---
title: "Social Sciences — papers, page 3 — Elamur Research"
description: "Social Sciences: 744 papers of the Elamur Research library · page 3 of 9 · 126–225, the most cited first — our summary of each, its ideas…"
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# 🤝 Social Sciences

744 papers · page 3 of 9 · 126–225 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Society, politics, law, education, communication, geography and the study of language in use.

## Papers (744)

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126. [**Green AI**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
127. [**Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good**Xuewei Wang, Weiyan Shi, Richard Kim, et al.*2019 · 369 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-persuasion-good-personalized-persuasive-dialogue/)
128. [**Political Ideology Detection Using Recursive Neural Networks**Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, et al.*2014 · 369 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2014-political-ideology-detection-recursive-neural/)
129. [**Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence**Federico Bianchi, Silvia Terragni, Dirk Hovy*2021 · 366 citations*](https://md.research.elamur.ai/free/en/papers/bianchi-2021-pre-training-is-hot-topic/)
130. [**Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection**Maarten Sap, Swabha Swayamdipta, Laura Vianna, et al.*2022 · 365 citations*](https://md.research.elamur.ai/free/en/papers/sap-2022-annotators-attitudes-how-annotator-beliefs/)
131. [**Latent Hatred: A Benchmark for Understanding Implicit Hate Speech**Mai ElSherief, Caleb Ziems, David Muchlinski, et al.*2021 · 365 citations*](https://md.research.elamur.ai/free/en/papers/elsherief-2021-latent-hatred-benchmark-understanding-implicit/)
132. [**The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation**Barbara Plank*2022 · 364 citations*](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/)
133. [**Identifying and Reducing Gender Bias in Word-Level Language Models**Shikha Bordia, Samuel R. Bowman*2019 · 364 citations*](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/)
134. [**The Media Frames Corpus: Annotations of Frames Across Issues**Dallas Card, Amber E. Boydstun, Justin H. Gross, et al.*2015 · 359 citations*](https://md.research.elamur.ai/free/en/papers/card-2015-media-frames-corpus-annotations-frames/)
135. [**Adversarial Removal of Demographic Attributes from Text Data**Yanai Elazar, Yoav Goldberg*2018 · 357 citations*](https://md.research.elamur.ai/free/en/papers/elazar-2018-adversarial-removal-demographic-attributes-text/)
136. [**Towards Understanding Sycophancy in Language Models**Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2023-towards-understanding-sycophancy-language-models/)
137. [**BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 352 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/)
138. [**Toxicity in chatgpt: Analyzing persona-assigned language models**Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, et al.*2023 · 346 citations*](https://md.research.elamur.ai/free/en/papers/deshpande-2023-toxicity-chatgpt-analyzing-persona-assigned/)
139. [**The Creation and Analysis of a Website Privacy Policy Corpus**Shomir Wilson, Florian Schaub, Aswarth Abhilash Dara, et al.*2016 · 336 citations*](https://md.research.elamur.ai/free/en/papers/wilson-2016-creation-analysis-website-privacy-policy/)
140. [**SemEval-2019 Task 4: Hyperpartisan News Detection**Johannes Kiesel, Maria Mestre, Rishabh Shukla, et al.*2019 · 335 citations*](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/)
141. [**Predicting Factuality of Reporting and Bias of News Media Sources**Ramy Baly, Georgi Karadzhov, Dimitar Alexandrov, et al.*2018 · 335 citations*](https://md.research.elamur.ai/free/en/papers/baly-2018-predicting-factuality-reporting-bias-news/)
142. [**A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection**Aditya Bohra, Deepanshu Vijay, Vinay Singh, et al.*2018 · 333 citations*](https://md.research.elamur.ai/free/en/papers/bohra-2018-dataset-hindi-english-code-mixed/)
143. [**Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings**Thomas Manzini, Lim Yao Chong, Alan W Black, et al.*2019 · 332 citations*](https://md.research.elamur.ai/free/en/papers/manzini-2019-black-is-criminal-as-caucasian/)
144. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 331 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
145. [**Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 325 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-cultural-shift-or-linguistic-drift/)
146. [**The Fact Extraction and VERification (FEVER) Shared Task**James Thorne, Andreas Vlachos, Oana Cocarascu, et al.*2018 · 322 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-fact-extraction-verification-fever-shared/)
147. [**Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection**Bertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.*2021 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2021-learning-worst-dynamically-generated-datasets/)
148. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 319 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
149. [**Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI)**Elisabetta Fersini, Debora Nozza, Paolo Rosso*2018 · 315 citations*](https://md.research.elamur.ai/free/en/papers/fersini-2018-overview-evalita-2018-task-automatic/)
150. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
151. [**Gender Bias in Machine Translation**Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.*2021 · 310 citations*](https://md.research.elamur.ai/free/en/papers/savoldi-2021-gender-bias-machine-translation/)
152. [**Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?**Peter Hase, Mohit Bansal*2020 · 309 citations*](https://md.research.elamur.ai/free/en/papers/hase-2020-evaluating-explainable-ai-which-algorithmic/)
153. [**Discovering Language Model Behaviors with Model-Written Evaluations**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 307 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
154. [**Challenges and frontiers in abusive content detection**Bertie Vidgen, Alex Harris, Dong Nguyen, et al.*2019 · 307 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2019-challenges-frontiers-abusive-content-detection/)
155. [**Get out the vote: Determining support or opposition from Congressional floor-debate transcripts**Matt Thomas, Bo Pang, Lillian Lee*2006 · 307 citations*](https://md.research.elamur.ai/free/en/papers/thomas-2006-get-out-vote-determining-support/)
156. [**From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/)
157. [**Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model**Marzieh Mozafari, Reza Farahbakhsh, Noel Crespi*2020 · 305 citations*](https://md.research.elamur.ai/free/en/papers/mozafari-2020-hate-speech-detection-racial-bias/)
158. [**Automated Fact Checking: Task Formulations, Methods and Future Directions**James Thorne, Andreas Vlachos*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-automated-fact-checking-task-formulations/)
159. [**Learning to Write with Cooperative Discriminators**Ari Holtzman, Jan Buys, Maxwell Forbes, et al.*2018 · 301 citations*](https://md.research.elamur.ai/free/en/papers/holtzman-2018-learning-write-cooperative-discriminators/)
160. [**Multi-step Jailbreaking Privacy Attacks on ChatGPT**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/)
161. [**S2ORC: The Semantic Scholar Open Research Corpus**Kyle Lo, Lucy Lu Wang, Mark Neumann, et al.*2019 · 298 citations*](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/)
162. [**Towards Debiasing Fact Verification Models**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/)
163. [**Evaluating Verifiability in Generative Search Engines**Nelson Liu, Tianyi Zhang, Percy Liang*2023 · 294 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/)
164. [**A Benchmark Dataset for Learning to Intervene in Online Hate Speech**Jing Qian, Anna Bethke, Yinyin Liu, et al.*2019 · 292 citations*](https://md.research.elamur.ai/free/en/papers/qian-2019-benchmark-dataset-learning-intervene-online/)
165. [**Ethical Research Protocols for Social Media Health Research**Adrian Benton, Glen Coppersmith, Mark Dredze*2017 · 292 citations*](https://md.research.elamur.ai/free/en/papers/benton-2017-ethical-research-protocols-social-media/)
166. [**SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours**Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/)
167. [**Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/)
168. [**GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification**Jie Zhou, Xu Han, Cheng Yang, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/)
169. [**A Bayesian Mixed Effects Model of Literary Character**David Bamman, Ted Underwood, Noah A. Smith*2014 · 285 citations*](https://md.research.elamur.ai/free/en/papers/bamman-2014-bayesian-mixed-effects-model-literary/)
170. [**Large-Scale Multi-Label Text Classification on EU Legislation**Ilias Chalkidis, Emmanouil Fergadiotis, Prodromos Malakasiotis, et al.*2019 · 283 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2019-large-scale-multi-label-text/)
171. [**Fine-grained Fact Verification with Kernel Graph Attention Network**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/)
172. [**Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/)
173. [**COVIDLies: Detecting COVID-19 Misinformation on Social Media**Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, et al.*2020 · 270 citations*](https://md.research.elamur.ai/free/en/papers/hossain-2020-covidlies-detecting-covid-19-misinformation/)
174. [**Having Beer after Prayer? Measuring Cultural Bias in Large Language Models**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/)
175. [**Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations**Emily Allaway, Kathleen McKeown*2020 · 268 citations*](https://md.research.elamur.ai/free/en/papers/allaway-2020-zero-shot-stance-detection-dataset/)
176. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
177. [**CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review**Dan Hendrycks, Collin Burns, Anya Chen, et al.*2021 · 267 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-cuad-expert-annotated-nlp-dataset/)
178. [**Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study**Yi Liu, Gelei Deng, Zhengzi Xu, et al.*2023 · 266 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-jailbreaking-chatgpt-prompt-engineering-empirical/)
179. [**Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation**Emily Dinan, Angela Fan, Adina Williams, et al.*2020 · 266 citations*](https://md.research.elamur.ai/free/en/papers/dinan-2020-queens-are-powerful-too-mitigating/)
180. [**Towards Understanding and Mitigating Social Biases in Language Models**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
181. [**Evaluating the Underlying Gender Bias in Contextualized Word Embeddings**Christine Basta, Marta R. Costa-jussà, Noe Casas*2019 · 265 citations*](https://md.research.elamur.ai/free/en/papers/basta-2019-evaluating-underlying-gender-bias-contextualized/)
182. [**Towards Measuring the Representation of Subjective Global Opinions in Language Models**Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.*2023 · 262 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2023-towards-measuring-representation-subjective-global/)
183. [**Detection of Abusive Language: the Problem of Biased Datasets**Michael Wiegand, Josef Ruppenhofer, Thomas Kleinbauer*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/wiegand-2019-detection-abusive-language-problem-biased/)
184. [**Towards Debiasing Sentence Representations**Paul Pu Liang, Irene Mengze Li, Emily Zheng, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-debiasing-sentence-representations/)
185. [**Distinguish Confusing Law Articles for Legal Judgment Prediction**Nuo Xu, Pinghui Wang, Long Chen, et al.*2020 · 258 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-distinguish-confusing-law-articles-legal/)
186. [**UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification**Andreas Hanselowski, Hao Zhang, Zile Li, et al.*2018 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2018-ukp-athene-multi-sentence-textual/)
187. [**L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language**Hala Mulki, Hatem Haddad, Chedi Bechikh Ali, et al.*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/mulki-2019-l-hsab-levantine-twitter-dataset/)
188. [**Hurtlex: A Multilingual Lexicon of Words to Hurt**Elisa Bassignana, Valerio Basile, Viviana Patti*2018 · 255 citations*](https://md.research.elamur.ai/free/en/papers/bassignana-2018-hurtlex-multilingual-lexicon-words-hurt/)
189. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
190. [**Decolonising Speech and Language Technology**Steven Bird*2020 · 254 citations*](https://md.research.elamur.ai/free/en/papers/bird-2020-decolonising-speech-language-technology/)
191. [**Societal Biases in Language Generation: Progress and Challenges**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 253 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/)
192. [**Measuring and Reducing Gendered Correlations in Pre-trained Models**Kellie Webster, Xuezhi Wang, Ian Tenney, et al.*2020 · 253 citations*](https://md.research.elamur.ai/free/en/papers/webster-2020-measuring-reducing-gendered-correlations-pre/)
193. [**An Italian Twitter Corpus of Hate Speech against Immigrants**Manuela Sanguinetti, Fabio Poletto, Cristina Bosco, et al.*2018 · 253 citations*](https://md.research.elamur.ai/free/en/papers/sanguinetti-2018-italian-twitter-corpus-hate-speech/)
194. [**Revisiting Readability: A Unified Framework for Predicting Text Quality**Emily Pitler, Ani Nenkova*2008 · 253 citations*](https://md.research.elamur.ai/free/en/papers/pitler-2008-revisiting-readability-unified-framework-predicting/)
195. [**ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation**Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam, et al.*2021 · 251 citations*](https://md.research.elamur.ai/free/en/papers/malik-2021-ildc-cjpe-indian-legal-documents/)
196. [**Generalizing Word Lattice Translation**Christopher Dyer, Smaranda Muresan, Philip Resnik*2008 · 249 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2008-generalizing-word-lattice-translation/)
197. [**Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings**Rishi Bommasani, Kelly Davis, Claire Cardie*2020 · 248 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2020-interpreting-pretrained-contextualized-representations-reductions/)
198. [**Overview of the EVALITA 2018 Hate Speech Detection Task**Cristina Bosco, Felice Dell'Orletta, Fabio Poletto, et al.*2018 · 248 citations*](https://md.research.elamur.ai/free/en/papers/bosco-2018-overview-evalita-2018-hate-speech/)
199. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 247 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
200. [**DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/)
201. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
202. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
203. [**Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations**Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-synthetic-data-generation-large-language/)
204. [**Stance Classification using Dialogic Properties of Persuasion**Marilyn Walker, Pranav Anand, Rob Abbott, et al.*2012 · 241 citations*](https://md.research.elamur.ai/free/en/papers/walker-2012-stance-classification-dialogic-properties-persuasion/)
205. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 239 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
206. [**Conventional Orthography for Dialectal Arabic**Nizar Habash, Mona Diab, Owen Rambow*2012 · 237 citations*](https://md.research.elamur.ai/free/en/papers/habash-2012-conventional-orthography-dialectal-arabic/)
207. [**Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models**Myra Cheng, Esin Durmus, Dan Jurafsky*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2023-marked-personas-natural-language-prompts/)
208. [**SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification**Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, et al.*2022 · 234 citations*](https://md.research.elamur.ai/free/en/papers/fersini-2022-semeval-2022-task-5-multimedia/)
209. [**Stance Classification of Ideological Debates: Data, Models, Features, and Constraints**Kazi Saidul Hasan, Vincent Ng*2013 · 233 citations*](https://md.research.elamur.ai/free/en/papers/hasan-2013-stance-classification-ideological-debates-data/)
210. [**ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning**Petter Tornberg*2023 · 231 citations*](https://md.research.elamur.ai/free/en/papers/tornberg-2023-chatgpt-4-outperforms-experts-crowd/)
211. [**Cross-topic Argument Mining from Heterogeneous Sources**Christian Stab, Tristan Miller, Benjamin Schiller, et al.*2018 · 229 citations*](https://md.research.elamur.ai/free/en/papers/stab-2018-cross-topic-argument-mining-heterogeneous/)
212. [**Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies**Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, et al.*2021 · 228 citations*](https://md.research.elamur.ai/free/en/papers/dev-2021-harms-gender-exclusivity-challenges-non/)
213. [**Learning to Deceive with Attention-Based Explanations**Danish Pruthi, Mansi Gupta, Bhuwan Dhingra, et al.*2020 · 227 citations*](https://md.research.elamur.ai/free/en/papers/pruthi-2020-learning-deceive-attention-based-explanations/)
214. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
215. [**A Survey of Hallucination in Large Foundation Models**Vipula Rawte, Amit Sheth, Amitava Das*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-survey-hallucination-large-foundation-models/)
216. [**Identifying Appropriate Support for Propositions in Online User Comments**Joonsuk Park, Claire Cardie*2014 · 222 citations*](https://md.research.elamur.ai/free/en/papers/park-2014-identifying-appropriate-support-propositions-online/)
217. [**HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/)
218. [**Reasoning Over Semantic-Level Graph for Fact Checking**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/)
219. [**Few-Shot Charge Prediction with Discriminative Legal Attributes**Zikun Hu, Xiang Li, Cunchao Tu, et al.*2018 · 221 citations*](https://md.research.elamur.ai/free/en/papers/hu-2018-few-shot-charge-prediction-discriminative/)
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