--- title: "Who cites Induction Networks for Few-Shot Text Classification" description: "64 papers of the Elamur Research library cite «Induction Networks for Few-Shot Text Classification», found in their bibliographies; the most…" canonical: "https://research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Induction Networks for Few-Shot Text…](https://md.research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/) / cited by # Who cites «Induction Networks for Few-Shot Text Classification» 64 papers of our library cite it (of the 141,840 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Induction Networks for Few-Shot Text Classification»](https://md.research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/) 1. **[Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network](https://md.research.elamur.ai/free/en/papers/hou-2020-few-shot-slot-tagging-collapsed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutai Hou, Wanxiang Che, Yongkui Lai, et al.*2020 · 265 citations* 2. **[CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/das-2022-container-few-shot-named-entity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sarkar Snigdha Sarathi Das, Arzoo Katiyar, Rebecca Passonneau, et al.*2022 · 233 citations* 62 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/geng-2019-induction-networks-few-shot-text/) — Induction Networks for Few-Shot Text Classification