Who cites «Compositional Evaluation on Japanese Textual Entailment and Similarity»
- Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language CapabilitiesarXiv:2404.17790Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.2024 · 114 citations
- MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
- Label and Explanation Variation in LLM-Based Annotation: a Case Study in Natural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Artur Kulmizev, Erika Lombart, Patrick Watrin, et al.2026 · 2 citations
- Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMsLanguage Resources and Evaluation Conference (LREC)Kei Moriyama, Takashi Kodama, Kouta Nakayama2026
- JSTS-Neg: Japanese Semantic Textual Similarity Dataset for Evaluating Negation Understanding AbilityLanguage Resources and Evaluation Conference (LREC)Reiko Yuasa, Yoshihide Kato, Shigeki Matsubara2026
This page in Markdown → https://md.research.elamur.ai/free/en/papers/yanaka-2022-compositional-evaluation-japanese-textual-entailment/cited-by/