Fetching the paper…
Reading the bibliography…
We evaluate the ability of large language models (LLMs) to infer causal relations from natural language.
Semeval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals
Hendrickx, I.; Kim, S. N.; Kozareva, Z.; Nakov, P.; Séaghdha, D. O.; Padó, S.; Pennacchiotti, M.; Romano, L.; and Szpakowicz, S. 2019 · 1911
Earlier work this paper cites.
Causation, prediction, and search
Spirtes, P.; Glymour, C. N.; and Scheines, R. 2000 · 2000
Earlier work this paper cites.
Optimal structure identification with greedy search
Chickering, D. M. 2002 · 2002
Earlier work this paper cites.
Causality
Pearl, J. 2009 · 2009
Earlier work this paper cites.
Reasoning with causal cycles
Rehder, B. 2017 · 2017
Earlier work this paper cites.
Deep learning in medical image analysis
Shen, D.; Wu, G.; and Suk, H.-I. 2017 · 2017
Earlier work this paper cites.
Comparative study of CNN and RNN for natural language processing
Yin, W.; Kann, K.; Yu, M.; and Schütze, H. 2017 · 2017
Cited alongside, same era.
Fulminant type 1 diabetes: a comprehensive review of an autoimmune condition
Luo, S.; Ma, X.; Li, X.; Xie, Z.; and Zhou, Z. 2020 · 2020
Cited alongside, same era.
A survey on knowledge graphs: Representation, acquisition, and applications
Ji, S.; Pan, S.; Cambria, E.; Marttinen, P.; and Philip, S. Y. 2021 · 2021
Cited alongside, same era.
Prompt programming for large language models: Beyond the few-shot paradigm
Reynolds, L.; and McDonell, K. 2021 · 2021
Cited alongside, same era.
On Pearl’s hierarchy and the foundations of causal inference
Bareinboim, E.; Correa, J. D.; Ibeling, D.; and Icard, T. 2022 · 2022
Cited alongside, same era.
Large Language Models for Biomedical Causal Graph Construction
Arsenyan, V.; and Shahnazaryan, D. 2023 · 2023
Closest in time.
Can Large Language Models Infer Causation from Correlation?
Jin, Z.; Liu, J.; Lyu, Z.; Poff, S.; Sachan, M.; Mihalcea, R.; Diab, M.; and Schölkopf, B. 2023 · 2023
Closest in time.
Large language models and knowledge graphs: Opportunities and challenges
Pan, J. Z.; Razniewski, S.; Kalo, J.-C.; Singhania, S.; Chen, J.; Dietze, S.; Jabeen, H.; Omeliyanenko, J.; Zhang, W.; Lissandrini, M.; et al. 2023 · 2023
Closest in time.
Towards expert-level medical question answering with large language models
Singhal, K.; Tu, T.; Gottweis, J.; Sayres, R.; Wulczyn, E.; Hou, L.; Clark, K.; Pfohl, S.; Cole-Lewis, H.; Neal, D.; et al. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Li, Q.; Peng, H.; Li, J.; Xia, C.; Yang, R.; Sun, L.; Yu, P. S.; and He, L. 2022 · 2022
Cited alongside, same era.
Approximating counterfactual bounds while fusing observational, biased and randomised data sources
Zaffalon, M.; Antonucci, A.; Cabañas, R.; and Huber, D. 2023 · 2023
Closest in time.
Understanding causality with large language models: Feasibility and opportunities
Zhang, C.; Bauer, S.; Bennett, P.; Gao, J.; Gong, W.; Hilmkil, A.; Jennings, J.; Ma, C.; Minka, T.; Pawlowski, N.; et al. 2023 · 2023
Closest in time.