{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T23:53:55Z","timestamp":1781740435130,"version":"3.54.5"},"reference-count":64,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100010418","name":"Institute for Information and Communications Technology Promotion","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["RS-2022-00187238"],"award-info":[{"award-number":["RS-2022-00187238"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.eswa.2026.132351","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T17:23:00Z","timestamp":1776100980000},"page":"132351","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GateLM: Jointly injecting knowledge graphs and texts for reasoning-enhanced language models on commonsense question answering"],"prefix":"10.1016","volume":"323","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-3739-7024","authenticated-orcid":false,"given":"Jinwoo","family":"Min","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8230-0298","authenticated-orcid":false,"given":"Kun-Hui","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8617-1633","authenticated-orcid":false,"given":"Roseline","family":"Nyange","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4372-7125","authenticated-orcid":false,"given":"Seung-Hoon","family":"Na","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.132351_bib0001","unstructured":"Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S. et al. (2023). Gpt-4 technical report. arXiv: 2303.08774."},{"key":"10.1016\/j.eswa.2026.132351_bib0002","series-title":"Proceedings of the 2025 conference on empirical methods in natural language processing","first-page":"24296","article-title":"Sketch-of-thought: Efficient LLM reasoning with adaptive cognitive-inspired sketching","author":"Aytes","year":"2025"},{"key":"10.1016\/j.eswa.2026.132351_bib0003","series-title":"Proceedings of the 13th international joint conference on natural language processing and the 3rd conference of the Asia-Pacific chapter of the association for computational linguistics (volume 1: Long papers)","first-page":"675","article-title":"A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity","author":"Bang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0004","series-title":"Proceedings of the 2008\u202fACM SIGMOD international conference on management of data","first-page":"1247","article-title":"Freebase: a collaboratively created graph database for structuring human knowledge","author":"Bollacker","year":"2008"},{"key":"10.1016\/j.eswa.2026.132351_bib0005","series-title":"International conference on learning representations","article-title":"How attentive are graph attention networks?","author":"Brody","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0006","series-title":"Advances in neural information processing systems","first-page":"1877","article-title":"Language models are few-shot learners","volume":"vol. 33","author":"Brown","year":"2020"},{"issue":"4","key":"10.1016\/j.eswa.2026.132351_bib0007","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1609\/aimag.v41i4.5304","article-title":"From \u2018f\u2019 to \u2018a\u2019 on the NY regents science exams: An overview of the aristo project","volume":"41","author":"Clark","year":"2020","journal-title":"Ai Magazine"},{"key":"10.1016\/j.eswa.2026.132351_bib0008","series-title":"Proceedings of the 2019 conference of the north American chapter of the association for computational linguistics: Human language technologies, volume 1 (long and short papers)","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2019"},{"key":"10.1016\/j.eswa.2026.132351_bib0009","series-title":"Advances in neural information processing systems","first-page":"115261","article-title":"Cost-efficient knowledge-based question answering with large language models","volume":"vol. 37","author":"Dong","year":"2024"},{"key":"10.1016\/j.eswa.2026.132351_bib0010","series-title":"The thirteenth international conference on learning representations","article-title":"Alphaedit: Null-space constrained model editing for language models","author":"Fang","year":"2025"},{"key":"10.1016\/j.eswa.2026.132351_bib0011","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP)","first-page":"4937","article-title":"Entities as experts: Sparse memory access with entity supervision","author":"F\u00e9vry","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0012","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1162\/tacl_a_00615","article-title":"Hallucinations in large multilingual translation models","volume":"11","author":"Guerreiro","year":"2023","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.eswa.2026.132351_bib0013","series-title":"Proceedings of the 37th international conference on machine learning","first-page":"3929","article-title":"Retrieval augmented language model pre-training","volume":"Vol. 119","author":"Guu","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0014","series-title":"Proceedings of the 2022 conference on empirical methods in natural language processing","first-page":"8461","article-title":"ACENet: Attention guided commonsense reasoning on hybrid knowledge graph","author":"Hao","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0015","series-title":"Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: Long papers)","first-page":"13417","article-title":"MVP-tuning: Multi-view knowledge retrieval with prompt tuning for commonsense reasoning","author":"Huang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0016","series-title":"Proceedings of the 2023 conference on empirical methods in natural language processing","first-page":"9237","article-title":"StructGPT: A general framework for large language model to reason over structured data","author":"Jiang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0017","series-title":"Proceedings of the 2024 conference of the North American chapter of the association for computational linguistics: Human language technologies (volume 1: Long papers)","first-page":"1434","article-title":"OrchestraLLM: Efficient orchestration of language models for dialogue state tracking","author":"Lee","year":"2024"},{"key":"10.1016\/j.eswa.2026.132351_bib0018","series-title":"Advances in neural information processing systems","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive NLP tasks","volume":"vol. 33","author":"Lewis","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0019","series-title":"Findings of the association for computational linguistics: ACL 2022","first-page":"1720","article-title":"How pre-trained language models capture factual knowledge? a causal-inspired analysis","author":"Li","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0020","series-title":"Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","first-page":"2829","article-title":"KagNet: Knowledge-aware graph networks for commonsense reasoning","author":"Lin","year":"2019"},{"key":"10.1016\/j.eswa.2026.132351_bib0021","series-title":"Proceedings of the 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024)","first-page":"9961","article-title":"KPatch: Knowledge patch to pre-trained language model for zero-shot stance detection on social media","author":"Lin","year":"2024"},{"issue":"03","key":"10.1016\/j.eswa.2026.132351_bib0022","doi-asserted-by":"crossref","first-page":"2901","DOI":"10.1609\/aaai.v34i03.5681","article-title":"K-BERT: Enabling language representation with knowledge graph","volume":"34","author":"Liu","year":"2020","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.1016\/j.eswa.2026.132351_bib0023","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.neucom.2023.03.002","article-title":"Commonsense knowledge graph-based adapter for aspect-level sentiment classification","volume":"534","author":"Lu","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2026.132351_bib0024","series-title":"Findings of the association for computational linguistics: EMNLP 2023","first-page":"3999","article-title":"KAPALM: Knowledge grAPh enhAnced language models for fake news detection","author":"Ma","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0025","series-title":"Advances in neural information processing systems","first-page":"17359","article-title":"Locating and editing factual associations in GPT","volume":"Vol. 35","author":"Meng","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0026","series-title":"The eleventh international conference on learning representations","article-title":"Mass-editing memory in a transformer","author":"Meng","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0027","series-title":"Proceedings of the 2018 conference on empirical methods in natural language processing","first-page":"2381","article-title":"Can a suit of armor conduct electricity? a new dataset for open book question answering","author":"Mihaylov","year":"2018"},{"key":"10.1016\/j.eswa.2026.132351_bib0028","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"13457","article-title":"Relation-aware language-graph transformer for question answering","volume":"vol. 37","author":"Park","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0029","series-title":"Proceedings of the 2018 conference of the North American chapter of the association for computational linguistics: Human language technologies, volume 1 (long papers)","first-page":"2227","article-title":"Deep contextualized word representations","author":"Peters","year":"2018"},{"key":"10.1016\/j.eswa.2026.132351_bib0030","series-title":"Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","first-page":"43","article-title":"Knowledge enhanced contextual word representations","author":"Peters","year":"2019"},{"key":"10.1016\/j.eswa.2026.132351_bib0031","series-title":"Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","first-page":"2463","article-title":"Language models as knowledge bases?","author":"Petroni","year":"2019"},{"key":"10.1016\/j.eswa.2026.132351_bib0032","series-title":"Improving language understanding by generative pre-training","author":"Radford","year":"2018"},{"issue":"8","key":"10.1016\/j.eswa.2026.132351_bib0033","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"10.1016\/j.eswa.2026.132351_bib0034","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP)","first-page":"5418","article-title":"How much knowledge can you pack into the parameters of a language model?","author":"Roberts","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0035","unstructured":"Shao, C., Liu, X., Lin, Y., Xu, F., & Li, Y. (2025). Route-and-reason: Scaling large language model reasoning with reinforced model router. arXiv: 2506.05901."},{"issue":"1","key":"10.1016\/j.eswa.2026.132351_bib0036","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.11164","article-title":"Conceptnet 5.5: An open multilingual graph of general knowledge","volume":"31","author":"Speer","year":"2017","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.1016\/j.eswa.2026.132351_bib0037","series-title":"Proceedings of the 2022 conference of the North American chapter of the association for computational linguistics: Human language technologies","first-page":"5049","article-title":"JointLK: Joint reasoning with language models and knowledge graphs for commonsense question answering","author":"Sun","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0038","series-title":"Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: Human language technologies, volume 1 (long and short papers)","first-page":"4149","article-title":"CommonsenseQA: A question answering challenge targeting commonsense knowledge","author":"Talmor","year":"2019"},{"key":"10.1016\/j.eswa.2026.132351_bib0039","unstructured":"Tan, X., Wang, H., Qiu, X., Cheng, Y., Xu, Y., Chu, W., & Qi, Y. (2024). Struct-x: Enhancing large language models reasoning with structured data. arXiv: 2407.12522."},{"key":"10.1016\/j.eswa.2026.132351_bib0040","unstructured":"Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozi\u00e8re, B., Goyal, N., Hambro, E., Azhar, F. et al. (2023a). Llama: Open and efficient foundation language models. arXiv: 2302.13971."},{"key":"10.1016\/j.eswa.2026.132351_bib0041","unstructured":"Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S. et al. (2023b). Llama 2: Open foundation and fine-tuned chat models.arXiv: 2307.09288."},{"key":"10.1016\/j.eswa.2026.132351_bib0042","series-title":"Proceedings of the 63rd annual meeting of the association for computational linguistics (volume 1: Long papers)","first-page":"18305","article-title":"RARE: Retrieval-augmented reasoning enhancement for large language models","author":"Tran","year":"2025"},{"key":"10.1016\/j.eswa.2026.132351_bib0043","series-title":"International conference on learning representations","article-title":"Graph attention networks","author":"Velivckovi\u0107","year":"2018"},{"issue":"10","key":"10.1016\/j.eswa.2026.132351_bib0044","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1145\/2629489","article-title":"Wikidata: A free collaborative knowledgebase","volume":"57","author":"Vrande\u010di\u0107","year":"2014","journal-title":"Communications of the ACM"},{"key":"10.1016\/j.eswa.2026.132351_bib0045","unstructured":"Wang, C., Liu, X., & Song, D. (2021a). Language models are open knowledge graphs. https:\/\/openreview.net\/forum?id=aRTRjVPkm-."},{"key":"10.1016\/j.eswa.2026.132351_bib0046","series-title":"International conference on learning representations","article-title":"GNN is a counter? Revisiting GNN for question answering","author":"Wang","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0047","unstructured":"Wang, S., Zhu, Y., Liu, H., Zheng, Z., Chen, C., & Li, J. (2023a). Knowledge editing for large language models: A survey. https:\/\/arxiv.org\/abs\/2310.16218."},{"key":"10.1016\/j.eswa.2026.132351_bib0048","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1162\/tacl_a_00360","article-title":"KEPLER: A unified model for knowledge embedding and pre-trained language representation","volume":"9","author":"Wang","year":"2021","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.eswa.2026.132351_bib0049","series-title":"Proceedings of the 2025 conference of the nations of the Americas chapter of the association for computational linguistics: Human language technologies (volume 1: Long papers)","first-page":"10912","article-title":"MixLLM: Dynamic routing in mixed large language models","author":"Wang","year":"2025"},{"key":"10.1016\/j.eswa.2026.132351_bib0050","series-title":"Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: Long papers)","first-page":"14048","article-title":"Dynamic heterogeneous-graph reasoning with language models and knowledge representation learning for commonsense question answering","author":"Wang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0051","series-title":"Advances in neural information processing systems","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume":"vol. 35","author":"Wei","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0052","series-title":"Findings of the association for computational linguistics: EMNLP 2024","first-page":"1103","article-title":"Guided knowledge generation with language models for commonsense reasoning","author":"Wei","year":"2024"},{"key":"10.1016\/j.eswa.2026.132351_bib0053","unstructured":"Wikipedia (2025). Wikipedia. https:\/\/www.wikipedia.org\/. Accessed September 5, 2025."},{"key":"10.1016\/j.eswa.2026.132351_bib0054","unstructured":"Wiktionary (2025). Wiktionary. https:\/\/www.wiktionary.org\/. Accessed September 5, 2025."},{"key":"10.1016\/j.eswa.2026.132351_bib0055","series-title":"International conference on learning representations","article-title":"Pretrained encyclopedia: Weakly supervised knowledge-pretrained language model","author":"Xiong","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0056","series-title":"Findings of the association for computational linguistics: ACL-IJCNLP 2021","first-page":"1201","article-title":"Fusing context into knowledge graph for commonsense question answering","author":"Xu","year":"2021"},{"key":"10.1016\/j.eswa.2026.132351_bib0057","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP)","first-page":"6442","article-title":"LUKE: Deep contextualized entity representations with entity-aware self-attention","author":"Yamada","year":"2020"},{"key":"10.1016\/j.eswa.2026.132351_bib0058","series-title":"Advances in neural information processing systems","first-page":"11809","article-title":"Tree of thoughts: Deliberate problem solving with large language models","volume":"Vol. 36","author":"Yao","year":"2023"},{"key":"10.1016\/j.eswa.2026.132351_bib0059","series-title":"Proceedings of the 2021 conference of the north american chapter of the association for computational linguistics: Human language technologies","first-page":"535","article-title":"QA-GNN: Reasoning with language models and knowledge graphs for question answering","author":"Yasunaga","year":"2021"},{"issue":"11","key":"10.1016\/j.eswa.2026.132351_bib0060","doi-asserted-by":"crossref","first-page":"13914","DOI":"10.1609\/aaai.v37i11.26629","article-title":"Fits: Fine-grained two-stage training for knowledge-aware question answering","volume":"37","author":"Ye","year":"2023","journal-title":"Proceedings of the AAAI conference on artificial intelligence"},{"key":"10.1016\/j.eswa.2026.132351_bib0061","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"11630","article-title":"Jaket: Joint pre-training of knowledge graph and language understanding","volume":"Vol. 36","author":"Yu","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0062","series-title":"Findings of the association for computational linguistics: ACL 2022","first-page":"1907","article-title":"Dict-BERT: Enhancing language model pre-training with dictionary","author":"Yu","year":"2022"},{"key":"10.1016\/j.eswa.2026.132351_bib0063","series-title":"International conference on learning representations","article-title":"Greaselm: Graph reasoning enhanced language models","author":"Zhang","year":"2021"},{"key":"10.1016\/j.eswa.2026.132351_bib0064","series-title":"Proceedings of the 57th annual meeting of the association for computational linguistics","first-page":"1441","article-title":"ERNIE: Enhanced language representation with informative entities","author":"Zhang","year":"2019"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012649?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012649?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T23:23:35Z","timestamp":1781738615000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426012649"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":64,"alternative-id":["S0957417426012649"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132351","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GateLM: Jointly injecting knowledge graphs and texts for reasoning-enhanced language models on commonsense question answering","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132351","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"132351"}}