🧑‍🔬 Who cites Zhiying Jiang

235 citations of their works from 233 papers of our library (of the 149,439 whose bibliographies we read) · 45 with a page here, the most cited first · ← Zhiying Jiang

1. Large Language Models for Information Retrieval: A SurveyACM Transactions on Information SystemsYutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen2023 · 339 citations
2. mGPT: Few-Shot Learners Go MultilingualarXiv:2204.07580Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.2022 · 203 citations
3. Re2G: Retrieve, Rerank, GenerateConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.2022 · 184 citations
4. ToolQA: A Dataset for LLM Question Answering with External ToolsConference on Neural Information Processing Systems (NeurIPS)Yuchen Zhuang, Yue Yu, Kuan Wang, et al.2023 · 182 citations
5. Promptagator: Few-shot Dense Retrieval From 8 ExamplesarXiv:2209.11755Zhuyun Dai, Vincent Y. Zhao, Ji Ma, et al.2022 · 170 citations
6. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
7. LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt CompressionarXiv:2310.06839Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.2023 · 158 citations
8. How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language modelConference on Neural Information Processing Systems (NeurIPS)Michael Hanna, Ollie Liu, Alexandre Variengien2023 · 151 citations
9. Searching for Best Practices in Retrieval-Augmented GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.2024 · 150 citations
10. MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse LanguagesTransactions of the Association for Computational Linguistics (TACL)Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, et al.2023 · 149 citations
11. Representing Numbers in NLP: a Survey and a VisionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Avijit Thawani, Jay Pujara, Filip Ilievski, et al.2021 · 139 citations
12. SciMON: Scientific Inspiration Machines Optimized for NoveltyAnnual Meeting of the Association for Computational Linguistics (ACL)Qingyun Wang, Doug Downey, Heng Ji, et al.2023 · 131 citations
13. In-context Autoencoder for Context Compression in a Large Language ModelarXiv:2307.06945Tao Ge, Jing Hu, Lei Wang, et al.2023 · 114 citations
14. ExT5: Towards Extreme Multi-Task Scaling for Transfer LearningarXiv:2111.10952Vamsi Aribandi, Yi Tay, Tal Schuster, et al.2021 · 114 citations
15. Evaluating the Evaluation of Diversity in Natural Language GenerationConference of the European Chapter of the Association for Computational Linguistics (EACL)Guy Tevet, Jonathan Berant2021 · 106 citations
16. Teaching Algorithmic Reasoning via In-context LearningarXiv:2211.09066Hattie Zhou, Azade Nova, Hugo Larochelle, et al.2022 · 96 citations
17. How well do Large Language Models perform in Arithmetic tasks?arXiv:2304.02015Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 93 citations
18. AutoSurvey: Large Language Models Can Automatically Write SurveysConference on Neural Information Processing Systems (NeurIPS)Yidong Wang, Qi Guo, Wenjin Yao, et al.2024 · 91 citations
19. Language Modeling Is CompressionarXiv:2309.10668Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.2023 · 91 citations
20. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
21. InPars: Data Augmentation for Information Retrieval using Large Language ModelsarXiv:2202.05144Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, et al.2022 · 72 citations
22. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
23. Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic TasksarXiv:2305.14201Tiedong Liu, Bryan Kian Hsiang Low2023 · 65 citations
24. Questions Are All You Need to Train a Dense Passage RetrieverTransactions of the Association for Computational Linguistics (TACL)Devendra Singh Sachan, Mike Lewis, Dani Yogatama, et al.2023 · 65 citations
25. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
26. Tokenization counts: the impact of tokenization on arithmetic in frontier LLMsarXiv:2402.14903Aaditya K. Singh, DJ Strouse2024 · 55 citations
27. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow InstructionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Orion Weller, Benjamin Chang, Sean MacAvaney, et al.2025 · 40 citations
28. Linear algebra with transformersarXiv:2112.01898François Charton2021 · 31 citations
29. Can Large Language Models Unlock Novel Scientific Research Ideas?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal, et al.2025 · 27 citations
30. Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and EvaluationACM Computing SurveysSteffen Eger, Yong Cao, Jennifer D'Souza, et al.2025 · 25 citations
31. Evaluating Transformer Language Models on Arithmetic Operations Using Number DecompositionLanguage Resources and Evaluation Conference (LREC)Matteo Muffo, Aldo Cocco, Enrico Bertino2022 · 19 citations
32. Explaining Relationships Among Research PapersInternational Conference on Computational Linguistics (COLING)Xiangci Li, Jessica Ouyang2025 · 11 citations
33. Test-time Corpus Feedback: From Retrieval to RAGFindings of the Association for Computational LinguisticsMandeep Rathee, Venktesh V, Sean MacAvaney, et al.2026 · 4 citations
34. Tokenisation is NP-CompleteAnnual Meeting of the Association for Computational Linguistics (ACL)Philip Whittington, Gregor Bachmann, Tiago Pimentel2025 · 4 citations
35. Leveraging Syntactic Dependencies in Disambiguation: The Case of African American EnglishLanguage Resources and Evaluation Conference (LREC)Wilermine Previlon, Alice Rozet, Jotsna Gowda, et al.2024 · 4 citations
36. Itri Amigos at ArAIEval Shared Task: Transformer vs. Compression-Based Models for Persuasion Techniques and Disinformation DetectionArabic Natural Language Processing Conference (ArabicNLP)Jehad Oumer, Nouman Ahmed, Natalia Flechas Manrique2023 · 2 citations
37. Conversational Assistants to Support Patients with Heart Failure: Comparing a Neurosymbolic Architecture with GPTLanguage Resources and Evaluation Conference (LREC)Anuja Tayal, Devika Salunke, Barbara Di Eugenio, et al.2026 · 1 citation
38. Diffusion-CAM: Faithful Visual Explanations for dMLLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Haomin Zuo, Yidi Li, Luoxiao Yang, et al.2026 · 1 citation
39. Language Modeling for the Future of Finance: A Survey into Metrics, Tasks, and Data OpportunitiesWorkshop on Generation, Evaluation and Metrics (GEM)Nikita Tatarinov, Siddhant Sukhani, Agam Shah, et al.2026 · 1 citation
40. Mechanistic Interpretability of Text-to-Image Diffusion Models via Cross-Attention InterventionsFindings of the Association for Computational LinguisticsMaisha Maliha, Dean F. Hougen2026 · 1 citation
41. ReAttn: Improving Attention-based Re-ranking via Attention Re-weightingFindings of the Association for Computational LinguisticsYuxing Tian, Fengran Mo, Weixu Zhang, et al.2026 · 1 citation
42. 1,729 vs. 1729: The Effect of Scripts and Formats on LLM NumeracyFindings of the Association for Computational LinguisticsVarshini Reddy, Craig W Schmidt, Seth Ebner, et al.2026
43. Bloom-Eval: A Hierarchical Evaluation Benchmark for Automatic Survey Generation Based on Bloom's TaxonomyAnnual Meeting of the Association for Computational Linguistics (ACL)Fei Zhang, Zhe Zhao, HaiBin Wen, et al.2026
44. Stop Hardening Everything: A Training-Free Neuron-Level Defense for Neural Ranking ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yu-An Liu, Ruqing Zhang, Hongru Song, et al.2026
45. Test-Time Training for Zero-Resource Dense Retrieval RerankingWorkshop on Towards Knowledgeable Foundation ModelsShiyan Liu, Yichen Li2026

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