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Papers by Chronological Order

• T. Yang, L. Wu, R. Sun, Y. Shi, Y. Wang, M. Darbari, N. Liu, J. Sun and L. Hong. Self-Evolving Code-with-Image Reasoning. ArXiv. 2026.
• J. Zhang, L. Wu, K. Wan, H. Chen and L. Hong. SPECTRA: Pushing the KV Cache Beyond the 2-Bit Cliff via Spectral Transform Coding. ArXiv. 2026.
• G. Min, L. Wu, M. Darbari, C. Chen and L. Hong. Toward Reliable Context Compression for Long-Horizon Agents: An Empirical Study of Execution Instability. ArXiv. 2026.
• L. Wu, K. Wan, M. Darbari and L. Hong. Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026), Jeju Island, Republic of Korea, August, 2026. (Blue Sky Ideas Track) [DOI] [Earlier ArXiv Version]
• P. Liu, Q. Shen, J. Shen, C. Yao, K. Kao, R. Arora, D. Xu, B. Zheng, Y. Ren, B. Le, A. Hooshmand, I. Lapchuk, J. Bottaro, R. Muthuregunathan, C. Johnson, L. Hong, J. Wu and W. Zhang. A Unified Structured Query Understanding Framework for Industrial Semantic Search. In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026), Jeju Island, Republic of Korea, August, 2026. [DOI] [Earlier ArXiv Version]
• P. Goulart, L. Wu, K. Wan, E. E. Papalexakis and L. Hong. Field Aware Agent Skill Retrieval. ArXiv. 2026.
• D. Xu, B. Zheng, J. Shen, Q. Xiao, B. H. Le, W. Pu, S. Gupta, R. Zhou, N. Saraf, A. Leung, Q. Shen, L. Hong, J. Wu and W. Zhang. Unified Semantic Modeling Framework for Large-Scale Job Understanding at LinkedIn. In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2026), Melbourne, VIC, Australia, July, 2026. [DOI] [Earlier ArXiv Version]
• J. Zhang, L. Wu, M. Darbari and L. Hong. WiSP: A Working-Set View of Mixture-of-Experts Serving on Extremely Low-Resource Hardware. ArXiv. 2026. [Code]
• Z. Zheng, G. Min, Y. Zhu, L. Wu, L. Hong, C. Chen and J. Li. SAPO: Step-Aligned Policy Optimization for Reasoning-Based Generative Recommendation. ArXiv. 2026.
• Y. He, W. Zheng, Y. Zhu, Z. Zheng, L. Su, S. Vasudevan, Q. Guo, L. Hong and J. Li. SemCoT: Accelerating Chain-of-Thought Reasoning through Semantically-Aligned Implicit Tokens. In Advances in Neural Information Processing Systems 38 (NeurIPS 2025), San Diego, CA, USA, December, 2025. [DOI] [Earlier ArXiv Version]
• Z. Fu, Y. Cao, Y. Chen, A. Lunia, L. Dong, N. Saraf, R. Jiang, Y. Dai, Q. Song, T. Wang, G. Li, D. Koh, H. Wei, Z. Wang, A. Gupta, C. Jiang, J. Shen, L. Hong and W. Zhang. LANTERN: Scalable Distillation of Large Language Models for Job-Person Fit and Explanation. ArXiv. 2025.
• X. Wang, L. Wu, L. Hong, H. Liu and Y. Fu. LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations. ACM Transactions on Intelligent Systems and Technology, Volume 16, Feb, 2025. [DOI]
• P. Liu, J. Shen, Q. Shen, C. Yao, K. Kao, D. Xu, R. Arora, B. Zheng, C. Johnson, L. Hong, J. Wu and W. Zhang. Powering Job Search at Scale: LLM-Enhanced Query Understanding in Job Matching Systems. In Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM 2025), Seoul, Korea, November, 2025. [DOI]
• Z. Zheng, S. Wang, Z. Chen, Y. Zhu, Y. He, L. Hong, Q. Guo and J. Li. CoRAG: Enhancing Hybrid Retrieval-Augmented Generation Through a Cooperative Retriever Architecture. In Proceedings of The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025), Suzhou, China, November, 2025. [DOI]
• Y. Juan, J. Shen, S. Zhang, Q. Shen, C. Johnson, L. Simon, L. Hong and W. Zhang. Scaling Retrieval for Web-Scale Recommenders: Lessons from Inverted Indexes to Embedding Search. In Proceedings of the Nineteenth ACM Conference on Recommender Systems (RecSys 2025), Prague, Czech Republic, September, 2025. [DOI]
• P. Liu, R. Arora, X. Shi, B. Le, Q. Shen, J. Shen, C. Jiang, N. Zhiltsov, P, Bannur, Y. Zhu, L. Dong, H. Wei, Q. Guo, L. Simon, L. Hong and W. Zhang. A Scalable and Efficient Signal Integration System for Job Matching. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2 (KDD 2025), Toronto, Canada, August, 2025. [DOI]
• Y. Zhu, J. Ma, L. Wu, Q. Guo, L. Hong and J. Li. Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables. In Proceedings of the Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore, April, 2025. [DOI]
• J. Shen, Y. Juan, P. Liu, W. Pu, S. Zhang, Q. Shen, L. Hong and W. Zhang. Learning Links for Adaptable and Explainable Retrieval. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, ID, USA, October 2024. [DOI]
• Y. Zhu, L. Wu, B. Zhang, S. Wang, Q. Guo, L. Hong, L. Simon and and J. Li. Understanding and Modeling Job Marketplace with Pretrained Language Models. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Boise, ID, USA, October 2024. [DOI] [Earlier ArVix Version]
• Y. Zhu, L. Wu, Q. Guo, L. Hong and J. Li. Collaborative Large Language Model for Recommender Systems. In Proceedings of the ACM on Web Conference 2024 (WWW 2024), Singapore, May 2024. [DOI] [Earlier ArVix Version]
• X. Wang, L. Wu, L. Hong, H. Liu and Y. Fu. LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations. ArXiv. 2024.
• J. Shen, Y. Juan, S. Zhang, P. Liu, W. Pu, S. Vasudevan, Q. Song, F. Borisyuk, K. Qianqi Shen, H, Wei, Y. Ren, Y. S. Chiou, S. Kuang, Y. Yin, B. Zheng, M. Wu, S. Gharghabi, X. Wang, H. Xue, Q. Guo, D. Hewlett, L. Simon, L. Hong and W. Zhang. Learning to Retrieve for Job Matching. ArXiv. 2024.
• Y. Zhu, J. Ma, L. Wu, Q. Guo, L. Hong and J. Li. Path-Specific Counterfactual Fairness for Recommender Systems. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), Long Beach CA, August 2023. [DOI] [Earlier ArVix Version]
• Q. Zhu, L. Wu, Q. Guo and L. Hong. Remote Work Optimization with Robust Multi-channel Graph Neural Networks. ArXiv. 2022.
• Z. Wang, X. Yin, T. Li, and L. Hong. Causal Meta-Mediation Analysis: Inferring Dose-Response Function From Summary Statistics of Many Randomized Experiments. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020). Virtual Event, August 2020. (Full Paper, 16% Acceptance) [DOI] [Local Copy]
• R. Guo, X. Zhao, A. Henderson, L. Hong, and H. Liu. Debiasing Grid-based Product Search in E-commerce. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020). Virtual Event, August 2020. (Full Paper, 16% Acceptance) [DOI] [Local Copy]
• J. Wang, K. Ding, L. Hong, H. Liu, and J. Caverlee. Next-item Recommendation with Sequential Hypergraphs. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Virtual Event, July 2020. (Full Paper, 26% Acceptance) [DOI]
• M. Tanjim, C. Su, E. Benjamin, D. Hu, L. Hong, and J. McAuley. Attentive Sequential Models of Latent Intent for Next Item Recommendation. In Proceedings of The Web Conference 2020 (WWW 2020), Taipei, April 2020. [Local Copy] [DOI]
• X. Zhao, R. Louca, D. Hu, and L. Hong. The Difference Between a Click and a Cart-Add: Learning Interaction-Specific Embeddings. In Companion Proceedings of the Web Conference 2020 (WWW 2020), Taipei, April 2020. [DOI]
• J. Wang, R. Louca, D. Hu, C. Cellier, J. Caverlee and L. Hong. Time to Shop for Valentine’s Day: Shopping Occasions and Sequential Recommendation in E-commerce. In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020), Houston, Texas, Feb, 2020. (Full Paper, 15% Acceptance) [Local Copy] [DOI]
• R. Louca, M. Bhattacharya, D. Hu and L. Hong. Joint Optimization of Profit and Relevance for Recommendation Systems in E-commerce. In Proceedings of RMSE Workshop 2019 at RecSys 2019. [Local Copy]
• X. Yin and L. Hong. The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis. In Proceedings of the 25th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August, 2019. (Full Paper, Oral Presentation, 6.4% Acceptance) [Local Copy] [DOI]
• H. Jiang, A. Sabharwal, A. Henderson, D. Hu and L. Hong. Understanding the Role of Style in E-commerce Shopping. In Proceedings of the 25th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August, 2019. (Full Paper, 20% Acceptance) [Local Copy] [DOI]
• A. Stanton, A. Ananthram, C. Su and L. Hong. Revenue, Relevance, Arbitrage and More: Joint Optimization Framework for Search Experiences in Two-Sided Marketplaces. ArXiv. 2019.
• X. Zhao, R. Louca, D. Hu and L. Hong. Learning Item-Interaction Embeddings for User Recommendations. DAPA at WSDM 2019. [Local Copy]
• N. Ju, D. Hu, A. Henderson and L. Hong. A Sequential Test for Selecting the Better Variant – Online A/B testing, Adaptive Allocation, and Continuous Monitoring. In Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019), Melbourne, Australia, Feb, 2019. (Full Paper, 16% Acceptance) [Local Copy] [DOI]
• D. Hu, R. Louca, L. Hong and J. McAuley. Learning Within-Session Budgets from Browsing Trajectories. In the proceedings of the 12th ACM Conference on Recommender Systems (RecSys 2018), Vancouver, Canada, October, 2018. (Short Paper, 25% Acceptance) [Local Copy] [DOI]
• L. Wu, D. Hu, L. Hong and H. Liu. Turning Clicks into Purchases: Revenue Optimization for Product Search in E-Commerce. In Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, U.S.A. July 8-12, 2018. (Full Paper, 21% Acceptance) [Local Copy] [DOI]
• A. Stanton, L. Hong and M. Rajashekhar. Buzzsaw: A System for High Speed Feature Engineering. In Proceedings of the 1st SysML Conference, Stanford, CA, Feb, 2018. [Local Copy]
• Q. Wu, H. Wang, L. Hong and Y. Shi. Returning is Believing: Optimizing Long-term User Engagement in Recommender Systems. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM 2017), Singapore, November, 2017. (Full Paper, 21% Acceptance) [Local Copy] [DOI]
• K. Aryafar, D. Guillory and L. Hong. An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy. In Proceedings of AdKDD & TargetAd 2017 workshop, held in conjunction with the 23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, August, 2017. [PDF]
• Y. Ning, Y. Shi, L. Hong, H. Rangwala and N. Ramakrishnan. A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. In Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August, 2017. (Full Paper, 20.8% Acceptance) [Local Copy] [DOI]
• T. Chen, L. Hong, Y. Shi and Y. Sun. Joint Text Embedding for Personalized Content-based Recommendation. ArXiv. 2017.
• T. Chen, Y. Sun, Y. Shi and L. Hong. On Sampling Strategies for Neural Network-based Collaborative Filtering. In Proceedings of the 23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, August, 2017. (Full Paper, 17% Acceptance) [Local Copy] [Local Supplementary] [DOI] [Code]
• Q. Zhao, Y. Shi and L. Hong. GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees. In Proceedings of the 26th International Conference on World Wide Web (WWW 2017), Perth, Australia, April, 2017. (Full Paper, 17% Acceptance) [Local Copy] [DOI]
• L. Hong, Y. Shi and S. Rajan. Learning Optimal Card Ranking from Query Reformulation. ArXiv. 2016.
• L. Hong and A. Boz. An Unbiased Data Collection and Content Exploitation/Exploration Strategy for Personalization. ArXiv. 2016.
• M. Qian, L. Hong, Y. Shi and S. Rajan. Structured Sparse Regression for Recommender Systems [Short Paper]. In Proceedings of the 24th ACM International  Conference on Information & Knowledge Management (CIKM 2015). Melbourne, Australia.[Local Copy] [DOI]
• Z. Yang, L. Hong, D. Yin and B. D. Davison. Ranking Authors with Learning-to-Rank Topic Modeling. In International Journal of Innovative Computing, Information and Control (IJICIC), 11(4), August 2015. [PDF]
• X. Yi, L. Hong, E. Zhong, NN. Liu and S. Rajan. Beyond Clicks: Dwell Time in Personalization. In Proceedings of the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, Silicon Valley, USA, October, 2014. (Full Paper, 23% Acceptance) [Local Copy] [DOI] Best Paper Award
• A. Ahmed, L. Hong and A. Smola. Nested Chinese Restaurant Franchise Process:  Applications to User Tracking and Document Modeling. In Proceedings of the 30th International Conference on Machine Learning (ICML 2013), Atlanta, GA, May, 2013. [PDF] [Supplementary]
• A. Ahmed, L. Hong and A. Smola. Hierarchical Geographical Modeling of User Locations from Social Media Posts. In Proceedings of the 22nd International Conference on World Wide Web (WWW 2013), Rio de Janeiro, Brazil, May, 2013. (Full Paper, 15% Acceptance) [Local Copy]  [DOI]
• L. Hong, A. Doumith and B. D. Davison. Co-Factorization Machines: Modeling User Interests and Predicting Individual Decisions in Twitter. In Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM 2013), Rome, Italy, Feb, 2013. (Full Paper, 19% Acceptance) [Local Copy] [DOI] Best Paper Nominated
• Z. Yang, L. Hong and B. D. Davison. Academic Network Analysis: A Joint Topic Modeling Approach. In the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013). Niagara Falls, Canada, August 25-28, 2013. (Full Paper) [Local Copy]
• L. Hong.  Mining and Understanding Online Conversational Media. Doctoral Dissertation, Department of Computer Science and Engineering, Lehigh University, May. [Local Copy]
• L. Hong and S. Yang. The First Workshop on User Engagement Optimization. In Proceedings of the 22nd ACM International  Conference on Information & Knowledge Management (CIKM 2013). ACM, New York, NY, USA. [DOI]
• Yookyung Kim and L. Hong. Topic Model in Personalization. Yahoo TechPulse Conference (TechPulse 2013), Santa Clara, CA, Dec., 2013. [Internal Publication]
• L. Hong, R. Bekkerman, J. Adler and B. D. Davison. Learning to Rank Social Update Streams. In Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2012), Portland, Oregon, August, 2012.  [Local Copy] [DOI] [Slides]
• L. Hong, A. Ahmed, S. Gurumurthy, A. Smola and K. Tsioutsiouliklis. Discovering Geographical Topics in the Twitter Stream. In Proceedings of the 21st International Conference on World Wide Web (WWW 2012), Lyon, France, 2012. [Local Copy] [DOI] [Slides]
• L. Hong, A. Doumith and B. D. Davison. Personalized Retweet Prediction in Twitter. In Proceedings of the 4th Workshop on Information in Networks (WIN), New York City, September, 2012. [Local Copy] [Slides]
• L. Hong. A Tutorial on Probabilistic Latent Semantic Analysis. ArXiv. 2012.
• D. Yin, L. Hong and B. D. Davison. Structural Link Analysis and Prediction in Microblogs [Short Paper]. In Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM 2011), Glasgow, Scotland, 2011. [Local Copy] [DOI]
• L. Hong, D. Yin, J. Guo and B. D. Davison. Tracking Trends: Incorporating Term Volume into Temporal Topic Models. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2011), San Diego, CA, USA, 2011. [Local Copy] [DOI] [Slides] (Oral Presentation)
• L. Hong, B. Dom, S. Gurumurthy and K. Tsioutsiouliklis. A Time-Dependent Topic Model for Multiple Text Streams. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2011), San Diego, CA, USA, 2011. [Local Copy][DOI]
• D. Yin, L. Hong, Z. Xue and B. D. Davison. Temporal Dynamics of User Interests in Tagging Systems. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), San Francisco, USA, 2011. [Local Copy]
• D. Yin, L. Hong, X. Xiong and B. D. Davison. Link Formation Analysis in MicroBlogs [Poster]. In Proceedings of the 34th Annual ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2011), Beijing, China, July, 2011. [Local Copy] [DOI]
• D. Yin, L. Hong and B. D. Davison. Exploiting Session-like Behaviors in Tag Prediction [Poster]. In Proceedings of the 20th international conference on World Wide Web (WWW 2011), Hyderabad, India. [Local Copy] [DOI]
• L. Hong, O. Dan and B. D. Davison. Predicting Popular Messages in Twitter [Poster]. In Proceedings of the 20th international conference on World Wide Web (WWW 2011), Hyderabad, India. [Local Copy] [DOI] Best Poster Award
• L. Hong and B. D. Davison. Empirical Study of Topic Modeling in Twitter. In Proceedings of Workshop on Social Media Analytics (SOMA 2010), held in conjunction the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC., USA, July 25 – July 28, 2010. [Local Copy] [DOI]
• D. Yin, Z. Xue, L. Hong and B. D. Davison. A Probabilistic Model for Personalized Tag Prediction. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC., USA, July 25 – July 28, 2010. (Full paper, 17% Acceptance) [Local Copy] [DOI]
• Z. Yang, L. Hong and B. D. Davison. Topic-driven Multi-type Citation Network Analysis. In Proceedings of The 9th International Conference on Adaptivity, Personalization and Fusion of Heterogeneous Information (RIAO 2010), Paris, France, April, 2010. [Local Copy] [DOI]
• L. Hong and B. D. Davison. Wanted: A Unified Model for Search in Social Media [Position Paper]. In Proceedings of The Third Annual Workshop on Search in Social Media (SSM 2010), held in conjunction with Third ACM International Conference on Web Search and Data Mining (WSDM), New York, USA, February 2010. [Local Copy]
• L. Hong, Z. Yang and B. D. Davison. Incorporating Participant Reputation in Community-driven Question Answering Systems. In Proceedings of the Symposium on Social Intelligence and Networking (SIN09), held in conjunction with IEEE SocialCom-09 , Vancouver, Canada, August 2009. [Local Copy] [DOI]
• L. Hong and B. D. Davison. A Classification-Based Approach to Question Answering in Discussion Boards. In Proceedings of the 32st Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2009), Boston, July 2009. [Local Copy] [DOI]
• J. Wang, L. Hong and B. D. Davison. Tag Recommendation Using Keywords and Association Rules. In Proceedings of the 2009 ECML PKDD Discovery Challenge Workshop, Bled, Slovenia, September 2009. [Local Copy] [Proceeding Copy]
• D. Yin, Z. Xue, L. Hong, B. D. Davison, A. Kontostathis and L. Edwards. Detection of Harassment on Web 2.0. In Proceedings of the 1st CAW2 (Content Analysis in Web 2.0) Workshop, Madrid, Spain, April 2009. [Local Copy] [Proceeding Copy]