Spearman correlation above 0.97 while supporting efficiency variant comparisons.
Ruri: Japanese general text embeddings
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
The paper constructs an SCPI dataset via LLM-based annotation and trains classifiers to detect sensitive personal information in Japanese pre-training corpora, claiming this is the first such exploration.
JFinTEB is the first benchmark for evaluating Japanese financial text embeddings across retrieval and classification tasks derived from realistic financial scenarios.
citing papers explorer
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HAKARI-Bench: A Lightweight Benchmark for Comparing Retrieval Architectures and Efficiency Settings under Unified Conditions
HAKARI-Bench reconstructs 35 benchmarks into 551 tasks across 43 languages, reproducing full MTEB, MMTEB, and BEIR rankings with Spearman correlation above 0.97 while supporting efficiency variant comparisons.
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Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models
The paper constructs an SCPI dataset via LLM-based annotation and trains classifiers to detect sensitive personal information in Japanese pre-training corpora, claiming this is the first such exploration.
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JFinTEB: Japanese Financial Text Embedding Benchmark
JFinTEB is the first benchmark for evaluating Japanese financial text embeddings across retrieval and classification tasks derived from realistic financial scenarios.