TW-LegalBench evaluates 13 LLMs on over 30,000 Taiwanese legal tasks from exams and judgments, showing top models pass lawyer thresholds but struggle with exact statute citations.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
CIExplainer uses causal inference via the Potential Outcome Framework to find high-impact subgraphs for GNN explanations, with G2TeXplainer generating feature and relation-aware natural language descriptions.
citing papers explorer
-
TW-LegalBench: Measuring Taiwanese Legal Understanding
TW-LegalBench evaluates 13 LLMs on over 30,000 Taiwanese legal tasks from exams and judgments, showing top models pass lawyer thresholds but struggle with exact statute citations.
-
CIExplainer++: Generating Causal and Interpretable Explanations for Graph Neural Networks
CIExplainer uses causal inference via the Potential Outcome Framework to find high-impact subgraphs for GNN explanations, with G2TeXplainer generating feature and relation-aware natural language descriptions.