🔗 Who cites «Improving Length-Generalization in Transformers via Task Hinting»

7 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · ← back to «Improving Length-Generalization in Transformers via Task Hinting»

1. H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language ModelsarXiv:2306.14048Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.2023 · 124 citations
2. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
3. Transformers Can Achieve Length Generalization But Not RobustlyarXiv:2402.09371Yongchao Zhou, Uri Alon, Xinyun Chen, et al.2024 · 29 citations
4. Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic PuzzlesConference on Neural Information Processing Systems (NeurIPS)Kulin Shah, Nishanth Dikkala, Xin Wang, et al.2024 · 12 citations

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

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