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Large Language Models (LLMs) have demonstrated strong performance in handling complex tasks requiring both extensive knowledge and reasoning abilities.
Skeleton-to-response: Dialogue generation guided by retrieval memory
Deng Cai, Yan Wang, Wei Bi, Zhaopeng Tu, Xiaojiang Liu, Wai Lam, and Shuming Shi. 2019 · 2019
Earlier work this paper cites.
CommonsenseQA: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
Earlier work this paper cites.
Quantifying attention flow in transformers
Samira Abnar and Willem Zuidema. 2020 · 2020
Earlier work this paper cites.
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, and Jonathan Berant. 2021 · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Earlier work this paper cites.
Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
Earlier work this paper cites.
Can llm-generated misinformation be detected?
Canyu Chen and Kai Shu. 2023 · 2023
Earlier work this paper cites.
Chain-of-symbol prompting elicits planning in large langauge models
Hanxu Hu, Hongyuan Lu, Huajian Zhang, Yun-Ze Song, Wai Lam, and Yue Zhang. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
Earlier work this paper cites.
Survey on factuality in large language models: Knowledge, retrieval and domain-specificity
Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, et al. 2023 · 2023
Earlier work this paper cites.
Linyao Yang, Hongyang Chen, Zhao Li, Xiao Ding, and Xindong Wu. 2023 · 2023
Earlier work this paper cites.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2023 · 2023
Earlier work this paper cites.
Thread of thought unraveling chaotic contexts
Yucheng Zhou, Xiubo Geng, Tao Shen, Chongyang Tao, Guodong Long, Jian-Guang Lou, and Jianbing Shen. 2023 · 2023
Cited alongside, same era.
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Michał Podstawski, Hubert Niewiadomski, Piotr Nyczyk, and Torsten Hoefler. 2024 · 2024
Cited alongside, same era.
Guide for defense (g4d): Dynamic guidance for robust and balanced defense in large language models
He Cao, Weidi Luo, Yu Wang, Zijing Liu, Bing Feng, Yuan Yao, and Yu Li. 2024 · 2024
Cited alongside, same era.
Understanding the interplay between parametric and contextual knowledge for large language models
Sitao Cheng, Liangming Pan, Xunjian Yin, Xinyi Wang, and William Yang Wang. 2024 · 2024
Cited alongside, same era.
Deceptive semantic shortcuts on reasoning chains: How far can models go without hallucination?
Bangzheng Li, Ben Zhou, Fei Wang, Xingyu Fu, Dan Roth, and Muhao Chen. 2024a · 2024
Closest in time.
Understanding and patching compositional reasoning in LLMs
Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, and Ying Wei. 2024b · 2024
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Ryan Liu, Jiayi Geng, Addison J. Wu, Ilia Sucholutsky, Tania Lombrozo, and Thomas L. Griffiths. 2024 · 2024
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OpenAI. 2024 · 2024
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Duy Khoa Pham and Bao Quoc Vo. 2024 · 2024
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Pedro Colon-Hernandez, Nanxi Liu, Chelsea Joe, Peter Chin, Claire Yin, Henry Lieberman, Yida Xin, and Cynthia Breazeal. 2024 · 2024
Cited alongside, same era.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
Cited alongside, same era.
Towards revealing the mystery behind chain of thought: a theoretical perspective
Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, and Liwei Wang. 2024 · 2024
Cited alongside, same era.
Two-stage generative question answering on temporal knowledge graph using large language models
Yifu Gao, Linbo Qiao, Zhigang Kan, Zhihua Wen, Yongquan He, and Dongsheng Li. 2024 · 2024
Cited alongside, same era.
Think before you speak: Training language models with pause tokens
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, and Vaishnavh Nagarajan. 2024 · 2024
Cited alongside, same era.
Token-budget-aware llm reasoning
Tingxu Han, Zhenting Wang, Chunrong Fang, Shiyu Zhao, Shiqing Ma, and Zhenyu Chen. 2024 · 2024
Cited alongside, same era.
The impact of reasoning step length on large language models
Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, and Mengnan Du. 2024 · 2024
Cited alongside, same era.
Same task, more tokens: the impact of input length on the reasoning performance of large language models
Mosh Levy, Alon Jacoby, and Yoav Goldberg. 2024 · 2024
Cited alongside, same era.
Closest in time.
To cot or not to cot? chain-of-thought helps mainly on math and symbolic reasoning
Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, Dongwei Jiang, Manya Wadhwa, Prasann Singhal, Xinyu Zhao, Xi Ye, Kyle Mahowald, and Greg Durrett. 2024 · 2024
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M 2 PT: Multimodal prompt tuning for zero-shot instruction learning
Taowen Wang, Yiyang Liu, James Chenhao Liang, Junhan Zhao, Yiming Cui, Yuning Mao, Shaoliang Nie, Jiahao Liu, Fuli Feng, Zenglin Xu, Cheng Han, Lifu Huang, Qifan Wang, and Dongfang Liu. 2024b · 2024
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Tow: Thoughts of words improve reasoning in large language models
Zhikun Xu, Ming Shen, Jacob Dineen, Zhaonan Li, Xiao Ye, Shijie Lu, Aswin RRV, Chitta Baral, and Ben Zhou. 2024 · 2024
Closest in time.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2024 · 2024
Closest in time.
Distilling system 2 into system 1
Ping Yu, Jing Xu, Jason Weston, and Ilia Kulikov. 2024 · 2024
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Enhancing zero-shot chain-of-thought reasoning in large language models through logic
Xufeng Zhao, Mengdi Li, Wenhao Lu, Cornelius Weber, Jae Hee Lee, Kun Chu, and Stefan Wermter. 2024 · 2024
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Visual agents as fast and slow thinkers
Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Tong Geng, Ying Nian Wu, Yongfeng Zhang, and Dongfang Liu. 2025 · 2025
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