--- title: "Who cites Attention is Not Only a Weight: Analyzing…" description: "125 papers of the Elamur Research library cite «Attention is Not Only a Weight: Analyzing Transformers with Vector Norms», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Attention is Not Only a Weight: Analyzing…](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/) / cited by # Who cites «Attention is Not Only a Weight: Analyzing Transformers with Vector Norms» 125 papers of our library cite it (of the 140,884 whose bibliographies we read) · 3 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/) 1. [**CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task**Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, et al.*2022 · 325 citations*](https://md.research.elamur.ai/free/en/papers/rei-2022-cometkiwi-ist-unbabel-2022-submission/) 2. [**Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning**Lean Wang, Lei Li, Damai Dai, et al.*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-label-words-anchors-information-flow/) 3. [**Aggregated Transformer Attention Measures Predict Reading Times Beyond Surprisal**Lukas Mielczarek, Laura Kallmeyer*2026*](https://md.research.elamur.ai/free/en/papers/mielczarek-2026-aggregated-transformer-attention-measures-predict/) 122 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/) — Attention is Not Only a Weight: Analyzing Transformers with Vector Norms