5 papers
UNISON: A Unified Framework for Learning from Scored Bags
Ofek Kirshenboim, Or Shkuri, Shani Finkelshtein +1
We introduce UNISON, a unified framework that bridges multiple instance learning and recommendation systems by treating both as instances of learning from scored bag collections of…
ReMatch: Boosting Representation through Matching for Multimodal Retrieval
Qianying Liu, Xiao Liang, Zhiqiang Zhang +6
We present ReMatch, a framework that leverages the generative strength of MLLMs for multimodal retrieval. Previous approaches treated an MLLM as a simple encoder, ignoring its gene…
RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Services
Fei Zhao, Chonggang Lu, Haofu Qian +9
As a key medium for human interaction and information exchange, social networking services (SNS) pose unique challenges for large language models (LLMs): heterogeneous workloads, f…
HyMiRec: A Hybrid Multi-interest Learning Framework for LLM-based Sequential Recommendation
Jingyi Zhou, Cheng Chen, Kai Zuo +5
Large language models (LLMs) have recently demonstrated strong potential for sequential recommendation. However, current LLM-based approaches face critical limitations in modeling…
Cross-Scenario Unified Modeling of User Interests at Billion Scale
Manjie Xu, Cheng Chen, Xin Jia +9
User interests on content platforms are inherently diverse, manifesting through complex behavioral patterns across heterogeneous scenarios such as search, feed browsing, and conten…