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Theory-of-Mind (ToM) ability possessed by Large Language Models (LLMs) has been shown to be limited.
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Deutsch, D., Upadhyay, S., Roth, D.: A general-purpose algorithm for constrained sequential inference. In: Bansal, M., Villavicencio, A. (eds.) CoNLL. pp. 482–492. ACL (2019)
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Reimers, N., Gurevych, I.: Sentence-BERT: Sentence embeddings using Siamese BERT-networks. In: EMNLP-IJCNLP. pp. 3982–3992. ACL (2019)
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Lin, Z., Ke, H., Wong, N., Bai, J., Song, Y., Zhao, H., Ye, J.: Multi-relational graph based heterogeneous multi-task learning in community question answering. In: CIKM. pp. 1038–1047 (2021)
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Bara, C.P., Ma, Z., Yu, Y., Shah, J., Chai, J.: Towards collaborative plan acquisition through theory of mind modeling in situated dialogue. In: IJCAI. pp. 2958–2966. IJCAI Organization (2023)
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Ma, Z., Sansom, J., Peng, R., Chai, J.: Towards A holistic landscape of situated theory of mind in large language models. In: Findings EMNLP. pp. 1011–1031. ACL (2023)
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Sclar, M., Kumar, S., West, P., Suhr, A., Choi, Y., Tsvetkov, Y.: Minding language models’ (lack of) theory of mind: A plug-and-play multi-character belief tracker. In: ACL. pp. 13960–13980. ACL (2023)
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Faghihi, H.R., Nafar, A., Zheng, C., Mirzaee, R., Zhang, Y., Uszok, A., Wan, A., Premsri, T., Roth, D., Kordjamshidi, P.: Gluecons: A generic benchmark for learning under constraints. In: AAAI. pp. 9552–9561. AAAI Press (2023)
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Favier, A., Shekhar, S., Alami, R.: Models and algorithms for human-aware task planning with integrated theory of mind. In: RO-MAN. pp. 1279–1286. IEEE (2023)
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Gandhi, K., Fränken, J., Gerstenberg, T., Goodman, N.D.: Understanding social reasoning in language models with language models. In: NeurIPS (2023)
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