---
title: "Who cites The Curious Case of — page 2 — 1,581 citing papers"
description: "1,581 papers of the Elamur Research library cite «The Curious Case of Neural Text Degeneration», found in their bibliographies · page 2 of 4…"
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---
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# Who cites «The Curious Case of Neural Text Degeneration»

1,581 papers of our library cite it (of the 149,439 whose bibliographies we read) · 343 with a page here, the most cited first · page 2 of 4 · 101–200 · [← back to «The Curious Case of Neural Text Degeneration»](https://md.research.elamur.ai/free/en/papers/holtzman-2019-curious-case-neural-text-degeneration/)

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101. **[Challenges in Detoxifying Language Models](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 213 citations*
102. **[Do Massively Pretrained Language Models Make Better Storytellers?](https://md.research.elamur.ai/free/en/papers/see-2019-massively-pretrained-language-models-make/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Abigail See, Aneesh Pappu, Rohun Saxena, et al.*2019 · 213 citations*
103. [**Generating Training Data with Language Models: Towards Zero-Shot Language Understanding arXiv:2202.04538**Yu Meng, Jiaxin Huang, Yu Zhang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/meng-2022-generating-training-data-language-models/)
104. **[On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?](https://md.research.elamur.ai/free/en/papers/dziri-2022-origin-hallucinations-conversational-models-is/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nouha Dziri, Sivan Milton, Mo Yu, et al.*2022 · 208 citations*
105. [**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/)
106. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears arXiv:2304.05302**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
107. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 198 citations*
108. **[Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering](https://md.research.elamur.ai/free/en/papers/honovich-2021-q-2-evaluating-factual-consistency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Or Honovich, Leshem Choshen, Roee Aharoni, et al.*2021 · 196 citations*
109. **[LLM in a flash: Efficient Large Language Model Inference with Limited Memory](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.*2024 · 193 citations*
110. [**Multilingual Jailbreak Challenges in Large Language Models arXiv:2310.06474**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
111. [**DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models arXiv:2210.08933**Shansan Gong, Mukai Li, Jiangtao Feng, et al.*2022 · 189 citations*](https://md.research.elamur.ai/free/en/papers/gong-2022-diffuseq-sequence-sequence-text-generation/)
112. **[VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 184 citations*
113. **[Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/zhang-2020-grounded-conversation-generation-as-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houyu Zhang, Zhenghao Liu, Chenyan Xiong, et al.*2020 · 183 citations*
114. **[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*
115. **[CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages](https://md.research.elamur.ai/free/en/papers/nguyen-2023-culturax-cleaned-enormous-multilingual-dataset/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.*2023 · 181 citations*
116. **[Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 178 citations*
117. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs arXiv:2210.12283**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 178 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/)
118. **[Large Language Model Unlearning](https://md.research.elamur.ai/free/en/papers/yao-2023-large-language-model-unlearning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuanshun Yao, Xiaojun Xu, Yang Liu*2023 · 174 citations*
119. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
120. **[Unsupervised Opinion Summarization as Copycat-Review Generation](https://md.research.elamur.ai/free/en/papers/brazinskas-2020-unsupervised-opinion-summarization-as-copycat/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arthur Bražinskas, Mirella Lapata, Ivan Titov*2020 · 173 citations*
121. **[DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text](https://md.research.elamur.ai/free/en/papers/su-2023-detectllm-leveraging-log-rank-information/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyan Su, Terry Zhuo, Di Wang, et al.*2023 · 172 citations*
122. **[Quark: Controllable Text Generation with Reinforced Unlearning](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 170 citations*
123. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation arXiv:2310.06987**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/)
124. **[Factuality Enhanced Language Models for Open-Ended Text Generation](https://md.research.elamur.ai/free/en/papers/lee-2022-factuality-enhanced-language-models-open/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nayeon Lee, Wei Ping, Peng Xu, et al.*2022 · 168 citations*
125. **[Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eikema-2020-is-map-decoding-all-you/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bryan Eikema, Wilker Aziz*2020 · 167 citations*
126. **[Membership Inference Attacks against Language Models via Neighbourhood Comparison](https://md.research.elamur.ai/free/en/papers/mattern-2023-membership-inference-attacks-against-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, et al.*2023 · 165 citations*
127. [**AgentTuning: Enabling Generalized Agent Abilities for LLMs arXiv:2310.12823**Aohan Zeng, Mingdao Liu, Rui Lu, et al.*2023 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2023-agenttuning-enabling-generalized-agent/)
128. **[If beam search is the answer, what was the question?](https://md.research.elamur.ai/free/en/papers/meister-2020-if-beam-search-is-answer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clara Meister, Ryan Cotterell, Tim Vieira*2020 · 163 citations*
129. [**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/)
130. **[Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Antoine Louis, Gijs van Dijck, Gerasimos Spanakis*2023 · 157 citations*
131. **[Locally Typical Sampling](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 157 citations*
132. **[Explaining NLP Models via Minimal Contrastive Editing (MiCE)](https://md.research.elamur.ai/free/en/papers/ross-2021-explaining-nlp-models-minimal-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexis Ross, Ana Marasović, Matthew Peters*2021 · 155 citations*
133. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation arXiv:2305.15852**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
134. **[Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text](https://md.research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, et al.*2022 · 152 citations*
135. **[Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding](https://md.research.elamur.ai/free/en/papers/dziri-2021-neural-path-hunter-reducing-hallucination/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nouha Dziri, Andrea Madotto, Osmar Zaïane, et al.*2021 · 152 citations*
136. **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 150 citations*
137. **[Self-Evaluation Guided Beam Search for Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2023-self-evaluation-guided-beam-search/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.*2023 · 149 citations*
138. **[Language Model Behavior: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/chang-2024-language-model-behavior-comprehensive-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tyler A. Chang, Benjamin K. Bergen*2024 · 148 citations*
139. **[Quality-Aware Decoding for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fernandes-2022-quality-aware-decoding-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Fernandes, António Farinhas, Ricardo Rei, et al.*2022 · 146 citations*
140. [**MiniLLM: On-Policy Distillation of Large Language Models arXiv:2306.08543**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
141. [**Efficient Training of Language Models to Fill in the Middle arXiv:2207.14255**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
142. [**A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation arXiv:2307.03987**Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/varshney-2023-stitch-time-saves-nine-detecting/)
143. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics arXiv:2302.12433**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
144. **[A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 142 citations*
145. **[Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features](https://md.research.elamur.ai/free/en/papers/rashkin-2021-increasing-faithfulness-knowledge-grounded-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hannah Rashkin, David Reitter, Gaurav Singh Tomar, et al.*2021 · 141 citations*
146. **[NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics](https://md.research.elamur.ai/free/en/papers/lu-2022-neurologic-esque-decoding-constrained-text/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ximing Lu, Sean Welleck, Peter West, et al.*2022 · 140 citations*
147. **[Paragraph-level Simplification of Medical Texts](https://md.research.elamur.ai/free/en/papers/devaraj-2021-paragraph-level-simplification-medical-texts/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ashwin Devaraj, Iain Marshall, Byron Wallace, et al.*2021 · 140 citations*
148. [**Self-Alignment with Instruction Backtranslation arXiv:2308.06259**Xian Li, Ping Yu, Chunting Zhou, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/)
149. [**Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets arXiv:2106.10328**Irene Solaiman, Christy Dennison OpenAI)*2021 · 136 citations*](https://md.research.elamur.ai/free/en/papers/solaiman-2021-process-adapting-language-models-society/)
150. [**Secrets of RLHF in Large Language Models Part I: PPO arXiv:2307.04964**Rui Zheng, Shihan Dou, Songyang Gao, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/)
151. [**Analyzing and Mitigating Object Hallucination in Large Vision-Language Models arXiv:2310.00754**Yiyang Zhou, Chenhang Cui, Jaehong Yoon, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-analyzing-mitigating-object-hallucination-large/)
152. **[Improved Natural Language Generation via Loss Truncation](https://md.research.elamur.ai/free/en/papers/kang-2020-improved-natural-language-generation-loss/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Kang, Tatsunori B. Hashimoto*2020 · 130 citations*
153. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 127 citations*
154. [**A Recipe For Arbitrary Text Style Transfer with Large Language Models arXiv:2109.03910**Emily Reif, Daphne Ippolito, Ann Yuan, et al.*2021 · 127 citations*](https://md.research.elamur.ai/free/en/papers/reif-2021-recipe-arbitrary-text-style-transfer/)
155. [**PEER: A Collaborative Language Model arXiv:2208.11663**Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/schick-2022-peer-collaborative-language-model/)
156. [**A Systematic Evaluation of Large Language Models of Code arXiv:2202.13169**Frank F. Xu, Uri Alon, Graham Neubig, et al.*2022 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xu-2022-systematic-evaluation-large-language-models/)
157. **[The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems](https://md.research.elamur.ai/free/en/papers/ziems-2022-moral-integrity-corpus-benchmark-ethical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane A. Yu, Yi-Chia Wang, et al.*2022 · 122 citations*
158. [**Pretraining Language Models with Human Preferences arXiv:2302.08582**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 121 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
159. [**Compositional Exemplars for In-context Learning arXiv:2302.05698**Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/)
160. **[The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning](https://md.research.elamur.ai/free/en/papers/kim-2023-cot-collection-improving-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seungone Kim, Se Joo, Doyoung Kim, et al.*2023 · 118 citations*
161. **[Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech](https://md.research.elamur.ai/free/en/papers/fanton-2021-human-loop-data-collection-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, et al.*2021 · 118 citations*
162. **[A Critical Evaluation of Evaluations for Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/xu-2023-critical-evaluation-evaluations-long-form/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangyuan Xu, Yixiao Song, Mohit Iyyer, et al.*2023 · 117 citations*
163. **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.*2023 · 117 citations*
164. [**Break the Sequential Dependency of LLM Inference Using Lookahead Decoding arXiv:2402.02057**Yichao Fu, Peter Bailis, Ion Stoica, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-break-sequential-dependency-llm-inference/)
165. [**A Survey on Hallucination in Large Vision-Language Models arXiv:2402.00253**Hanchao Liu, Wenyuan Xue, Yifei Chen, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-survey-hallucination-large-vision-language/)
166. **[Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest](https://md.research.elamur.ai/free/en/papers/hessel-2023-do-androids-laugh-electric-sheep/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jack Hessel, Ana Marasovic, Jena D. Hwang, et al.*2023 · 112 citations*
167. [**Reframing Human-AI Collaboration for Generating Free-Text Explanations arXiv:2112.08674**Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta, et al.*2021 · 111 citations*](https://md.research.elamur.ai/free/en/papers/wiegreffe-2021-reframing-human-ai-collaboration-generating/)
168. **[We're Afraid Language Models Aren't Modeling Ambiguity](https://md.research.elamur.ai/free/en/papers/liu-2023-we-re-afraid-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alisa Liu, Zhaofeng Wu, Julian Michael, et al.*2023 · 110 citations*
169. **[Evaluating the Evaluation of Diversity in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/tevet-2021-evaluating-evaluation-diversity-natural-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Guy Tevet, Jonathan Berant*2021 · 106 citations*
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