1 citations · 2 across the 7 of their papers we have counts for
9 papers
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…
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…
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…
RankGR: Rank-Enhanced Generative Retrieval with Listwise Direct Preference Optimization in Recommendation
Kairui Fu, Changfa Wu, Kun Yuan +8
Generative retrieval (GR) has emerged as a promising paradigm in recommendation systems by autoregressively decoding identifiers of target items. Despite its potential, current app…
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…
HiVid-Narrator: Hierarchical Video Narrative Generation with Scene-Primed ASR-anchored Compression
Haoxuan Li, Mengyan Li, Junjun Zheng
Generating structured narrations for real-world e-commerce videos requires models to perceive fine-grained visual details and organize them into coherent, high-level stories--capab…
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…
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…
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…