The following papers have been accepted at SIGIR eCom 2020:

Workshop Papers
       1. Light Feed-Forward Networks for Shard Selection in Large-scale Product Search  [PDF]
            Heran Lin, Pengcheng Xiong, Danqing Zhang, Fan Yang, Ryoichi Kato, Mukul Kumar, William Headden and Bing Yin (Amazon)
       2. Query Transformation for Multi-Lingual Product Search  [PDF]
            Qie Hu, Hsiang-Fu Yu, Vishnu Narayanan, Ivan Davchev, Rahul Bhagat (Amazon) and Inderjit Dhillon (Amazon & UT Austin)
       3. Context-Aware Learning to Rank with Self-Attention  [PDF]
            Przemysław Pobrotyn, Tomasz Bartczak, Mikołaj Synowiec, Radosław Białobrzeski and Jarosław Bojar (Allegro.pl)
       4. Counterfactual Learning to Rank using Heterogeneous Treatment Effect Estimation  [PDF]
            Mucun Tian, Chun Guo, Vito Ostuni and Zhen Zhu (Pandora)
       5. Shopping in the Multiverse: A Counterfactual Approach to In-Session Attribution  [PDF]
            Jacopo Tagliabue and Bingqing Yu (Coveo Labs)
       6. Improved Session based Recommendation using Graph-based Item Embedding  [PDF]
            Madiraju Srilakshmi, Gourab Chowdhury and Sudeshna Sarkar (IIT Kharagpur)
       7. Discriminative Pre-training for Low Resource Title Compression in Conversational Grocery  [PDF]
            Snehasish Mukherjee, Phaniram Sayapaneni and Shankar Subramanya (Walmart Labs)
       8. A Comparison of Supervised Learning to Match Methods for Product Search  [PDF]
            Fatemeh Sarvi (AIRLab, University of Amsterdam), Nikos Voskarides (University of Amsterdam), Lois Mooiman (Bol.com),
            Sebastian Schelter (University of Amsterdam & Ahold Delhaize) and Maarten de Rijke (University of Amsterdam & Ahold Delhaize)
       9. Bias Correction for Supervised Learning in Email Marketing  [PDF]
            Moumita Sinha, Yancheng Li, Wei Shung Chung and Paul Hsiung (Adobe)
     10. Atlas: A Dataset and Benchmark for E-commerce Clothing Product Categorization  [PDF]
             Venkatesh Umaashankar (Ericsson Research), Girish Shanmugam S (Uppsala University) and Aditi Prakash (University of Colorado, Boulder)
     11. Fantastic Embeddings and How to Align Them: Zero-Shot Inference in a Multi-Shop Scenario  [PDF]
             Federico Bianchi, Jacopo Tagliabue, Bingqing Yu, Luca Bigon and Ciro Greco (Coveo Labs)
     12. Revenue, Relevance, Arbitrage and More: Joint Optimization Framework for Search Experiences in Two-Sided Marketplaces  [PDF]
             Andrew Stanton (Etsy Inc.), Akhila Ananthram (Etsy Inc.), Congzhe Su (Etsy Inc.) and Liangjie Hong (LinkedIn)
     13. Exploiting Neural Query Translation into Cross Lingual Information Retrieval  [PDF]
             Liang Yao, Baosong Yang, Haibo Zhang, Weihua Luo and Boxing Chen (Alibaba)
     14. Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers  [PDF]
             Mariya Hendriksen (AIRLab, University of Amsterdam), Ernst Kuiper (Bol.com), Pim Nauts (Albert Heijn),
             Sebastian Schelter (University of Amsterdam & Ahold Delhaize) and Maarten de Rijke (University of Amsterdam & Ahold Delhaize)
     15. A Pipeline of Aspect Detection and Sentiment Analysis for E-Commerce Customer Reviews  [PDF]
             Haozheng Tian and James White (Home Depot)
     16. KENRM : Knowledge Enhanced Neural Relevance Matching in Online Tourism Industry  [PDF]
             Feng Wei, Shihao Li, Dekun Yang and Bufeng Zhang (Alibaba)
     17. Online Product Feature Recommendations with Interpretable Machine Learning  [PDF]
             Mingming Guo, Nian Yan, Xiquan Cui, Simon Hughes and Khalifeh Al Jadda (Home Depot)
     18. Aspect Category Detection in Product Reviews using Contextual Representation  [PDF]
             Shiva Ramezani, Razieh Rahimi and James Allan (College of Information and Computer Sciences, UMass, Amherst)
     19. Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval  [PDF]
             Tianchi Bi, Liang Yao, Baosong Yang, Haibo Zhang, Weihua Luo and Boxing Chen (Alibaba)

Data Challenge Papers
       1. Synerise at SIGIR Rakuten Data Challenge 2020: Efficient Manifold Density Estimator for Cross-Modal Retrieval  
            Barbara Rychalska and Jacek Dąbrowski |     Team Synerise - Cross-Modal Retrieval
       2. CBB-FE, CamemBERT and BiT Feature Extraction for Multimodal Product Classification and Retrieval  
            Hou Wei Chou, Younghun Lee, Lei Chen, Yandi Xia and Wei Te Chen |     Team Beantown
       3. A Multi-Modal Late Fusion Model for E-Commerce Product Classification and Retrieval  
            Shuo Wang, Ye Bi and Zhongrui Fan |     Team pa_curis
       4. Large Scale Multimodal Classification Using an Ensemble of Transformer Models and Co-Attention  
            Varnith Chordia and Vijay Kumar |     Team Alto
       5. Synerise at SIGIR Rakuten Data Challenge 2020: Efficient Manifold Density Estimator for Multimodal Classification  
            Dominika Basaj, Barbara Rychalska, Jacek Dąbrowski and Konrad Gołuchowski |     Team Synerise - Classification
       6. Deep Multi-level Fusion Learning Framework forMulti-modal Product Classification  
            Ekansh Verma, Souradip Chakraborty and Vinodh Motupalli |     Team Transformers