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20242026
most citedCheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent

19 citations · 70 across the 32 of their papers we have counts for

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6 papers · 1 filter

cs.IR2026

HVM-GraphRAG: Holistic-View Multimodal Graph Retrieval-Augmented Generation on Complex Document

Xin He, Yili Wang, Wenqi Fan +4

Question answering (QA) over complex documents requires models to retrieve and integrate evidence distributed across distant document regions and modalities. Multimodal GraphRAG pr…

cs.LG2026

Learning Spatio-Temporal Foundation Models from Pure Synthetic Data

Yutong Feng, Shiyuan Piao, Yutong Xia +5

Spatio-Temporal Foundation Models (STFMs) aim to learn generalizable representations of complex dynamical systems across space and time. However, existing approaches suffer from di…

cs.IR2026

CFALR: Collaborative Filtering-Augmented Large Language Model for Personalized Fashion Outfit Recommendation

Yujuan Ding, Junrong Liao, Yunshan Ma +4

Personalized outfit recommendation poses a significant challenge in e-commerce and social media platforms, requiring systems that balance user preferences with aesthetic compatibil…

cs.IR2026

ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning

Jiani Huang, Shijie Wang, Liangbo Ning +2

With the rise of LLMs, there is an increasing need for intelligent recommendation assistants that can handle complex queries and provide personalized, reasoning-driven recommendati…

cs.CL2026

Double-Calibration: Towards Reliable LLMs via Calibrating Knowledge and Reasoning Confidence

Yuyin Lu, Ziran Liang, Yanghui Rao +3

Reliable reasoning in Large Language Models (LLMs) is challenged by their propensity for hallucination. While augmenting LLMs with Knowledge Graphs (KGs) improves factual accuracy,…

cs.LG2026

DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis

Rui An, Haohao Qu, Wenqi Fan +2

Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within this realm, Transformers have emerged a…