most citedSaviorRec: Semantic-Behavior Alignment for Cold-Start Recommendation

1 citations · 2 across the 8 of their papers we have counts for

collaborators

10 papers

cs.IR2026

AdaM-Rec: Adaptive Modality Routing for Multimodal Recommendation

Honghao Fu, Jiacheng Chen, Manxi Lin +7

While recent multimodal recommender systems have demonstrated the effectiveness of incorporating visual and textual information to improve downstream performance, most existing met…

cs.CV2026

Structured Local Differential Modeling for AI-Generated Image Detection

Jiazhen Yang, Ruijin Jin, Junjun Zheng +3

The rapid advancement of AI-generated content has made the reliable detection of generated images an increasingly critical challenge. Existing detection methods are often dominated…

cs.IR2026

RecGPT-V3 Technical Report

Bowen Zheng, Chao Yi, Dian Chen +26

Large language models (LLMs) are transforming recommender systems from matching co-occurrence patterns in historical behavior toward reasoning about the intent that drives it. RecG…

cs.IR2026

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping

Jiacheng Chen, Tao Zhang, Manxi Lin +26

The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents. A common design wraps an LLM…

cs.AI2026

Pailitao-MMSearch: Building Native E-Commerce Multimodal Search Foundation

Xiaohan Ye, Xu Chen, Zihan Gong +15

The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex multimodal interactions that sea…

cs.CV2026

Adaptive Forensic Feature Refinement via Intrinsic Importance Perception

Jiazhen Yang, Junjun Zheng, Kejia Chen +5

With the rapid development of generative models and multimodal content editing technologies, the key challenge in synthetic image detection (SID) lies in cross-distribution general…

cs.IR2026

CoNRec: Context-Discerning Negative Recommendation with LLMs

Xinda Chen, Jiawei Wu, Yishuang Liu +5

Understanding what users like is relatively straightforward; understanding what users dislike, however, remains a challenging and underexplored problem. Research into users' negati…

cs.IR2025★ 1 cited

FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets

Kairui Fu, Tao Zhang, Shuwen Xiao +9

Semantic identifiers (SIDs) have gained increasing attention in generative retrieval (GR) for recommendation due to their meaningful semantic discriminability. However, current stu…

cs.CV2025

MIRAGE: Towards AI-Generated Image Detection in the Wild

Cheng Xia, Manxi Lin, Jiexiang Tan +6

The spreading of AI-generated images (AIGI), driven by advances in generative AI, poses a significant threat to information security and public trust. Existing AIGI detectors, whil…

cs.IR2025★ 1 cited

SaviorRec: Semantic-Behavior Alignment for Cold-Start Recommendation

Yining Yao, Ziwei Li, Shuwen Xiao +5

In recommendation systems, predicting Click-Through Rate (CTR) is crucial for accurately matching users with items. To improve recommendation performance for cold-start and long-ta…