activity
20222026
most citedFacet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR2026

RedVisor: Reasoning-Aware Prompt Injection Defense via Zero-Copy KV Cache Reuse

Mingrui Liu, Sixiao Zhang, Cheng Long +1

Large Language Models (LLMs) are increasingly vulnerable to Prompt Injection (PI) attacks, where adversarial instructions hidden within retrieved contexts hijack the model's execut…

cs.IR2026

Facet-Aware Multi-Head Mixture-of-Experts Model with Text-Enhanced Pre-training for Sequential Recommendation

Mingrui Liu, Sixiao Zhang, Cheng Long

Sequential recommendation (SR) systems excel at capturing users' dynamic preferences by leveraging their interaction histories. Most existing SR systems assign a single embedding v…

cs.CV2025

Wukong Framework for Not Safe For Work Detection in Text-to-Image systems

Mingrui Liu, Sixiao Zhang, Cheng Long

Text-to-Image (T2I) generation is a popular AI-generated content (AIGC) technology enabling diverse and creative image synthesis. However, some outputs may contain Not Safe For Wor…

cs.IR20241 cited

Facet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation

Mingrui Liu, Sixiao Zhang, Cheng Long

Sequential recommendation (SR) systems excel at capturing users' dynamic preferences by leveraging their interaction histories. Most existing SR systems assign a single embedding v…

cs.LG2022

On Inferring User Socioeconomic Status with Mobility Records

Zheng Wang, Mingrui Liu, Cheng Long +3

When users move in a physical space (e.g., an urban space), they would have some records called mobility records (e.g., trajectories) generated by devices such as mobile phones and…