---
title: "Who cites Olivia Redfield — page 2 — 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 2 of 5 · 101–200; 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) · 444 with a page here, the most cited first · page 2 of 5 · 101–200 · [← Olivia Redfield](https://md.research.elamur.ai/free/en/authors/olivia-redfield/)

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101. [**BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage arXiv:2208.03188**Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.*2022 · 241 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2022-blenderbot-3-deployed-conversational-agent/)
102. **[Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 239 citations*
103. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
104. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
105. **[A Discrete Hard EM Approach for Weakly Supervised Question Answering](https://md.research.elamur.ai/free/en/papers/min-2019-discrete-hard-em-approach-weakly/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Danqi Chen, Hannaneh Hajishirzi, et al.*2019 · 237 citations*
106. **[Hurdles to Progress in Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/krishna-2021-hurdles-progress-long-form-question/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kalpesh Krishna, Aurko Roy, Mohit Iyyer*2021 · 233 citations*
107. **[Open-Domain Question Answering Goes Conversational via Question Rewriting](https://md.research.elamur.ai/free/en/papers/anantha-2021-open-domain-question-answering-goes/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, et al.*2021 · 228 citations*
108. **[Coreferential Reasoning Learning for Language Representation](https://md.research.elamur.ai/free/en/papers/ye-2020-coreferential-reasoning-learning-language-representation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Deming Ye, Yankai Lin, Jiaju Du, et al.*2020 · 228 citations*
109. **[Transformer Memory as a Differentiable Search Index](https://md.research.elamur.ai/free/en/papers/tay-2022-transformer-memory-differentiable-search-index/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yi Tay, Vinh Q. Tran, Mostafa Dehghani, et al.*2022 · 223 citations*
110. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models arXiv:2405.17428**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 222 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
111. [**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 · 222 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/)
112. **[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 · 222 citations*
113. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models arXiv:2308.16149**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 218 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
114. [**Teaching language models to support answers with verified quotes arXiv:2203.11147**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 218 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/)
115. **[Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-Trained Language Models](https://md.research.elamur.ai/free/en/papers/lin-2020-birds-have-four-legs-numersense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, et al.*2020 · 218 citations*
116. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
117. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 212 citations*
118. **[Search-o1: Agentic Search-Enhanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/li-2025-search-o1-agentic-search-enhanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.*2025 · 211 citations*
119. [**Internet-augmented language models through few-shot prompting for open-domain question answering arXiv:2203.05115**Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, et al.*2022 · 209 citations*](https://md.research.elamur.ai/free/en/papers/lazaridou-2022-internet-augmented-language-models-through/)
120. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
121. **[Neural Arabic Question Answering](https://md.research.elamur.ai/free/en/papers/mozannar-2019-neural-arabic-question-answering/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Hussein Mozannar, Elie Maamary, Karl El Hajal, et al.*2019 · 206 citations*
122. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs arXiv:2310.01801**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/)
123. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
124. **[Improving Passage Retrieval with Zero-Shot Question Generation](https://md.research.elamur.ai/free/en/papers/sachan-2022-improving-passage-retrieval-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Devendra Sachan, Mike Lewis, Mandar Joshi, et al.*2022 · 199 citations*
125. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
126. [**Making Retrieval-Augmented Language Models Robust to Irrelevant Context arXiv:2310.01558**Ori Yoran, Tomer Wolfson, Ori Ram, et al.*2023 · 195 citations*](https://md.research.elamur.ai/free/en/papers/yoran-2023-making-retrieval-augmented-language-models/)
127. **[Unsupervised Question Answering by Cloze Translation](https://md.research.elamur.ai/free/en/papers/lewis-2019-unsupervised-question-answering-cloze-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Patrick Lewis, Ludovic Denoyer, Sebastian Riedel*2019 · 195 citations*
128. [**PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization arXiv:2306.05087**Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pandalm-automatic-evaluation-benchmark-llm/)
129. [**One Embedder, Any Task: Instruction-Finetuned Text Embeddings arXiv:2212.09741**Hongjin Su, Weijia Shi, Jungo Kasai, et al.*2022 · 194 citations*](https://md.research.elamur.ai/free/en/papers/su-2022-one-embedder-any-task-instruction/)
130. [**Effective Long-Context Scaling of Foundation Models arXiv:2309.16039**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
131. **[Re2G: Retrieve, Rerank, Generate](https://md.research.elamur.ai/free/en/papers/glass-2022-re2g-retrieve-rerank-generate/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, et al.*2022 · 184 citations*
132. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
133. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
134. [**The False Promise of Imitating Proprietary LLMs arXiv:2305.15717**Arnav Gudibande, Eric Wallace, Charlie Snell, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/gudibande-2023-false-promise-imitating-proprietary-llms/)
135. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model arXiv:2502.02737**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 181 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
136. **[Evaluating Retrieval Quality in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/salemi-2024-evaluating-retrieval-quality-retrieval-augmented/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Alireza Salemi, Hamed Zamani*2024 · 181 citations*
137. **[RealTime QA: What's the Answer Right Now?](https://md.research.elamur.ai/free/en/papers/kasai-2022-realtime-qa-s-answer-right/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, et al.*2022 · 181 citations*
138. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
139. **[On the Risk of Misinformation Pollution with Large Language Models](https://md.research.elamur.ai/free/en/papers/pan-2023-risk-misinformation-pollution-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yikang Pan, Liangming Pan, Wenhu Chen, et al.*2023 · 179 citations*
140. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
141. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
142. [**Promptagator: Few-shot Dense Retrieval From 8 Examples arXiv:2209.11755**Zhuyun Dai, Vincent Y. Zhao, Ji Ma, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/dai-2022-promptagator-few-shot-dense-retrieval/)
143. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 169 citations*
144. **[SCROLLS: Standardized CompaRison Over Long Language Sequences](https://md.research.elamur.ai/free/en/papers/shaham-2022-scrolls-standardized-comparison-over-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Uri Shaham, Elad Segal, Maor Ivgi, et al.*2022 · 165 citations*
145. **[Explanations for CommonsenseQA: New Dataset and Models](https://md.research.elamur.ai/free/en/papers/aggarwal-2021-explanations-commonsenseqa-new-dataset-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.*2021 · 164 citations*
146. **[Question Answering for Privacy Policies: Combining Computational and Legal Perspectives](https://md.research.elamur.ai/free/en/papers/ravichander-2019-question-answering-privacy-policies-combining/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abhilasha Ravichander, Alan W Black, Shomir Wilson, et al.*2019 · 163 citations*
147. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models arXiv:2307.11088**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/)
148. [**Measuring short-form factuality in large language models arXiv:2411.04368**Jason Wei, Nguyen Karina, Hyung Won Chung, et al.*2024 · 160 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-measuring-short-form-factuality-large/)
149. [**Jamba: A Hybrid Transformer-Mamba Language Model arXiv:2403.19887**Opher Lieber, Barak Lenz, Hofit Bata, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/lieber-2024-jamba-hybrid-transformer-mamba-language/)
150. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression arXiv:2310.06839**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
151. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 157 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
152. **[LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/elhoushi-2024-layerskip-enabling-early-exit-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.*2024 · 156 citations*
153. **[GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2022-gpl-generative-pseudo-labeling-unsupervised/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kexin Wang, Nandan Thakur, Nils Reimers, et al.*2022 · 155 citations*
154. [**Generation-Augmented Retrieval for Open-domain Question Answering arXiv:2009.08553**Yuning Mao, Pengcheng He, Xiaodong Liu, et al.*2020 · 151 citations*](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/)
155. **[Searching for Best Practices in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2024-searching-best-practices-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.*2024 · 150 citations*
156. **[Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yu-2024-chain-note-enhancing-robustness-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhao Yu, Hongming Zhang, Xiaoman Pan, et al.*2024 · 149 citations*
157. **[Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering](https://md.research.elamur.ai/free/en/papers/adlakha-2024-evaluating-correctness-faithfulness-instruction-following/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, et al.*2024 · 149 citations*
158. **[MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages](https://md.research.elamur.ai/free/en/papers/zhang-2023-miracl-multilingual-retrieval-dataset-covering/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, et al.*2023 · 149 citations*
159. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning arXiv:2310.01352**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 149 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
160. [**TALM: Tool Augmented Language Models arXiv:2205.12255**Aaron Parisi, Yao Zhao, Noah Fiedel*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2022-talm-tool-augmented-language-models/)
161. **[Context-faithful Prompting for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 148 citations*
162. **[Text Embeddings Reveal (Almost) As Much As Text](https://md.research.elamur.ai/free/en/papers/morris-2023-text-embeddings-reveal-almost-as/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Morris, Volodymyr Kuleshov, Vitaly Shmatikov, et al.*2023 · 147 citations*
163. **[UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/oguz-2022-unik-qa-unified-representations-structured/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Barlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.*2022 · 147 citations*
164. **[Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 146 citations*
165. **[RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder](https://md.research.elamur.ai/free/en/papers/xiao-2022-retromae-pre-training-retrieval-oriented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shitao Xiao, Zheng Liu, Yingxia Shao, et al.*2022 · 145 citations*
166. **[TopiOCQA: Open-domain Conversational Question Answering with Topic Switching](https://md.research.elamur.ai/free/en/papers/adlakha-2022-topiocqa-open-domain-conversational-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, et al.*2022 · 145 citations*
167. **[Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation](https://md.research.elamur.ai/free/en/papers/ma-2021-zero-shot-neural-passage-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ji Ma, Ivan Korotkov, Yinfei Yang, et al.*2021 · 144 citations*
168. **[Dense X Retrieval: What Retrieval Granularity Should We Use?](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Chen, Hongwei Wang, Sihao Chen, et al.*2024 · 142 citations*
169. **[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*
170. [**Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models arXiv:2404.18796**Pat Verga, Sebastian Hofstatter, Sophia Althammer, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/verga-2024-replacing-judges-juries-evaluating-llm/)
171. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models arXiv:2212.08037**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 138 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
172. [**RAFT: Adapting Language Model to Domain Specific RAG arXiv:2403.10131**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/)
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175. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 133 citations*
176. **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 132 citations*
177. **[Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion](https://md.research.elamur.ai/free/en/papers/shuster-2022-language-models-that-seek-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, et al.*2022 · 132 citations*
178. **[Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup](https://md.research.elamur.ai/free/en/papers/gao-2021-scaling-deep-contrastive-learning-batch/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Luyu Gao, Yunyi Zhang, Jiawei Han, et al.*2021 · 131 citations*
179. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
180. **[Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/chen-2020-open-domain-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danqi Chen, Wen-tau Yih*2020 · 129 citations*
181. **[LM vs LM: Detecting Factual Errors via Cross Examination](https://md.research.elamur.ai/free/en/papers/cohen-2023-lm-vs-lm-detecting-factual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Roi Cohen, May Hamri, Mor Geva, et al.*2023 · 126 citations*
182. **[Learning Dense Representations of Phrases at Scale](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhyuk Lee, Mujeen Sung, Jaewoo Kang, et al.*2021 · 126 citations*
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186. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation arXiv:2310.04408**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
187. **[DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 113 citations*
188. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
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190. **[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*
191. **[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*
192. **[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*
193. **[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*
194. **[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*
195. **[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*
196. **[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*
197. [**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/)
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199. **[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*
200. [**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/)

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