GRAB is a benchmark dataset of 1.61M sentences from 8,247 10-K filings with taxonomy-anchored weak supervision labels for standardized evaluation of unsupervised topic models on financial risk disclosures.
M ulti F in: A dataset for multilingual financial NLP
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
JFinTEB is the first benchmark for evaluating Japanese financial text embeddings across retrieval and classification tasks derived from realistic financial scenarios.
citing papers explorer
-
GRAB: A Risk Taxonomy--Grounded Benchmark for Unsupervised Topic Discovery in Financial Disclosures
GRAB is a benchmark dataset of 1.61M sentences from 8,247 10-K filings with taxonomy-anchored weak supervision labels for standardized evaluation of unsupervised topic models on financial risk disclosures.
-
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.