---
title: "Keihanshin — works of 2023: 5 papers, the most cited first"
description: "5 works of Keihanshin from 2023 in our library, the most cited first. Among them: GPT-RE: In-context Learning for Relation Extraction using…"
canonical: "https://research.elamur.ai/free/en/agglomerations/keihanshin/year/2023/"
---
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# Works of Keihanshin from 2023

5 works · the most cited first · [← Keihanshin](https://md.research.elamur.ai/free/en/agglomerations/keihanshin/)

1. **[GPT-RE: In-context Learning for Relation Extraction using Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 253 citations*
2. **[FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN](https://md.research.elamur.ai/free/en/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Milind Agarwal, Sweta Agrawal, Antonios Anastasopoulos, et al.*2023 · 152 citations*
3. [**PandaGPT: One Model To Instruction-Follow Them All arXiv:2305.16355**Yixuan Su, Tian Lan, Huayang Li, et al.*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/su-2023-pandagpt-one-model-instruction-follow/)
4. [**Knowledge Sanitization of Large Language Models arXiv:2309.11852**Yoichi Ishibashi, Hidetoshi Shimodaira*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/ishibashi-2023-knowledge-sanitization-large-language-models/)
5. **[BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisition](https://md.research.elamur.ai/free/en/papers/oba-2023-babylm-challenge-curriculum-learning-based/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Miyu Oba, Akari Haga, Akiyo Fukatsu, et al.*2023 · 9 citations*
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