🔗 Who cites «All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality»

74 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality»

1. Eliciting Latent Predictions from Transformers with the Tuned LensNora Belrose, Igor Ostrovsky, Lev McKinney, et al.2023 · 179 citations
2. The case for 4-bit precision: k-bit Inference Scaling LawsTim Dettmers, Luke Zettlemoyer2022 · 119 citations
3. Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word EmbeddingsTimothee Mickus, Kees Van Deemter, Mathieu Constant, et al.2022 · 59 citations
4. On Quick Kisses and How to Make Them Count: A Study on Event Construal in Light Verb Constructions with BERTChenxin Liu, Emmanuele Chersoni2023 · 2 citations
5. Embedding Similarity Is Not Quality Estimation: Lessons from Replacing a Dedicated QE ModelDimitrios Zaikis, Andrea Biondo, Matthew Dixon, et al.2026
6. From sunblock to softblock: Analyzing the correlates of neology in published writing and on social mediaMaria Ryskina, Matthew R. Gormley, Kyle Mahowald, et al.2026
7. Is Cross-Lingual Transfer in Bilingual Models Human-Like? A Study with Overlapping Word Forms in Dutch and EnglishIza Škrjanec, Irene Elisabeth Winther, Vera Demberg, et al.2026

67 more papers of our library cite it; they have no page here yet.

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