---
title: "Who cites Stefano Soatto — 122 papers of our library"
description: "122 papers of the Elamur Research library cite the works of Stefano Soatto, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/stefano-soatto/cited-by/"
---
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# Who cites Stefano Soatto

123 citations of their works from 122 papers of our library (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← Stefano Soatto](https://md.research.elamur.ai/free/en/authors/stefano-soatto/)

1. [**Editing Models with Task Arithmetic arXiv:2212.04089**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
2. [**Transformers learn in-context by gradient descent arXiv:2212.07677**Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.*2022 · 247 citations*](https://md.research.elamur.ai/free/en/papers/oswald-2022-transformers-learn-context-gradient-descent/)
3. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
4. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 208 citations*
5. **[Exploring and Predicting Transferability across NLP Tasks](https://md.research.elamur.ai/free/en/papers/vu-2020-exploring-predicting-transferability-across-nlp/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tu Vu, Tong Wang, Tsendsuren Munkhdalai, et al.*2020 · 198 citations*
6. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models arXiv:2412.03603**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 169 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
7. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
8. [**A Survey of On-Policy Distillation for Large Language Models arXiv:2604.00626**Mingyang Song, Mao Zheng*2026 · 41 citations*](https://md.research.elamur.ai/free/en/papers/song-2026-survey-policy-distillation-large-language/)
9. [**Self-Distilled RLVR arXiv:2604.03128**Chenxu Yang, Chuanyu Qin, Qingyi Si, et al.*2026 · 37 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-self-distilled-rlvr/)
10. [**Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation arXiv:2604.13010**Yecheng Wu, Song Han, Han Cai*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wu-2026-lightning-opd-efficient-post-training/)
11. [**HDPO: Hybrid Distillation Policy Optimization via Privileged Self-Distillation arXiv:2603.23871**Ken Ding*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/ding-2026-hdpo-hybrid-distillation-policy-optimization/)
12. [**Self-Distilled Policy Gradient arXiv:2606.04036**Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/liu-2026-self-distilled-policy-gradient/)

110 more citing papers of our library have no page here yet.

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