works on

From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.IR2026

SlimPer: Make Personalization Model Slim and Smart

Siqi Wang, Xianjie Chen, Shaofeng Deng +42

SlimPer is a transformer‑based recommendation model that treats personalized ranking as iterative refinement of a compact user‑item knowledge base, achieving linear per‑layer cost…

cs.CV2026

DriftScope: Measuring The Hidden Effects of Diffusion Model Adaptation

Héctor Laria, Yiping Han, Julian D. Santamaria +4

Adapting pre-trained text-to-image diffusion models, whether to learn new visual concepts or erase unwanted ones, is routinely evaluated on its intended effects alone. We argue thi…

cs.IR2026

ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified Recommendation

Yihua Zhang, Mingfu Liang, Jiyan Yang +11

Recent advances in multimodal recommenders excel at feature fusion but remain opaque and inefficient decision-makers, lacking explicit reasoning and self-awareness of uncertainty.…

cs.IR2026

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit

Huixue Zhou, Hengrui Gu, Xi Liu +15

The deployment of Large Language Models (LLMs) in recommender systems for predicting Click-Through Rates (CTR) necessitates a delicate balance between computational efficiency and…

cs.IR2025

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction

Zhichen Zeng, Xiaolong Liu, Mengyue Hang +25

Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous informati…

cs.IR2025

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation

Mingfu Liang, Xi Liu, Rong Jin +104

Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommenda…