Fetching the paper…
Reading the bibliography…
With the rapid advancement of large language models (LLMs) for handling complex language tasks, an increasing number of studies are employing LLMs as agents to emulate the sequential decision-making processes of humans often represented as Markov decision-making processes (MDPs).
The kolmogorov-smirnov test for goodness of fit
Frank J. Massey Jr. 1951 · 1951
Earlier work this paper cites.
Emotion model of interactive virtual humans on the basis of mdp
Wang Guojiang, Wang Zhiliang, Teng Shaodong, Xie Yinggang, and Wang Yujie. 2007 · 2007
Earlier work this paper cites.
Empirical analysis of individual popularity and activity on an online music service system
Hai-Bo Hu and Ding-Yi Han. 2008 · 2008
Earlier work this paper cites.
Patterns and dynamics of users’ behavior and interaction: Network analysis of an online community
Pietro Panzarasa, Tore Opsahl, and Kathleen M. Carley. 2009 · 2009
Earlier work this paper cites.
Implant: An integrated mdp and pomdp learning agent for adaptive games
Chek Tien Tan and Ho-Lun Cheng. 2009 · 2009
Earlier work this paper cites.
Reasoning about mdps as transformers of probability distributions
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul Agha, and YoungMin Kwon. 2010 · 2010
Earlier work this paper cites.
Heterogenous scaling in the inter-event time of on-line bookmarking
Peng Wang, Xiao-Yi Xie, Chi Ho Yeung, and Bing-Hong Wang. 2011 · 2011
Earlier work this paper cites.
Scalable, mdp-based planning for multiple, cooperating agents
J. D. Redding, Kemal N Ure, J. P. How, M. A. Vavrina, and J. Vian. 2012 · 2012
Earlier work this paper cites.
Human dynamic model co-driven by interest and social identity in the microblog community
Qiang Yan, Lanli Yi, and Lianren Wu. 2012 · 2012
Earlier work this paper cites.
The possibility of social media analysis for disaster management
Takeshi Sakaki, Yutaka Matsuo, Satoshi Kurihara, Fujio Toriumi, Kosuke Shinoda, Itsuki Noda, Koki Uchiyama, and Kazuhiro Kazama. 2013 · 2013
Earlier work this paper cites.
Learning probability distributions over partially-ordered human everyday activities
Moritz Tenorth, Fernando De la Torre, and Michael Beetz. 2013 · 2013
Earlier work this paper cites.
A practical overview on probability distributions
Andrea Viti, Alberto Terzi, and Luca Bertolaccini. 2015 · 2015
Earlier work this paper cites.
Mouselab-mdp: A new paradigm for tracing how people plan
Frederick Callaway, Falk Lieder, Paul M Krueger, and Thomas L Griffiths. 2017 · 2017
Earlier work this paper cites.
Fundamental patterns of in-store shopper behavior
Herb Sorensen, Svetlana Bogomolova, Katherine Anderson, Giang Trinh, Anne Sharp, Rachel Kennedy, Bill Page, and Malcolm Wright. 2017 · 2017
Earlier work this paper cites.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, and Heewoo Jun et.al. 2021 · 2021
Cited alongside, same era.
Glm: General language model pretraining with autoregressive blank infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. 2021 · 2021
Cited alongside, same era.
Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, and Sandipan Kundu et.al. 2022 · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Ai-augmented surveys: Leveraging large language models and surveys for opinion prediction
Junsol Kim and Byungkyu Lee. 2023 · 2023
Later among the works it cites.
Siyu Li, Jin Yang, and Kui Zhao. 2023 · 2023
Later among the works it cites.
Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, and Yuta Koreeda. 2023 · 2023
Later among the works it cites.
Toolformer: Language models can teach themselves to use tools
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez, and Robert Stojnic. 2022 · 2022
Cited alongside, same era.
Wordcraft: Story writing with large language models
Ann Yuan, Andy Coenen, Emily Reif, and Daphne Ippolito. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Cited alongside, same era.
Using large language models to simulate multiple humans and replicate human subject studies
Gati V Aher, Rosa I. Arriaga, and Adam Tauman Kalai. 2023 · 2023
Cited alongside, same era.
Using GPT for market research
James Brand, Ayelet Israeli, and Donald Ngwe. 2023 · 2023
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
Cited alongside, same era.
Ernie bot
ERNIE Bot. 2023 · 2023
Cited alongside, same era.
S3: Social-network simulation system with large language model-empowered agents
Chen Gao, Xiaochong Lan, Zhihong Lu, Jinzhu Mao, Jinghua Piao, Huandong Wang, Depeng Jin, and Yong Li. 2023 · 2023
Cited alongside, same era.
Timo Schick, Jane Dwivedi-Yu, Roberto Dessi, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023
Later among the works it cites.
Reflexion: language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
Later among the works it cites.
Gemini: A family of highly capable multimodal models
Gemini Team, Rohan Anil, and Sebastian Borgeaud et.al. 2023 · 2023
Later among the works it cites.
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, et al. 2023 · 2023
Later among the works it cites.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023 · 2023
Later among the works it cites.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen. 2023 · 2023
Later among the works it cites.
Exploring Human-Like Translation Strategy with Large Language Models
Zhiwei He, Tian Liang, Wenxiang Jiao, Zhuosheng Zhang, Yujiu Yang, Rui Wang, Zhaopeng Tu, Shuming Shi, and Xing Wang. 2024 · 2024
Closest in time.
Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
Closest in time.
Do llm agents exhibit social behavior?
Yan Leng and Yuan Yuan. 2024 · 2024
Closest in time.
What are the odds? language models are capable of probabilistic reasoning
Akshay Paruchuri, Jake Garrison, Shun Liao, John Hernandez, Jacob E. Sunshine, Tim Althoff, Xin Liu, and Daniel McDuff. 2024 · 2024
Closest in time.