{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:00:06Z","timestamp":1772906406774,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539090","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:41Z","timestamp":1660331201000},"page":"4363-4371","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["ReprBERT: Distilling BERT to an Efficient Representation-Based Relevance Model for E-Commerce"],"prefix":"10.1145","author":[{"given":"Shaowei","family":"Yao","sequence":"first","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Jiwei","family":"Tan","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Juhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Xiaoyi","family":"Zeng","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Keping","family":"Yang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371780"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143874"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_4_1","unstructured":"Geoffrey Hinton Oriol Vinyals and Jeff Dean. 2015. Distilling the Knowledge in a Neural Network. arXiv:1503.02531 [stat.ML]"},{"key":"e_1_3_2_2_5_1","volume-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems -","volume":"2","author":"Hu Baotian","year":"2014","unstructured":"Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014. Convolutional Neural Network Architectures for Matching Natural Language Sentences. In Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 2 (Montreal, Canada) (NIPS'14). 2042--2050."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505665"},{"key":"e_1_3_2_2_7_1","volume-title":"Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring. arXiv:1905.01969 [cs.CL]","author":"Humeau Samuel","year":"2020","unstructured":"Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2020. Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring. arXiv:1905.01969 [cs.CL]"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3326937.3341259"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"crossref","unstructured":"Xiaoqi Jiao Yichun Yin Lifeng Shang Xin Jiang Xiao Chen Linlin Li Fang Wang and Qun Liu. 2019. TinyBERT: Distilling BERT for Natural Language Understanding. arXiv:1909.10351 [cs.CL]","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_2_11_1","volume-title":"Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search. arXiv preprint arXiv:2101.04850","author":"Liu Ziyang","year":"2021","unstructured":"Ziyang Liu, Zhaomeng Cheng, Yunjiang Jiang, Yue Shang, Wei Xiong, Sulong Xu, Bo Long, and Di Jin. 2021. Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search. arXiv preprint arXiv:2101.04850 (2021)."},{"key":"e_1_3_2_2_12_1","unstructured":"Wenhao Lu Jian Jiao and Ruofei Zhang. 2020. TwinBERT: Distilling Knowledge to Twin-Structured BERT Models for Efficient Retrieval. arXiv:2002.06275 [cs.IR]"},{"key":"e_1_3_2_2_13_1","volume-title":"Pruning Convolutional Neural Networks for Resource Efficient Inference. In 5th International Conference on Learning Representations.","author":"Molchanov Pavlo","year":"2017","unstructured":"Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, and Jan Kautz. 2017. Pruning Convolutional Neural Networks for Resource Efficient Inference. In 5th International Conference on Learning Representations."},{"key":"e_1_3_2_2_14_1","volume-title":"Passage Re-ranking with BERT. arXiv preprint arXiv:1901.04085","author":"Nogueira Rodrigo","year":"2019","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. 2019. Passage Re-ranking with BERT. arXiv preprint arXiv:1901.04085 (2019)."},{"key":"e_1_3_2_2_15_1","unstructured":"Rodrigo Nogueira Wei Yang Kyunghyun Cho and Jimmy Lin. 2019. Multi-Stage Document Ranking with BERT. arXiv:1910.14424 [cs.IR]"},{"key":"e_1_3_2_2_16_1","unstructured":"H. Palangi L. Deng Y. Shen J. Gao X. He J. Chen X. Song and R. Ward. 2014. Semantic Modelling with Long-Short-Term Memory for Information Retrieval. arXiv:1412.6629 [cs.IR]"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2016.2520371"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.5555\/3016100.3016292"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1"},{"key":"e_1_3_2_2_20_1","volume-title":"Overview of the Third Text REtrieval Conference (TREC-3). Gaithersburg, MD: NIST, 109--126","author":"Robertson Stephen","unstructured":"Stephen Robertson, S. Walker, S. Jones, M. M. Hancock-Beaulieu, and M. Gatford. 1995. Okapi at TREC-3. In Overview of the Third Text REtrieval Conference (TREC-3). Gaithersburg, MD: NIST, 109--126."},{"key":"e_1_3_2_2_21_1","unstructured":"Victor Sanh Lysandre Debut Julien Chaumond and Thomas Wolf. 2020. DistilBERT a distilled version of BERT: smaller faster cheaper and lighter. arXiv:1910.01108 [cs.CL]"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2661935"},{"key":"e_1_3_2_2_23_1","volume-title":"Patient Knowledge Distillation for BERT Model Compression. arXiv preprint arXiv:1908.09355","author":"Sun Siqi","year":"2019","unstructured":"Siqi Sun, Yu Cheng, Zhe Gan, and Jingjing Liu. 2019. Patient Knowledge Distillation for BERT Model Compression. arXiv preprint arXiv:1908.09355 (2019)."},{"key":"e_1_3_2_2_24_1","unstructured":"Raphael Tang Yao Lu Linqing Liu Lili Mou Olga Vechtomova and Jimmy Lin. 2019. Distilling Task-Specific Knowledge from BERT into Simple Neural Networks. arXiv:1903.12136 [cs.CL]"},{"key":"e_1_3_2_2_25_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_2_26_1","volume-title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. AAAI Press, 2922--2928","author":"Wan Shengxian","year":"2016","unstructured":"Shengxian Wan, Yanyan Lan, Jun Xu, Jiafeng Guo, Liang Pang, and Xueqi Cheng. 2016. Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. AAAI Press, 2922--2928."},{"key":"e_1_3_2_2_27_1","volume-title":"International Conference on Learning Representations.","author":"Wang Wei","year":"2020","unstructured":"Wei Wang, Bin Bi, Ming Yan, Chen Wu, Jiangnan Xia, Zuyi Bao, Liwei Peng, and Luo Si. 2020. StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291039"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403309"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450129"},{"key":"e_1_3_2_2_31_1","unstructured":"Hongchun Zhang Tianyi Wang Xiaonan Meng and Yi Hu. 2019. Improving Semantic Matching via Multi-Task Learning in E-Commerce. In eCOM@SIGIR."}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Washington DC USA","acronym":"KDD '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539090","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539090","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:51Z","timestamp":1750183791000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539090"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":31,"alternative-id":["10.1145\/3534678.3539090","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539090","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}