{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:18:29Z","timestamp":1761175109613,"version":"build-2065373602"},"reference-count":10,"publisher":"Polish Information Processing Society","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.15439\/2025f3227","type":"proceedings-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T07:44:23Z","timestamp":1761119063000},"page":"813-818","source":"Crossref","is-referenced-by-count":1,"title":["Multi-Modal Deep Learning with Residual and Structure-Guided Refinement for Chess Puzzle Difficulty Prediction"],"prefix":"10.15439","volume":"43","author":[{"given":"Junlin","family":"Chen","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong, Shenzhen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cenru","family":"Liu","sequence":"additional","affiliation":[{"name":"Ngee Ann Poly"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Gao","sequence":"additional","affiliation":[{"name":"Melbourne Business School, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"6175","published-online":{"date-parts":[[2025,10,15]]},"reference":[{"key":"ref1","unstructured":"Lichess.org, \u201cPuzzle Rating System,\u201d Available: https:\/\/lichess.org\/training\/about, accessed Jan. 2025."},{"key":"ref2","doi-asserted-by":"publisher","unstructured":"J. Zy\u015bko, M. \u015al\u0119zak, D. \u015al\u0119zak, and M. \u015awiechowski, \u201cFedCSIS 2025\nknowledgepit.ai Competition: Predicting Chess Puzzle Difficulty Part 2\n& A Step Toward Uncertainty Contests,\u201d in Proc. 20th Conf. Comput.\nSci. Intell. Syst. (FedCSIS), vol. 43, Polish Inf. Process. Soc., 2025. \nhttp:\/\/dx.doi.org\/10.15439\/2025F5937.","DOI":"10.15439\/2025F5937"},{"key":"ref3","doi-asserted-by":"publisher","unstructured":"J. Zy\u015bko, M. \u015awiechowski, S. Stawicki, K. Jagie\u0142a, A. Janusz and D.\n\u015al\u02db ezak, \"IEEE Big Data Cup 2024 Report: Predicting Chess Puzzle\nDifficulty at KnowledgePit.ai,\" 2024 IEEE International Conference on\nBig Data (BigData), Washington, DC, USA, 2024, pp. 8423-8429, https:\/\/dx.doi.org\/10.1109\/BigData62323.2024.10825289.","DOI":"10.1109\/BigData62323.2024.10825289"},{"key":"ref4","doi-asserted-by":"publisher","unstructured":"D. Ruta, M. Liu and L. Cen, \"Moves Based Prediction of Chess\nPuzzle Difficulty with Convolutional Neural Networks,\" 2024 IEEE\nInternational Conference on Big Data (BigData), Washington, DC, USA,\n2024, pp. 8390-8395, https:\/\/dx.doi.org\/10.1109\/BigData62323.2024.10825595.","DOI":"10.1109\/BigData62323.2024.10825595"},{"key":"ref5","unstructured":"S. Mi\u0142osz and P. Kapusta, \u201cTransformer-based Modeling of Chess Puzzle\nDifficulty from Sequential Data,\u201d arXiv preprint https:\/\/arxiv.org\/abs\/2403.01234,\n2024."},{"key":"ref6","unstructured":"M. Omori and P. Tadepalli, \u201cJoint Puzzle and Player Rating Estimation\nwith CNN-LSTM Models,\u201d in Proc. IEEE BigData Cup, 2024."},{"key":"ref7","unstructured":"T. Woodruff, O. Filatov, and M. Cognetta, \u201cBread Emoji Team: Hybrid\nPrediction of Chess Puzzle Difficulty Using Maia\/Leela and Tree-Based\nRegressors,\u201d in Proc. IEEE BigData Cup, 2024."},{"key":"ref8","unstructured":"A. Sch\u00fctt, T. Huber, and E. Andr\u00e9, \u201cHuman Problem-Solving Inspired\nNeural Networks for Chess Puzzle Difficulty Prediction,\u201d in Proc. IEEE\nBigData Cup, 2024."},{"key":"ref9","unstructured":"M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen, \u201cMobileNetV2: Inverted Residuals and Linear Bottlenecks,\u201d arXiv preprint\nhttps:\/\/arxiv.org\/abs\/1801.04381, 2019. [Online]. Available: https:\/\/arxiv.org\/abs\/1801.04381"},{"key":"ref10","unstructured":"G. Ke et al., \u201cLightGBM: A Highly Efficient Gradient Boosting Decision\nTree,\u201d in Advances in Neural Information Processing Systems (NeurIPS),\n2017, pp. 3146\u20133154."}],"event":{"name":"20th Conference on Computer Science and Intelligence Systems (FedCSIS)","theme":"Computer Science and Intelligence Systems","location":"Krak\u00f3w, Poland","acronym":"FedCSIS","number":"20","start":{"date-parts":[[2025,9,14]]},"end":{"date-parts":[[2025,9,17]]}},"container-title":["Annals of Computer Science and Information Systems","Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS)"],"original-title":[],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T07:52:05Z","timestamp":1761119525000},"score":1,"resource":{"primary":{"URL":"https:\/\/annals-csis.org\/Volume_43\/drp\/3227.html"}},"subtitle":[],"proceedings-subject":"Computer Science and Information Systems","short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":10,"URL":"https:\/\/doi.org\/10.15439\/2025f3227","relation":{},"ISSN":["2300-5963"],"issn-type":[{"value":"2300-5963","type":"print"}],"subject":[],"published":{"date-parts":[[2025,10,15]]}}}