4 papers
Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation
Ziyun Xu, Bosen Ding, Yue Zhang +10
Industrial recommendation systems predominantly adopt a passive ranking paradigm that infers user preferences from implicit behavioral signals (e.g., clicks, dwell time) rather tha…
ConAlign: Conditional Alignment Framework for Balancing Biased and Unbiased Recommendation
Jingcheng Zhang, Yihan Wang, Qi Song +1
Industry recommender systems trained on observational data suffer from various biases that create filter bubbles, causing user interests to collapse into narrow categories and seve…
Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching
Yihan Wang, Fei Xiong, Zhexin Han +3
Two-tower models are widely adopted in the industrial-scale matching stage across a broad range of application domains, such as content recommendations, advertisement systems, and…
Enhancing Playback Performance in Video Recommender Systems with an On-Device Gating and Ranking Framework
Yunfei Yang, Zhenghao Qi, Honghuan Wu +6
Video recommender systems (RSs) have gained increasing attention in recent years. Existing mainstream RSs focus on optimizing the matching function between users and items. However…