The following papers have been accepted at SIGIR eCom 2023:

Workshop Papers
       1  . Don’t Lose Your Head(s): Model Pre-Training and Exploitation for Personalization  [PDF]
              Pablo Hernan Rodriguez Zivic, Jorge Sánchez and Rafael Carrascosa.

       2  . Behavior-driven Query Similarity Prediction based on Pre-trained Language Models for E-Commerce Search  [PDF]
              Yupin Huang, Jiri Gesi, Xinyu Hong, Kai Zhong, Han Cheng, Vivek Mittal, Qingjun Cui and Vamsi Salaka.

       3  . Cross-Domain User Similarity without Overlapping Attributes via Optimal Transport Theory  [PDF]
              Genki Kusano and Masafumi Oyamada.

       4  . CDR-Adapter: Learning Adapters to Dig Out More Transferring Ability for Cross-Domain Recommendation Models  [PDF]
              Yanyu Chen, Yao Yao, Wai Kin Victor Chan, Li Xiao, Kai Zhang, Liang Zhang and Ye Yun.

       5  . Ontology Guided Supervised Contrastive Learning For Fine-grained Attribute Extraction From Fashion Images  [PDF]
              Shubham Singh Paliwal, Bhagyashree Gaikwad, Mayur Patidar, Manasi Patwardhan, Lovekesh Vig, Meghna Mahajan, Bagya Lakshmi V and Shirish Karande.

       6  . GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation  [PDF]
              Jinming Li, Wentao Zhang, Tian Wang, Guanglei Xiong, Alan Lu and Gerard Medioni.

       7  . Improve Machine Translation in E-commerce Multilingual Search Using Contextual Signal from Search Sessions  [PDF]
              Bryan Zhang, Taichi Nakatani, Stephan Walter, Elizabeth Milkovits and Amita Misra.

       8  . (Vector) Space is Not the Final Frontier: Product Search as Program Synthesis  [PDF]
              Jacopo Tagliabue and Ciro Greco.

       9  . Pricing the Nearly Known - When Semantic Similarity is Just not Enough  [PDF]
              Gilad Fuchs, Pavel Petrov, Ido Ben-Shaul, Matan Mandelbrod, Oded Zinman, Dmitry Basin and Vadim Arshavski.

       10 . These Deals Won’t Last! Longevity, Uniformity, and Bias in Product Badge Assignment in eCommerce Platforms  [PDF]
                Archit Bansal, Kunal Banerjee and Abhijnan Chakraborty.

       11 . Real-time Integration of Social Media Background in Dynamic Recommendation Systems  [PDF]
                Yihong Zhang, Xiu Susie Fang and Takahiro Hara.

       12 . Aggregation-Based Answering for Broad Product Questions  [PDF]
                Eilon Sheetrit, Yuval Nezri, Avihai Mejer and David Carmel.

       13 . Dynamic Filter Discovery and Ranking Framework for Search and Browse Experiences in E-Commerce  [PDF]
                Ligaj Pradhan, Le Yu, Bingxin Li, Venkata Simhadri and Jeyaprakash Singarayar.

       14 . Aligning Ranking Objectives with E-commerce Search Intent  [PDF]
                Dominic Seyler, Ehsan Ebrahimzadeh, Alex Cozzi and Abraham Bagherjeiran.

       15 . XWalk: Random Walk Based Candidate Retrieval for Product Search  [PDF]
                Jon Eskreis-Winkler, Yubin Kim and Andrew Stanton.

       16 . Measuring Feature Quality for Improved Ranking Performance  [PDF]
                Sulagna Gope, Ravi Sugandharaju, Anup Kotalwar and Vamsi Salaka.

       17 . Exploring the Viability of Synthetic Query Generation forRelevance Prediction  [PDF]
                Aditi Chaudhary, Karthik Raman, Krishna Srinivisan, Kazuma Hashimoto, Mike Bendersky and Marc Najork.

       18 . Contextual Font Recommendations based on User Intent  [PDF]
                Sanat Sharma, Jayant Kumar, Jing Zheng and Tracy King.

       19 . X4SR: Post-Hoc Explanations for Session-based Recommendations  [PDF]
                Jyoti Narwariya, Priyanka Gupta, Garima Gupta, Lovekesh Vig and Gautam Shroff.