---
title: "Who cites CommonsenseQA: — page 2 — 1,148 citing papers"
description: "1,148 papers of the Elamur Research library cite «CommonsenseQA: A Question Answering Challenge Targeting Commonsense…"
canonical: "https://research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CommonsenseQA: A Question Answering Challenge…](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/) / [cited by](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/) / page 2

# Who cites «CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge»

1,148 papers of our library cite it (of the 141,840 whose bibliographies we read) · 141 with a page here, the most cited first · page 2 of 2 · 101–141 · [← back to «CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge»](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/)

[← prev](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/) **2**

101. **[Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/lin-2021-common-sense-beyond-english-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bill Yuchen Lin, Seyeon Lee, Xiaoyang Qiao, et al.*2021 · 106 citations*
102. **[TokenSkip: Controllable Chain-of-Thought Compression in LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-tokenskip-controllable-chain-thought-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Heming Xia, Chak Tou Leong, Wenjie Wang, et al.*2025 · 105 citations*
103. **[ChatGPT Is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models](https://md.research.elamur.ai/free/en/papers/bian-2024-chatgpt-is-knowledgeable-but-inexperienced/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ning Bian, Xianpei Han, Le Sun, et al.*2024 · 105 citations*
104. **[Boosting Language Models Reasoning with Chain-of-Knowledge Prompting](https://md.research.elamur.ai/free/en/papers/wang-2024-boosting-language-models-reasoning-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianing Wang, Qiushi Sun, Xiang Li, et al.*2024 · 94 citations*
105. **[Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate](https://md.research.elamur.ai/free/en/papers/xiong-2023-examining-inter-consistency-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Xiong, Xiao Ding, Yixin Cao, et al.*2023 · 94 citations*
106. **[LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models](https://md.research.elamur.ai/free/en/papers/parmar-2024-logicbench-systematic-evaluation-logical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.*2024 · 92 citations*
107. **[JGLUE: Japanese General Language Understanding Evaluation](https://md.research.elamur.ai/free/en/papers/kurihara-2022-jglue-japanese-general-language-understanding/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata*2022 · 90 citations*
108. **[“My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-my-answer-is-c-first/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinpeng Wang, Bolei Ma, Chengzhi Hu, et al.*2024 · 89 citations*
109. [**Small Language Models: Survey, Measurements, and Insights arXiv:2409.15790**Zhenyan Lu, Xiang Li, Dongqi Cai, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-small-language-models-survey-measurements/)
110. **[Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI](https://md.research.elamur.ai/free/en/papers/tian-2021-diagnosing-first-order-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jidong Tian, Yitian Li, Wenqing Chen, et al.*2021 · 86 citations*
111. **[Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering](https://md.research.elamur.ai/free/en/papers/liu-2022-rainier-reinforced-knowledge-introspector-commonsense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiacheng Liu, Skyler Hallinan, Ximing Lu, et al.*2022 · 82 citations*
112. **[CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation](https://md.research.elamur.ai/free/en/papers/shen-2025-codi-compressing-chain-thought-into/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyi Shen, Hanqi Yan, Linhai Zhang, et al.*2025 · 76 citations*
113. [**AlignBench: Benchmarking Chinese Alignment of Large Language Models arXiv:2311.18743**Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.*2023 · 73 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-alignbench-benchmarking-chinese-alignment/)
114. **[Aligning Large and Small Language Models via Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-aligning-large-small-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Andre Freitas*2024 · 70 citations*
115. **[English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too](https://md.research.elamur.ai/free/en/papers/phang-2020-english-intermediate-task-training-improves/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Jason Phang, Iacer Calixto, Phu Mon Htut, et al.*2020 · 70 citations*
116. **[ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness](https://md.research.elamur.ai/free/en/papers/prasad-2023-receval-evaluating-reasoning-chains-correctness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Archiki Prasad, Swarnadeep Saha, Xiang Zhou, et al.*2023 · 68 citations*
117. [**Contrastive Decoding Improves Reasoning in Large Language Models arXiv:2309.09117**Sean O'Brien, Mike Lewis*2023 · 67 citations*](https://md.research.elamur.ai/free/en/papers/o-brien-2023-contrastive-decoding-improves-reasoning-large/)
118. **[FORK: A Bite-Sized Test Set for Probing Culinary Cultural Biases in Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/palta-2023-fork-bite-sized-test-set/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shramay Palta, Rachel Rudinger*2023 · 67 citations*
119. **[Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models](https://md.research.elamur.ai/free/en/papers/amayuelas-2024-knowledge-knowledge-exploring-known-unknowns/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alfonso Amayuelas, Kyle Wong, Liangming Pan, et al.*2024 · 66 citations*
120. **[NormBank: A Knowledge Bank of Situational Social Norms](https://md.research.elamur.ai/free/en/papers/ziems-2023-normbank-knowledge-bank-situational-social/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, et al.*2023 · 66 citations*
121. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
122. **[Automatic Story Generation: Challenges and Attempts](https://md.research.elamur.ai/free/en/papers/alabdulkarim-2021-automatic-story-generation-challenges-attempts/) [Workshop on Narrative Understanding](https://md.research.elamur.ai/free/en/venues/nuse/)**Amal Alabdulkarim, Siyan Li, Xiangyu Peng*2021 · 61 citations*
123. [**Shepherd: A Critic for Language Model Generation arXiv:2308.04592**Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-shepherd-critic-language-model-generation/)
124. [**English Machine Reading Comprehension Datasets: A Survey**Daria Dzendzik, Jennifer Foster, Carl Vogel*2021 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dzendzik-2021-english-machine-reading-comprehension-datasets/)
125. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws arXiv:2401.00448**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/)
126. [**Transcending Scaling Laws with 0.1% Extra Compute arXiv:2210.11399**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 41 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
127. [**GRICE: A Grammar-based Dataset for Recovering Implicature and Conversational rEasoning**Zilong Zheng, Shuwen Qiu, Lifeng Fan, et al.*2021 · 36 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-grice-grammar-based-dataset-recovering/)
128. **[Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2022-distributed-nli-learning-predict-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiang Zhou, Yixin Nie, Mohit Bansal*2022 · 35 citations*
129. **[KACE: Generating Knowledge Aware Contrastive Explanations for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/chen-2021-kace-generating-knowledge-aware-contrastive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianglong Chen, Feng Ji, Xiangji Zeng, et al.*2021 · 28 citations*
130. **[Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 26 citations*
131. **[Integrating Transformers and Knowledge Graphs for Twitter Stance Detection](https://md.research.elamur.ai/free/en/papers/clark-2021-integrating-transformers-knowledge-graphs-twitter/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Thomas Clark, Costanza Conforti, Fangyu Liu, et al.*2021 · 14 citations*
132. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
133. [**Is this sentence valid? An Arabic Dataset for Commonsense Validation arXiv:2008.10873**Saja Tawalbeh, Mohammad AL-Smadi*2020 · 4 citations*](https://md.research.elamur.ai/free/en/papers/tawalbeh-2020-this-sentence-valid-arabic-dataset/)
134. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/)
135. **[QA-KGNet: Language Model-driven Knowledge Graph Question-answering Model (QA-KGNet: 一种语言模型驱动的知识图谱问答模型)](https://md.research.elamur.ai/free/en/papers/qiao-2023-qa-kgnet-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Shaojie Qiao (乔少杰), Guoping Yang (杨国平), Yong Yu (于泳), et al.*2023 · 1 citation*
136. **[DRInQ: Evaluating Conversational Implicature with Controlled Context Variation](https://md.research.elamur.ai/free/en/papers/arai-2026-drinq-evaluating-conversational-implicature-controlled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hirona Jacqueline Arai, Xiang Ren*2026*
137. **[EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
138. **[mSCoRe: A Multilingual and Scalable Benchmark for Skill-based Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/ngo-2026-mscore-multilingual-scalable-benchmark-skill/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen*2026*
139. [**MuDRiC: Multi-Dialect Reasoning for Arabic Commonsense Validation arXiv:2508.13130**Kareem Elozeiri, Mervat Abassy, Preslav Nakov, et al.*2025*](https://md.research.elamur.ai/free/en/papers/elozeiri-2025-mudric-multi-dialect-reasoning-arabic/)
140. **[Reverse Probing: Evaluating Knowledge Transfer via Finetuned Task Embeddings for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/anikina-2025-reverse-probing-evaluating-knowledge-transfer/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Tatiana Anikina, Arne Binder, David Harbecke, et al.*2025*
141. **[Survey on Commonsense Question Answering (常识问答研究综述)](https://md.research.elamur.ai/free/en/papers/fan-2023-commonsense-question-answering/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yifan Fan (范怡帆), Bowei Zou (邹博伟), Qingting Xu (徐庆婷), et al.*2023*

[← prev](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/cited-by/) **2**

1,007 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/) — CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge