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Author

Aman Gupta

Observed name: Gupta, Aman
Observed institution: LinkedIn (United States)
ORCID: 0009-0007-6620-841X
Observed ORCID: 0009-0007-6620-841X
OpenAlex ID: A5090079907
LiRank: Industrial Large Scale Ranking Models at LinkedIn
2024 · Fedor Borisyuk, Mingzhou Zhou, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 8
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LiMAML: Personalization of Deep Recommender Models via Meta Learning
2024 · Ruofan Wang, Prakruthi Prabhakar, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 5
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Neural Optimization with Adaptive Heuristics for Intelligent Marketing System
2024 · Changshuai Wei, Benjamin Zelditch, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 4
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Generalized Deep Mixed Models
2022 · Jun Shi, Chengming Jiang, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 3
Your Spending Needs Attention: Modeling Financial Habits with Transformers
2025 · Braithwaite, D. T., Cavalcanti, Misael, et al. · arXiv (Cornell University) · 2
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360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation
2025 · Firooz, Hamed, Sanjabi, Maziar, et al. · arXiv (Cornell University) · 2
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Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems
2025 · Behdin, Kayhan, Fatahibaarzi, Ata, et al. · arXiv (Cornell University) · 1
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LiNR: Model Based Neural Retrieval on GPUs at LinkedIn
2024 · Fedor Borisyuk, Qingquan Song, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 1
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Optimizing for Member Value in an Edge Building Marketplace
2023 · Ayan Acharya, Siyuan Gao, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 1
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Promoting Inactive Members in Edge-Building Marketplace
2023 · Ayan Acharya, Siyuan Gao, et al. · ACM Web Conference (WWW) · 1
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LANTERN: Scalable Distillation of Large Language Models for Job-Person Fit and Explanation
2025 · Fu, Zhoutong, Cao, Yihan, et al. · arXiv (Cornell University)
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Efficient Algorithms for Leveraging LLMs for Generative and Predictive Recommender Systems
2025 · Kayhan Behdin, Yun Dai, et al.
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Scaling Down, Serving Fast: Compressing and Deploying Efficient LLMs for Recommendation Systems
2025 · Kayhan Behdin, Ata Fatahibaarzi, et al. · Conference on Empirical Methods in Natural Language Processing: Industry Track (EMNLP)
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Efficient user history modeling with amortized inference for deep learning recommendation models
2024 · Hertel, Lars, Daftary, Neil, et al. · arXiv (Cornell University)
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Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference
2023 · Aman Gupta, S. Sathiya Keerthi, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
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Works count: 15
Citation count: 28
H-index: 3
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