1 citations · 1 across the 15 of their papers we have counts for
15 papers
Enhancing Social Intelligence in LLMs with Hierarchical Reasoning and Utterance-Level Goal Rewarding
Xiaofeng Wang, Kakam Chong, Shuai Xiao +9
Large language models (LLMs) excel in structured tasks but struggle with dynamic social interactions, where success requires long-term goal coordination and rapid adaptation. Curre…
PRECTR-V2:Unified Relevance-CTR Framework with Cross-User Preference Mining, Exposure Bias Correction, and LLM-Distilled Encoder Optimization
Shuzhi Cao, Rong Chen, Ailong He +2
In search systems, effectively coordinating the two core objectives of search relevance matching and click-through rate (CTR) prediction is crucial for discovering users' interests…
DAIAN: Deep Adaptive Intent-Aware Network for CTR Prediction in Trigger-Induced Recommendation
Zhihao Lv, Longtao Zhang, Ailong He +3
Recommendation systems are essential for personalizing e-commerce shopping experiences. Among these, Trigger-Induced Recommendation (TIR) has emerged as a key scenario, which utili…
LLP: LLM-Based Product Pricing in E-commerce
Hairu Wang, Sheng You, Qiheng Zhang +5
Unlike Business-to-Consumer e-commerce platforms (e.g., Amazon), inexperienced individual sellers on Consumer-to-Consumer platforms (e.g., eBay) often face significant challenges i…
Multi-Value-Product Retrieval-Augmented Generation for Industrial Product Attribute Value Identification
Huike Zou, Haiyang Yang, Yindu Su +5
Identifying attribute values from product profiles is a key task for improving product search, recommendation, and business analytics on e-commerce platforms, which we called Produ…
GSID: Generative Semantic Indexing for E-Commerce Product Understanding
Haiyang Yang, Qinye Xie, Qingheng Zhang +7
Structured representation of product information is a major bottleneck for the efficiency of e-commerce platforms, especially in second-hand ecommerce platforms. Currently, most pr…
Evaluating Multi-Turn Bargain Skills in LLM-Based Seller Agent
Issue Yishu Wang, Kakam Chong, Xiaofeng Wang +7
In online second-hand marketplaces, multi-turn bargaining is a crucial part of seller-buyer interactions. Large Language Models (LLMs) can act as seller agents, negotiating with bu…
PRECTR: A Synergistic Framework for Integrating Personalized Search Relevance Matching and CTR Prediction
Rong Chen, Shuzhi Cao, Ailong He +2
The two primary tasks in the search recommendation system are search relevance matching and click-through rate (CTR) prediction -- the former focuses on seeking relevant items for…
IU4Rec: Interest Unit-Based Product Organization and Recommendation for E-Commerce Platform
Wenhao Wu, Xiaojie Li, Lin Wang +8
Most recommendation systems typically follow a product-based paradigm utilizing user-product interactions to identify the most engaging items for users. However, this product-based…
FishBargain: An LLM-Empowered Bargaining Agent for Online Fleamarket Platform Sellers
Dexin Kong, Xu Yan, Ming Chen +3
Different from traditional Business-to-Consumer e-commerce platforms~(e.g., Amazon), online fleamarket platforms~(e.g., Craigslist) mainly focus on individual sellers who are lack…
TACLR: A Scalable and Efficient Retrieval-based Method for Industrial Product Attribute Value Identification
Yindu Su, Huike Zou, Lin Sun +7
Product Attribute Value Identification (PAVI) involves identifying attribute values from product profiles, a key task for improving product search, recommendation, and business ana…
IPL: Leveraging Multimodal Large Language Models for Intelligent Product Listing
Kang Chen, Qingheng Zhang, Chengbao Lian +6
Unlike professional Business-to-Consumer (B2C) e-commerce platforms (e.g., Amazon), Consumer-to-Consumer (C2C) platforms (e.g., Facebook marketplace) are mainly targeting individua…
MetaSplit: Meta-Split Network for Limited-Stock Product Recommendation
Wenhao Wu, Jialiang Zhou, Ailong He +3
Compared to business-to-consumer (B2C) e-commerce systems, consumer-to-consumer (C2C) e-commerce platforms usually encounter the limited-stock problem, that is, a product can only…
Effective Two-Stage Knowledge Transfer for Multi-Entity Cross-Domain Recommendation
Jianyu Guan, Zongming Yin, Tianyi Zhang +5
In recent years, the recommendation content on e-commerce platforms has become increasingly rich -- a single user feed may contain multiple entities, such as selling products, shor…
Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction
Yunfeng Zhao, Xu Yan, Xiaoqiang Gui +6
Conversion rate (CVR) prediction is an essential task for large-scale e-commerce platforms. However, refund behaviors frequently occur after conversion in online shopping systems,…