---
title: "Who cites Olivia Redfield — page 3 — 2,045 papers of our library"
description: "2,045 papers of the Elamur Research library cite the works of Olivia Redfield, found in their bibliographies · page 3 of 6 · 201–300; the most…"
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---
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# Who cites Olivia Redfield

2,045 citations of their works from 2,045 papers of our library (of the 149,439 whose bibliographies we read) · 510 with a page here, the most cited first · page 3 of 6 · 201–300 · [← Olivia Redfield](https://md.research.elamur.ai/free/en/authors/olivia-redfield/)

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201. **[Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Chen, Hexiang Hu, Yi Luan, et al.*2023 · 111 citations*
202. **[Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions](https://md.research.elamur.ai/free/en/papers/aliannejadi-2021-building-evaluating-open-domain-dialogue/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, et al.*2021 · 111 citations*
203. [**jina-embeddings-v3: Multilingual Embeddings With Task LoRA arXiv:2409.10173**Saba Sturua, Isabelle Mohr, Mohammad Kalim Akram, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/sturua-2024-jina-embeddings-v3-multilingual-embeddings/)
204. [**INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection arXiv:2402.03744**Chao Chen, Kai Liu, Ze Chen, et al.*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-inside-llms-internal-states-retain/)
205. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 106 citations*
206. **[Benchmarking Foundation Models with Language-Model-as-an-Examiner](https://md.research.elamur.ai/free/en/papers/bai-2023-benchmarking-foundation-models-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yushi Bai, Jiahao Ying, Yixin Cao, et al.*2023 · 106 citations*
207. **[SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2023-simlm-pre-training-representation-bottleneck/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2023 · 106 citations*
208. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
209. **[Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence](https://md.research.elamur.ai/free/en/papers/chen-2022-rich-knowledge-sources-bring-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hung-Ting Chen, Michael Zhang, Eunsol Choi*2022 · 105 citations*
210. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
211. **[Transformers for Tabular Data Representation: A Survey of Models and Applications](https://md.research.elamur.ai/free/en/papers/badaro-2023-transformers-tabular-data-representation-survey/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Gilbert Badaro, Mohammed Saeed, Paolo Papotti*2023 · 104 citations*
212. **[Look at the First Sentence: Position Bias in Question Answering](https://md.research.elamur.ai/free/en/papers/ko-2020-look-first-sentence-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, et al.*2020 · 104 citations*
213. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
214. **[Parallel Context Windows for Large Language Models](https://md.research.elamur.ai/free/en/papers/ratner-2023-parallel-context-windows-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nir Ratner, Yoav Levine, Yonatan Belinkov, et al.*2023 · 102 citations*
215. **[Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/ren-2025-investigating-factual-knowledge-boundary-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Ruiyang Ren, Yuhao Wang, Yingqi Qu, et al.*2025 · 101 citations*
216. [**Fine-grained Hallucination Detection and Editing for Language Models arXiv:2401.06855**Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2024-fine-grained-hallucination-detection-editing/)
217. **[AutoWebGLM: A Large Language Model-based Web Navigating Agent](https://md.research.elamur.ai/free/en/papers/lai-2024-autowebglm-large-language-model-based/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Hanyu Lai, Xiao Liu, Iat Long Iong, et al.*2024 · 96 citations*
218. **[WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences](https://md.research.elamur.ai/free/en/papers/liu-2023-webglm-efficient-web-enhanced/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Xiao Liu, Hanyu Lai, Hao Yu, et al.*2023 · 95 citations*
219. **[CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wu-2022-conqrr-conversational-query-rewriting-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zeqiu Wu, Yi Luan, Hannah Rashkin, et al.*2022 · 95 citations*
220. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 95 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
221. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations*
222. [**Proving Test Set Contamination in Black Box Language Models arXiv:2310.17623**Yonatan Oren, Nicole Meister, Niladri Chatterji, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/oren-2023-proving-test-set-contamination-black/)
223. **[QED: A Framework and Dataset for Explanations in Question Answering](https://md.research.elamur.ai/free/en/papers/lamm-2021-qed-framework-dataset-explanations-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Matthew Lamm, Jennimaria Palomaki, Chris Alberti, et al.*2021 · 91 citations*
224. **[Alignment for Honesty](https://md.research.elamur.ai/free/en/papers/yang-2023-alignment-honesty/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.*2023 · 90 citations*
225. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
226. [**Learning to Filter Context for Retrieval-Augmented Generation arXiv:2311.08377**Zhiruo Wang, Jun Araki, Zhengbao Jiang, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-learning-filter-context-retrieval-augmented/)
227. [**End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering arXiv:2106.05346**Devendra Singh Sachan, Siva Reddy, William Hamilton, et al.*2021 · 88 citations*](https://md.research.elamur.ai/free/en/papers/sachan-2021-end-end-training-multi-document/)
228. **[Complex Claim Verification with Evidence Retrieved in the Wild](https://md.research.elamur.ai/free/en/papers/chen-2024-complex-claim-verification-evidence-retrieved/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jifan Chen, Grace Kim, Aniruddh Sriram, et al.*2024 · 86 citations*
229. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
230. **[LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-Training](https://md.research.elamur.ai/free/en/papers/zhu-2024-llama-moe-building-mixture-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Zhu, Xiaoye Qu, Daize Dong, et al.*2024 · 85 citations*
231. **[DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering](https://md.research.elamur.ai/free/en/papers/neeman-2023-disentqa-disentangling-parametric-contextual-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ella Neeman, Roee Aharoni, Or Honovich, et al.*2023 · 85 citations*
232. **[CoLT5: Faster Long-Range Transformers with Conditional Computation](https://md.research.elamur.ai/free/en/papers/ainslie-2023-colt5-faster-long-range-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, Tao Lei, Michiel de Jong, et al.*2023 · 84 citations*
233. **[Selectively Answering Ambiguous Questions](https://md.research.elamur.ai/free/en/papers/cole-2023-selectively-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jeremy Cole, Michael Zhang, Daniel Gillick, et al.*2023 · 84 citations*
234. **[Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2023-tree-clarifications-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwoo Kim, Sungdong Kim, Byeongguk Jeon, et al.*2023 · 84 citations*
235. **[HalluLens: LLM Hallucination Benchmark](https://md.research.elamur.ai/free/en/papers/bang-2025-hallulens-llm-hallucination-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yejin Bang, Ziwei Ji, Alan Schelten, et al.*2025 · 82 citations*
236. [**PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models arXiv:2402.07867**Wei Zou, Runpeng Geng, Binghui Wang, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-poisonedrag-knowledge-corruption-attacks-retrieval/)
237. **[Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps](https://md.research.elamur.ai/free/en/papers/chuang-2024-lookback-lens-detecting-mitigating-contextual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, et al.*2024 · 78 citations*
238. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)
239. [**FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research arXiv:2405.13576**Jiajie Jin, Yutao Zhu, Guanting Dong, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-flashrag-modular-toolkit-efficient-retrieval/)
240. **[Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/laskar-2022-domain-adaptation-pre-trained-transformers/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang*2022 · 76 citations*
241. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
242. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/)
243. [**Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents arXiv:2310.19923**Michael Gunther, Jackmin Ong, Isabelle Mohr, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/gunther-2023-jina-embeddings-2-8192-token/)
244. [**Gecko: Versatile Text Embeddings Distilled from Large Language Models arXiv:2403.20327**Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-gecko-versatile-text-embeddings-distilled/)
245. [**QuRating: Selecting High-Quality Data for Training Language Models arXiv:2402.09739**Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/wettig-2024-qurating-selecting-high-quality-data/)
246. **[ScandEval: A Benchmark for Scandinavian Natural Language Processing](https://md.research.elamur.ai/free/en/papers/nielsen-2023-scandeval-benchmark-scandinavian-natural-language/) [Nordic Conference on Computational Linguistics (NoDaLiDa)](https://md.research.elamur.ai/free/en/venues/nodalida/)**Dan Nielsen*2023 · 73 citations*
247. [**InPars: Data Augmentation for Information Retrieval using Large Language Models arXiv:2202.05144**Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, et al.*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/bonifacio-2022-inpars-data-augmentation-information-retrieval/)
248. **[Tug-of-War between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-tug-war-between-knowledge-exploring/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhuoran Jin, Pengfei Cao, Yubo Chen, et al.*2024 · 70 citations*
249. **[Conditional Generation with a Question-Answering Blueprint](https://md.research.elamur.ai/free/en/papers/narayan-2023-conditional-generation-question-answering-blueprint/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, et al.*2023 · 70 citations*
250. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations*
251. [**LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations arXiv:2410.02707**Hadas Orgad, Michael Toker, Zorik Gekhman, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/orgad-2024-llms-know-more-than-they/)
252. **[Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue](https://md.research.elamur.ai/free/en/papers/gu-2024-model-editing-harms-general-abilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jia-Chen Gu, Hao-Xiang Xu, Jun-Yu Ma, et al.*2024 · 67 citations*
253. [**CREPE: Open-Domain Question Answering with False Presuppositions**Xinyan Yu, Sewon Min, Luke Zettlemoyer, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-crepe-open-domain-question-answering/)
254. **[Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/shi-2024-generate-then-ground-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengliang Shi, Shuo Zhang, Weiwei Sun, et al.*2024 · 65 citations*
255. **[Questions Are All You Need to Train a Dense Passage Retriever](https://md.research.elamur.ai/free/en/papers/sachan-2023-questions-are-all-you-need/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Devendra Singh Sachan, Mike Lewis, Dani Yogatama, et al.*2023 · 65 citations*
256. **[ParsiNLU: A Suite of Language Understanding Challenges for Persian](https://md.research.elamur.ai/free/en/papers/khashabi-2021-parsinlu-suite-language-understanding-challenges/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniel Khashabi, Arman Cohan, Siamak Shakeri, et al.*2021 · 65 citations*
257. [**Inquisitive Question Generation for High Level Text Comprehension**Wei-Jen Ko, Te-yuan Chen, Yiyan Huang, et al.*2020 · 65 citations*](https://md.research.elamur.ai/free/en/papers/ko-2020-inquisitive-question-generation-high-level/)
258. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
259. [**It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books**Bingsheng Yao, Dakuo Wang, Tongshuang Wu, et al.*2022 · 64 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-it-is-ai-s-turn/)
260. [**Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering**Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-which-linguist-invented-lightbulb-presupposition/)
261. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations*
262. [**In-context Pretraining: Language Modeling Beyond Document Boundaries arXiv:2310.10638**Weijia Shi, Sewon Min, Maria Lomeli, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/)
263. [**Shepherd: A Critic for Language Model Generation arXiv:2308.04592**Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-shepherd-critic-language-model-generation/)
264. **[Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks](https://md.research.elamur.ai/free/en/papers/asai-2022-evidentiality-guided-generation-knowledge-intensive/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Matt Gardner, Hannaneh Hajishirzi*2022 · 60 citations*
265. **[Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei Wang, Xingchen Wan, Ruoxi Sun, et al.*2025 · 59 citations*
266. **[BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zican Dong, Tianyi Tang, Junyi Li, et al.*2024 · 59 citations*
267. **[Bias in Large Language Models: Origin, Evaluation, and Mitigation](https://md.research.elamur.ai/free/en/papers/guo-2024-bias-large-language-models-origin/) [Electronics](https://md.research.elamur.ai/free/en/venues/electronics/)**Yufei Guo, Muzhe Guo, Juntao Su, et al.*2024 · 58 citations*
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