---
title: "Who cites Scaling Instruction-Finetuned Language Models —…"
description: "2,187 papers of the Elamur Research library cite «Scaling Instruction-Finetuned Language Models», found in their bibliographies · page 2 of 3 · 101–200…"
canonical: "https://research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/cited-by/page/2/"
---
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# Who cites «Scaling Instruction-Finetuned Language Models»

2,187 papers of our library cite it (of the 141,840 whose bibliographies we read) · 257 with a page here, the most cited first · page 2 of 3 · 101–200 · [← the paper](https://md.research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/)

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101. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
102. [**Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback**Viet Lai, Chien Nguyen, Nghia Ngo, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-okapi-instruction-tuned-large-language/)
103. [**GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/)
104. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
105. [**Towards Building Multilingual Language Model for Medicine**Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.*2024 · 183 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2024-towards-building-multilingual-language-model/)
106. [**GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models**Archiki Prasad, Peter Hase, Xiang Zhou, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/prasad-2023-grips-gradient-free-edit-based/)
107. [**On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning**Omar Shaikh, Hongxin Zhang, William Held, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/shaikh-2023-second-thought-let-s-not/)
108. [**The False Promise of Imitating Proprietary LLMs**Arnav Gudibande, Eric Wallace, Charlie Snell, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/gudibande-2023-false-promise-imitating-proprietary-llms/)
109. [**ToolQA: A Dataset for LLM Question Answering with External Tools**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/)
110. [**Learning to Compress Prompts with Gist Tokens**Jesse Mu, Xiang Lisa Li, Noah Goodman*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/mu-2023-learning-compress-prompts-gist-tokens/)
111. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**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/)
112. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
113. [**Binding Language Models in Symbolic Languages**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 167 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
114. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
115. [**Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/)
116. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/)
117. [**Reasoning with Language Model Prompting: A Survey**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
118. [**Orca 2: Teaching Small Language Models How to Reason**Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/)
119. [**MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/)
120. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/)
121. [**VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/)
122. [**LLM-based NLG Evaluation: Current Status and Challenges**Mingqi Gao, Xinyu Hu, Xunjian Yin, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-llm-based-nlg-evaluation-current/)
123. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 151 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
124. [**The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models**Junyi Li, Jie Chen, Ruiyang Ren, et al.*2024 · 150 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-dawn-after-dark-empirical-study/)
125. [**Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation**Marius Mosbach, Tiago Pimentel, Shauli Ravfogel, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/mosbach-2023-few-shot-fine-tuning-vs/)
126. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
127. [**Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering**Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/adlakha-2024-evaluating-correctness-faithfulness-instruction-following/)
128. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/)
129. [**Context-faithful Prompting for Large Language Models**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/)
130. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
131. [**PMC-LLaMA: Towards Building Open-source Language Models for Medicine**Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-pmc-llama-towards-building-open/)
132. [**Executable Code Actions Elicit Better LLM Agents**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
133. [**Generative Verifiers: Reward Modeling as Next-Token Prediction**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
134. [**MiniLLM: On-Policy Distillation of Large Language Models**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
135. [**Dense X Retrieval: What Retrieval Granularity Should We Use?**Tong Chen, Hongwei Wang, Sihao Chen, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/)
136. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
137. [**A fine-grained comparison of pragmatic language understanding in humans and language models**Jennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/)
138. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
139. [**Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/)
140. [**InFoBench: Evaluating Instruction Following Ability in Large Language Models**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/)
141. [**Prompting is not a substitute for probability measurements in large language models**Jennifer Hu, Roger Levy*2023 · 133 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/)
142. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/)
143. [**Self-Alignment with Instruction Backtranslation**Xian Li, Ping Yu, Chunting Zhou, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/)
144. [**Task-aware Retrieval with Instructions**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/)
145. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/)
146. [**GPT-4V(ision) is a Generalist Web Agent, if Grounded**Boyuan Zheng, Boyu Gou, Jihyung Kil, et al.*2024 · 130 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-gpt-4v-ision-generalist-web/)
147. [**MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/)
148. [**MAGE: Machine-generated Text Detection in the Wild**Yafu Li, Qintong Li, Leyang Cui, et al.*2024 · 129 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-mage-machine-generated-text-detection/)
149. [**Deductive Verification of Chain-of-Thought Reasoning**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/)
150. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models**Shahriar Golchin, Mihai Surdeanu*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/)
151. [**Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions**Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/bianchi-2023-safety-tuned-llamas-lessons-improving/)
152. [**DePlot: One-shot visual language reasoning by plot-to-table translation**Fangyu Liu, Julian Eisenschlos, Francesco Piccinno, et al.*2023 · 121 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-deplot-one-shot-visual-language/)
153. [**Fine-tuning Language Models for Factuality**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
154. [**UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/)
155. [**Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors**Kai Zhang, Bernal Jimenez Gutierrez, Yu Su*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-aligning-instruction-tasks-unlocks-large/)
156. [**The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning**Seungone Kim, Se Joo, Doyoung Kim, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-cot-collection-improving-zero-shot/)
157. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
158. [**Large Language Models Understand and Can be Enhanced by Emotional Stimuli**Cheng Li, Jindong Wang, Yixuan Zhang, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-understand-enhanced/)
159. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
160. [**ALLaM: Large Language Models for Arabic and English**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/)
161. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
162. [**Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study**Yi Chen, Rui Wang, Haiyun Jiang, et al.*2023 · 113 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-exploring-use-large-language-models/)
163. [**GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP**Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/khondaker-2023-gptaraeval-comprehensive-evaluation-chatgpt-arabic/)
164. [**ExpertQA: Expert-Curated Questions and Attributed Answers**Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/malaviya-2024-expertqa-expert-curated-questions-attributed/)
165. [**Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?**Yang Chen, Hexiang Hu, Yi Luan, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/)
166. [**We're Afraid Language Models Aren't Modeling Ambiguity**Alisa Liu, Zhaofeng Wu, Julian Michael, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-we-re-afraid-language-models/)
167. [**TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models**Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.*2023 · 106 citations*](https://md.research.elamur.ai/free/en/papers/gekhman-2023-trueteacher-learning-factual-consistency-evaluation/)
168. [**SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks**Bill Yuchen Lin, Yicheng Fu, Karina Yang, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-swiftsage-generative-agent-fast-slow/)
169. [**LENS: A Learnable Evaluation Metric for Text Simplification**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/)
170. [**LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition**Chengsong Huang, Qian Liu, Bill Yuchen Lin, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/)
171. [**BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting**Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/yong-2023-bloom-1-adding-language-support/)
172. [**Statistical Rejection Sampling Improves Preference Optimization**Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-statistical-rejection-sampling-improves-preference/)
173. [**MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning**Ke Wang, Houxing Ren, Aojun Zhou, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mathcoder-seamless-code-integration-llms/)
174. [**LongAlign: A Recipe for Long Context Alignment of Large Language Models**Yushi Bai, Xin Lv, Jiajie Zhang, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longalign-recipe-long-context/)
175. [**Inseq: An Interpretability Toolkit for Sequence Generation Models**Gabriele Sarti, Nils Feldhus, Ludwig Sickert, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/sarti-2023-inseq-interpretability-toolkit-sequence-generation/)
176. [**Bactrian-X: Multilingual Replicable Instruction-Following Models with Low-Rank Adaptation**Haonan Li, Fajri Koto, Minghao Wu, et al.*2023 · 95 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-bactrian-x-multilingual-replicable-instruction/)
177. [**MAmmoTH2: Scaling Instructions from the Web**Xiang Yue, Tuney Zheng, Ge Zhang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mammoth2-scaling-instructions-web/)
178. [**On Learning to Summarize with Large Language Models as References**Yixin Liu, Kejian Shi, Katherine He, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/)
179. [**Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate**Kai Xiong, Xiao Ding, Yixin Cao, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-examining-inter-consistency-large-language/)
180. [**FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets**Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-flask-fine-grained-language-model/)
181. [**INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models**Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chia-2023-instructeval-towards-holistic-evaluation-instruction/)
182. [**Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks**Andrea Sottana, Bin Liang, Kai Zou, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/sottana-2023-evaluation-metrics-era-gpt-4/)
183. [**Learning to Filter Context for Retrieval-Augmented Generation**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/)
184. [**On the Tool Manipulation Capability of Open-source Large Language Models**Qiantong Xu, Fenglu Hong, Bo Li, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-tool-manipulation-capability-open-source/)
185. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
186. [**LLM Comparative Assessment: Zero-shot NLG Evaluation through Pairwise Comparisons using Large Language Models**Adian Liusie, Potsawee Manakul, Mark Gales*2024 · 86 citations*](https://md.research.elamur.ai/free/en/papers/liusie-2024-llm-comparative-assessment-zero-shot/)
187. [**PromptNER: Prompting For Named Entity Recognition**Dhananjay Ashok, Zachary C. Lipton*2023 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ashok-2023-promptner-prompting-named-entity-recognition/)
188. [**The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs**Laura Ruis, Akbir Khan, Stella Biderman, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ruis-2022-goldilocks-pragmatic-understanding-fine-tuning/)
189. [**A Survey on Data Selection for Language Models**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
190. [**Benchmarking Vision Language Models for Cultural Understanding**Shravan Nayak, Kanishk Jain, Rabiul Awal, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/nayak-2024-benchmarking-vision-language-models-cultural/)
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