7 papers · 1 filter
LLMDistill4Ads: Using Cross-Encoders to Distill from LLM Signals for Advertiser Keyphrase Recommendations at eBay
Soumik Dey, Benjamin Braun, Naveen Ravipati +2
E-commerce sellers are advised to bid on keyphrases to boost their advertising campaigns. These keyphrases must be relevant to prevent irrelevant items from cluttering Search syste…
BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations
Ashirbad Mishra, Jinyu Zhao, Soumik Dey +3
In the domain of sponsored search advertising, the focus of Keyphrase recommendation has largely been on exact match types, which pose issues such as high management expenses, limi…
To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay
Soumik Dey, Hansi Wu, Binbin Li
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). The relevance of advertiser keyphrases p…
GraphEx: A Graph-based Extraction Method for Advertiser Keyphrase Recommendation
Ashirbad Mishra, Soumik Dey, Marshall Wu +5
Online sellers and advertisers are recommended keyphrases for their listed products, which they bid on to enhance their sales. One popular paradigm that generates such recommendati…
Middleman Bias in Advertising: Aligning Relevance of Keyphrase Recommendations with Search
Soumik Dey, Wei Zhang, Hansi Wu +2
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). Keyphrases must be pertinent to items; o…
From Lazy to Prolific: Tackling Missing Labels in Open Vocabulary Extreme Classification by Positive-Unlabeled Sequence Learning
Ranran Haoran Zhang, Bensu Uçar, Soumik Dey +3
Open-vocabulary Extreme Multi-label Classification (OXMC) extends traditional XMC by allowing prediction beyond an extremely large, predefined label set (typically to $10^{1…