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Tejaswi Tenneti

ACL 2026SIGIR 2026效率与系统强化学习与后训练可解释性对齐与偏好
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方向广度11
合作网络3
0 一作 · 2 篇 · ACL 2026 / SIGIR 2026

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2026 顶会论文

2
作者位次 #4/6ACL 2026Poster· ACL Industry Track

G roc LM : Grocery Category Recommendation in E -Commerce with Large Language Models

Yuan Zhong · Chuanwei Ruan · Moein Hasani · Tejaswi Tenneti · Haixun Wang · Fenglong Ma

摘要

The rapid growth of online grocery shopping requires recommendation systems that capture cyclical purchasing behavior and diverse user intents. Traditional item-level methods face scalability and accuracy challenges, motivating category-level recommendation as a more structured and practical alte...

效率与系统可解释性强化学习与后训练OpenReview 项目页
作者位次 #7/7SIGIR 2026Poster· Information Retrieval (Industry)

A Cascaded Generative Approach for e-Commerce Recommendations

Moein Hasani · Hamidreza Shahidi · Trace Levinson · Yuan Zhong · Guanghua Shu · Vinesh Gudla · Tejaswi Tenneti

摘要

Personalized storefronts in large e-commerce marketplaces are often assembled from many independent components: static themes per page section (''placement''), retrieval systems to fetch eligible products per placement, and pointwise rankers to order content. While effective in optimizing for agg...

对齐与偏好强化学习与后训练效率与系统OpenReview

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