activity
20202026
most citedUltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation

34 citations · 92 across the 30 of their papers we have counts for

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Showing cs.AIShow all

5 papers · 1 filter

cs.AI2026

RealWorldShop: Benchmarking and Improving Conversational Shopping Agents in Real-World E-commerce

Xinwei Yang, Kelong Mao, Yudong Guo +4

Large language models are reshaping ecommerce from static recommenders into interactive shopping assistants, yet real-world shopping requires session-level decision support: users…

cs.AI2026

Learning from Online User Feedback for Shopping Agents

Haobo Zhang, Kelong Mao, Sulong Xu +2

Large language model-based shopping agents are increasingly deployed in real-world e-commerce platforms, generating massive amounts of user interaction logs that provide valuable s…

cs.AI2026

ComBodied Agents: a New Paradigm of Human-Centric Agentic AI

Qianggang Ding, Xingyao Wang, Rui Feng +19

After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the person fo…

cs.AI2026

ComboShoppingBench: Evaluating LLM Agents for Budget-Constrained Basket Shopping with Coupons

Adrian Li, Kelong Mao, Yudong Guo +7

Real-world shopping often requires constructing a basket of complementary items rather than retrieving a single product. Such combo-shopping tasks arise in device setup, meal prepa…

cs.AI2026

SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use

Jiayin Zhu, Kelong Mao, Yudong Guo +4

Skills are becoming a reusable operational layer for LLM agents, encoding SOPs, domain rules, tool workflows, scripts, and validation routines. In realistic skill repositories, ove…