---
title: "Who cites Heinrich Kuttler — page 2 — 3,463 citing papers"
description: "3,463 papers of the Elamur Research library cite the works of Heinrich Kuttler, found in their bibliographies · page 2 of 8 · 101–200; the most…"
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---
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# Who cites Heinrich Kuttler

3,530 citations of their works from 3,463 papers of our library (of the 149,439 whose bibliographies we read) · 728 with a page here, the most cited first · page 2 of 8 · 101–200 · [← Heinrich Kuttler](https://md.research.elamur.ai/free/en/authors/heinrich-kuttler/)

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101. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
102. [**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/)
103. [**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/)
104. [**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/)
105. **[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*
106. [**Prompting GPT-3 To Be Reliable arXiv:2210.09150**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
107. [**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/)
108. **[RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 207 citations*
109. **[Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs](https://md.research.elamur.ai/free/en/papers/ovadia-2024-fine-tuning-or-retrieval-comparing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.*2024 · 206 citations*
110. **[Woodpecker: Hallucination Correction for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/yin-2023-woodpecker-hallucination-correction-multimodal-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Shukang Yin, Chaoyou Fu, Sirui Zhao, et al.*2023 · 206 citations*
111. **[Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning](https://md.research.elamur.ai/free/en/papers/wang-2021-improving-named-entity-recognition-external/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Wang, Yong Jiang, Nguyen Bach, et al.*2021 · 206 citations*
112. **[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*
113. **[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*
114. **[MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text](https://md.research.elamur.ai/free/en/papers/chen-2022-murag-multimodal-retrieval-augmented-generator/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Hexiang Hu, Xi Chen, et al.*2022 · 199 citations*
115. [**Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers arXiv:2409.04109**Chenglei Si, Diyi Yang, Tatsunori Hashimoto*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/si-2024-llms-generate-novel-research/)
116. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
117. [**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/)
118. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 193 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
119. [**One Embedder, Any Task: Instruction-Finetuned Text Embeddings arXiv:2212.09741**Hongjin Su, Weijia Shi, Jungo Kasai, et al.*2022 · 193 citations*](https://md.research.elamur.ai/free/en/papers/su-2022-one-embedder-any-task-instruction/)
120. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations*
121. [**Grounded Language Learning in a Simulated 3D World arXiv:1706.06551**Karl Moritz Hermann, Felix Hill, Simon Green, et al.*2017 · 190 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2017-grounded-language-learning-simulated-3d/)
122. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
123. [**LawBench: Benchmarking Legal Knowledge of Large Language Models arXiv:2309.16289**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 188 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
124. [**Pre-training via Paraphrasing arXiv:2006.15020**Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, et al.*2020 · 187 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-pre-training-paraphrasing/)
125. **[Towards Building Multilingual Language Model for Medicine](https://md.research.elamur.ai/free/en/papers/qiu-2024-towards-building-multilingual-language-model/) [Nature Communications](https://md.research.elamur.ai/free/en/venues/nature-communications/)**Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.*2024 · 184 citations*
126. **[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*
127. **[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*
128. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 182 citations*
129. **[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*
130. **[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*
131. **[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*
132. **[A-MEM: Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/xu-2025-mem-agentic-memory-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wujiang Xu, Zujie Liang, Kai Mei, et al.*2025 · 178 citations*
133. [**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/)
134. [**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/)
135. **[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*
136. **[Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/jeong-2024-improving-medical-reasoning-through-retrieval/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Minbyul Jeong, Jiwoong Sohn, Mujeen Sung, et al.*2024 · 164 citations*
137. **[CultureLLM: Incorporating Cultural Differences into Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-culturellm-incorporating-cultural-differences-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Cheng Li, Mengzhou Chen, Jindong Wang, et al.*2024 · 162 citations*
138. **[LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 161 citations*
139. [**FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios arXiv:2307.13528**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
140. **[MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2024-mindmap-knowledge-graph-prompting-sparks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilin Wen, Zifeng Wang, Jimeng Sun*2024 · 158 citations*
141. [**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/)
142. **[MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models](https://md.research.elamur.ai/free/en/papers/xu-2020-megatron-cntrl-controllable-story-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peng Xu, Mostofa Patwary, Mohammad Shoeybi, et al.*2020 · 158 citations*
143. **[Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/zhang-2024-extract-define-canonicalize-llm-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Zhang, Harold Soh*2024 · 155 citations*
144. **[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*
145. **[Multilingual Autoregressive Entity Linking](https://md.research.elamur.ai/free/en/papers/cao-2022-multilingual-autoregressive-entity-linking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nicola De Cao, Ledell Wu, Kashyap Popat, et al.*2022 · 153 citations*
146. [**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/)
147. [**A Review on Language Models as Knowledge Bases arXiv:2204.06031**Badr AlKhamissi, Millicent Li, Asli Celikyilmaz, et al.*2022 · 150 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2022-review-language-models-knowledge-bases/)
148. **[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*
149. **[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*
150. [**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/)
151. [**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/)
152. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 147 citations*
153. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
154. [**Rethinking with Retrieval: Faithful Large Language Model Inference arXiv:2301.00303**Hangfeng He, Hongming Zhang, Dan Roth*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/)
155. **[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*
156. **[Retrieval-based Language Models and Applications](https://md.research.elamur.ai/free/en/papers/asai-2023-retrieval-based-language-models-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akari Asai, Sewon Min, Zexuan Zhong, et al.*2023 · 141 citations*
157. **[DRAGIN: Dynamic Retrieval Augmented Generation based on the Real-time Information Needs of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-dragin-dynamic-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weihang Su, Yichen Tang, Qingyao Ai, et al.*2024 · 137 citations*
158. [**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/)
159. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/)
160. **[Self-Knowledge Guided Retrieval Augmentation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-self-knowledge-guided-retrieval-augmentation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yile Wang, Peng Li, Maosong Sun, et al.*2023 · 135 citations*
161. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation arXiv:2310.03214**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
162. **[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*
163. **[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*
164. **[Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://md.research.elamur.ai/free/en/papers/shao-2024-assisting-writing-wikipedia-like-articles/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yijia Shao, Yucheng Jiang, Theodore Kanell, et al.*2024 · 131 citations*
165. **[A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://md.research.elamur.ai/free/en/papers/yi-2024-survey-recent-advances-llm-based/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Zihao Yi, Jiarui Ouyang, Zhe Xu, et al.*2024 · 130 citations*
166. [**Retrieval meets Long Context Large Language Models arXiv:2310.03025**Peng Xu, Wei Ping, Xianchao Wu, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/)
167. **[Efficient Nearest Neighbor Language Models](https://md.research.elamur.ai/free/en/papers/he-2021-efficient-nearest-neighbor-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick*2021 · 130 citations*
168. [**Understanding the planning of LLM agents: A survey arXiv:2402.02716**Xu Huang, Weiwen Liu, Xiaolong Chen, et al.*2024 · 128 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-understanding-planning-llm-agents-survey/)
169. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform arXiv:2501.13944**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
170. [**Fine-tuning Language Models for Factuality arXiv:2311.08401**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
171. **[InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 126 citations*
172. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
173. **[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*
174. **[Generative Spoken Dialogue Language Modeling](https://md.research.elamur.ai/free/en/papers/nguyen-2023-generative-spoken-dialogue-language-modeling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tu Anh Nguyen, Eugene Kharitonov, Jade Copet, et al.*2023 · 124 citations*
175. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
176. **[Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/wu-2021-good-misconceived-reasons-empirical-revisiting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyong Wu, Lingpeng Kong, Wei Bi, et al.*2021 · 120 citations*
177. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
178. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
179. [**RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation arXiv:2303.12570**Fengji Zhang, Bei Chen, Yue Zhang, et al.*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-repocoder-repository-level-code-completion/)
180. [**Physics of Language Models: Part 3.1, Knowledge Storage and Extraction arXiv:2309.14316**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-3/)
181. **[KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2022-kg-fid-infusing-knowledge-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donghan Yu, Chenguang Zhu, Yuwei Fang, et al.*2022 · 116 citations*
182. **[End-to-End Training of Neural Retrievers for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/sachan-2021-end-end-training-neural-retrievers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Devendra Sachan, Mostofa Patwary, Mohammad Shoeybi, et al.*2021 · 116 citations*
183. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
184. [**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/)
185. [**BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents arXiv:2504.12516**Jason Wei, Zhiqing Sun, Spencer Papay, et al.*2025 · 114 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-browsecomp-simple-yet-challenging-benchmark/)
186. [**In-context Autoencoder for Context Compression in a Large Language Model arXiv:2307.06945**Tao Ge, Jing Hu, Lei Wang, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-context-autoencoder-context-compression-large/)
187. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
188. [**Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources arXiv:2305.13269**Xingxuan Li, Ruochen Zhao, Yew Ken Chia, et al.*2023 · 112 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-chain-knowledge-grounding-large-language/)
189. [**PaperQA: Retrieval-Augmented Generative Agent for Scientific Research arXiv:2312.07559**Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/)
190. **[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*
191. **[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*
192. **[CDLM: Cross-Document Language Modeling](https://md.research.elamur.ai/free/en/papers/caciularu-2021-cdlm-cross-document-language-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Avi Caciularu, Arman Cohan, Iz Beltagy, et al.*2021 · 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. **[Chain of Agents: Large Language Models Collaborating on Long-Context Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2024-chain-agents-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.*2024 · 104 citations*
196. [**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/)
197. **[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*
198. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
199. **[Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation](https://md.research.elamur.ai/free/en/papers/bulian-2022-tomayto-tomahto-beyond-token-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jannis Bulian, Christian Buck, Wojciech Gajewski, et al.*2022 · 100 citations*
200. **[ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/chen-2025-research-learning-reason-search-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mingyang Chen, Linzhuang Sun, Tianpeng Li, et al.*2025 · 99 citations*

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