Tootfinder

Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation
Narges Nemati, Mostafa Haghir Chehreghani
https://arxiv.org/abs/2506.10658

Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation
Matrix completion is a widely adopted framework in recommender systems, as predicting the missing entries in the user-item rating matrix enables a comprehensive understanding of user preferences. However, current graph neural network (GNN)-based approaches are highly sensitive to noisy or irrelevant edges--due to their inherent message-passing mechanisms--and are prone to overfitting, which limits their generalizability. To overcome these challenges, we propose a novel method called Matrix Comp…

MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization
Sean Feeney, Reuben Tate, John Golden, Stephan Eidenbenz
https://arxiv.org/abs/2508.05883 htt…

MPS-JuliQAOA: User-friendly, Scalable MPS-based Simulation for Quantum Optimization
We present the MPS-JuliQAOA simulator, a user-friendly, open-source tool to simulate the Quantum Approximate Optimization Algorithm (QAOA) of any optimization problem that can be expressed as diagonal Hamiltonian. By leveraging Julia-language constructs and the ITensor package to implement a Matrix Product State (MPS) approach to simulating QAOA, MPS-Juli-QAOA effortlessly scales to 512 qubits and 20 simulation rounds on the standard de-facto benchmark 3-regular MaxCut QAOA problem. MPS-JuliQAO…

Joint Beamforming with Extremely Large Scale RIS: A Sequential Multi-Agent A2C Approach
Zhi Chai, Jiajie Xu, Justin P Coon, Mohamed-Slim Alouini
https://arxiv.org/abs/2506.10815

Joint Beamforming with Extremely Large Scale RIS: A Sequential Multi-Agent A2C Approach
It is a challenging problem to jointly optimize the base station (BS) precoding matrix and the reconfigurable intelligent surface (RIS) phases simultaneously in a RIS-assisted multiple-user multiple-input-multiple-output (MU-MIMO) scenario when the size of the RIS becomes extremely large. In this paper, we propose a deep reinforcement learning algorithm called sequential multi-agent advantage actor-critic (A2C) to solve this problem. In addition, the discrete phase of RISs, imperfect channel st…

Joint Spatial Division and Multiplexing with Customized Orthogonal Group Channels in Multi-RIS-Assisted Systems
Weicong Chen, Chao-Kai Wen, Wankai Tang, Xiao Li, Shi Jin
https://arxiv.org/abs/2507.01641

Joint Spatial Division and Multiplexing with Customized Orthogonal Group Channels in Multi-RIS-Assisted Systems
Reconfigurable intelligent surfaces (RISs) offer the unique capability to reshape the radio environment, thereby simplifying transmission schemes traditionally contingent on channel conditions. Joint spatial division and multiplexing (JSDM) emerges as a low-overhead transmission scheme for multi-user equipment (UE) scenarios, typically requiring complex matrix decomposition to achieve block-diagonalization of the effective channel matrix. In this study, we introduce an innovative JSDM design th…

Adjoints of Polytopes: Determinantal Representations and Smoothness
Clemens Br\"user, Mario Kummer, Dmitrii Pavlov
https://arxiv.org/abs/2507.01672 ht…

Adjoints of Polytopes: Determinantal Representations and Smoothness
In this article we study determinantal representations of adjoint hypersurfaces of polytopes. We prove that adjoint polynomials of all polygons can be represented as determinants of tridiagonal symmetric matrices of linear forms with the matrix size being equal to the degree of the adjoint. We prove a sufficient combinatorial condition for a surface in the projective three-space to have a determinantal representation and use it to show that adjoints of all three-dimensional polytopes with at mo…

This https://arxiv.org/abs/2505.20730 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

What LLMs Miss in Recommendations: Bridging the Gap with Retrieval-Augmented Collaborative Signals
User-item interactions contain rich collaborative signals that form the backbone of many successful recommender systems. While recent work has explored the use of large language models (LLMs) for recommendation, it remains unclear whether LLMs can effectively reason over this type of collaborative information. In this paper, we conduct a systematic comparison between LLMs and classical matrix factorization (MF) models to assess LLMs' ability to leverage user-item interaction data. We further in…

Communication-Efficient Publication of Sparse Vectors under Differential Privacy
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
https://arxiv.org/abs/2506.20234

Communication-Efficient Publication of Sparse Vectors under Differential Privacy
In this work, we propose a differentially private algorithm for publishing matrices aggregated from sparse vectors. These matrices include social network adjacency matrices, user-item interaction matrices in recommendation systems, and single nucleotide polymorphisms (SNPs) in DNA data. Traditionally, differential privacy in vector collection relies on randomized response, but this approach incurs high communication costs. Specifically, for a matrix with $N$ users, $n$ columns, and $m$ nonzero …

Knowledge-aware Diffusion-Enhanced Multimedia Recommendation
Xian Mo, Fei Liu, Rui Tang, Jintao, Gao, Hao Liu
https://arxiv.org/abs/2507.16396 https://…

Knowledge-aware Diffusion-Enhanced Multimedia Recommendation
Multimedia recommendations aim to use rich multimedia content to enhance historical user-item interaction information, which can not only indicate the content relatedness among items but also reveal finer-grained preferences of users. In this paper, we propose a Knowledge-aware Diffusion-Enhanced architecture using contrastive learning paradigms (KDiffE) for multimedia recommendations. Specifically, we first utilize original user-item graphs to build an attention-aware matrix into graph neural …

Cross-Subreddit Behavior as Open-Source Indicators of Coordinated Influence: A Case Study of r/Sino & r/China
Manon Pilaud, Ian McCulloh
https://arxiv.org/abs/2507.16857 htt…

Cross-Subreddit Behavior as Open-Source Indicators of Coordinated Influence: A Case Study of r/Sino & r/China
This study investigates potential indicators of coordinated influence activity among users participating in both r/Sino and r/China, two ideologically divergent Reddit communities focused on Chinese political discourse. Topic modeling and sentiment analysis are applied to all posts and comments authored by dual-subreddit users to construct a user-topic sentiment matrix. Individual sentiment patterns are compared to global topic baselines derived from the broader r/Sino and r/China populations. …