--- title: "Who cites Yichen Jiang — 172 papers of our library" description: "172 papers of the Elamur Research library cite the works of Yichen Jiang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/yichen-jiang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yichen-jiang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Yichen Jiang](https://md.research.elamur.ai/free/en/authors/yichen-jiang/) / cited by # Who cites Yichen Jiang 173 citations of their works from 172 papers of our library (of the 141,840 whose bibliographies we read) · 29 with a page here, the most cited first · [← Yichen Jiang](https://md.research.elamur.ai/free/en/authors/yichen-jiang/) 1. [**Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned arXiv:2209.07858**Deep Ganguli, Liane Lovitt, Jackson Kernion, et al.*2022 · 460 citations*](https://md.research.elamur.ai/free/en/papers/ganguli-2022-red-teaming-language-models-reduce/) **[Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations* **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations* **[Hierarchical Graph Network for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/fang-2020-hierarchical-graph-network-multi-hop/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuwei Fang, Siqi Sun, Zhe Gan, et al.*2020 · 241 citations* [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/) **[HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 221 citations* [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models arXiv:2405.17428**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 219 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/) **[Break It Down: A Question Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 218 citations* **[Unsupervised Question Decomposition for Question Answering](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 218 citations* [**Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP arXiv:2212.14024**Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/) **[The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2022-unreliability-explanations-few-shot-prompting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Greg Durrett*2022 · 196 citations* **[ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts](https://md.research.elamur.ai/free/en/papers/koreeda-2021-contractnli-dataset-document-level-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuta Koreeda, Christopher Manning*2021 · 177 citations* [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/) **[COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic](https://md.research.elamur.ai/free/en/papers/saakyan-2021-covid-fact-fact-extraction-verification/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arkadiy Saakyan, Tuhin Chakrabarty, Smaranda Muresan*2021 · 168 citations* **[QuALITY: Question Answering with Long Input Texts, Yes!](https://md.research.elamur.ai/free/en/papers/pang-2022-quality-question-answering-long-input/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al.*2022 · 162 citations* **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations* **[ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/qin-2021-erica-improving-entity-relation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujia Qin, Yankai Lin, Ryuichi Takanobu, et al.*2021 · 139 citations* **[MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/zhao-2022-multihiertt-numerical-reasoning-over-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Yunxiang Li, Chenying Li, et al.*2022 · 128 citations* [**MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries arXiv:2401.15391**Yixuan Tang, Yi Yang*2024 · 103 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-multihop-rag-benchmarking-retrieval-augmented/) **[DialFact: A Benchmark for Fact-Checking in Dialogue](https://md.research.elamur.ai/free/en/papers/gupta-2022-dialfact-benchmark-fact-checking-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 97 citations* **[Efficient Long-Text Understanding with Short-Text Models](https://md.research.elamur.ai/free/en/papers/ivgi-2023-efficient-long-text-understanding-short/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Maor Ivgi, Uri Shaham, Jonathan Berant*2023 · 93 citations* **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 89 citations* **[Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI](https://md.research.elamur.ai/free/en/papers/tian-2021-diagnosing-first-order-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jidong Tian, Yitian Li, Wenqing Chen, et al.*2021 · 86 citations* [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/) **[Robustifying Multi-hop QA through Pseudo-Evidentiality Training](https://md.research.elamur.ai/free/en/papers/lee-2021-robustifying-multi-hop-qa-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kyungjae Lee, Seung-won Hwang, Sang-eun Han, et al.*2021 · 19 citations* **[CRiT-QA: Evaluating Multi-hop Reasoning with Counterfactual Chains and Distractor Traps](https://md.research.elamur.ai/free/en/papers/yun-2026-crit-qa-evaluating-multi-hop/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jungmin Yun, June Hyoung Kwon, Youngbin Kim*2026* 143 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/yichen-jiang/) — Yichen Jiang