Tootfinder

Enhanced Image Recognition Using Gaussian Boson Sampling
Si-Qiu Gong, Ming-Cheng Chen, Hua-Liang Liu, Hao Su, Yi-Chao Gu, Hao-Yang Tang, Meng-Hao Jia, Yu-Hao Deng, Qian Wei, Hui Wang, Han-Sen Zhong, Xiao Jiang, Li Li, Nai-Le Liu, Chao-Yang Lu, Jian-Wei Pan
https://arxiv.org/abs/2506.19707

Enhanced Image Recognition Using Gaussian Boson Sampling
Gaussian boson sampling (GBS) has emerged as a promising quantum computing paradigm, demonstrating its potential in various applications. However, most existing works focus on theoretical aspects or simple tasks, with limited exploration of its capabilities in solving real-world practical problems. In this work, we propose a novel GBS-based image recognition scheme inspired by extreme learning machine (ELM) to enhance the performance of perceptron and implement it using our latest GBS device, J…

Knapsack and Shortest Path Problems Generalizations From A Quantum-Inspired Tensor Network Perspective
Sergio Mu\~niz Subi\~nas, Jorge Mart\'inez Mart\'in, Alejandro Mata Ali, Javier Sedano, \'Angel Miguel Garc\'ia-Vico
https://arxiv.org/abs/2506.11711

Knapsack and Shortest Path Problems Generalizations From A Quantum-Inspired Tensor Network Perspective
In this paper, we present two tensor network quantum-inspired algorithms to solve the knapsack and the shortest path problems, and enables to solve some of its variations. These methods provide an exact equation which returns the optimal solution of the problems. As in other tensor network algorithms for combinatorial optimization problems, the method is based on imaginary time evolution and the implementation of restrictions in the tensor network. In addition, we introduce the use of symmetrie…

EditGen: Harnessing Cross-Attention Control for Instruction-Based Auto-Regressive Audio Editing
Vassilis Sioros, Alexandros Potamianos, Giorgos Paraskevopoulos
https://arxiv.org/abs/2507.11096

EditGen: Harnessing Cross-Attention Control for Instruction-Based Auto-Regressive Audio Editing
In this study, we investigate leveraging cross-attention control for efficient audio editing within auto-regressive models. Inspired by image editing methodologies, we develop a Prompt-to-Prompt-like approach that guides edits through cross and self-attention mechanisms. Integrating a diffusion-based strategy, influenced by Auffusion, we extend the model's functionality to support refinement edits, establishing a baseline for prompt-guided audio editing. Additionally, we introduce an alternativ…

Assessing the Alignment of Audio Representations with Timbre Similarity Ratings
Haokun Tian, Stefan Lattner, Charalampos Saitis
https://arxiv.org/abs/2507.07764

Assessing the Alignment of Audio Representations with Timbre Similarity Ratings
Psychoacoustical so-called "timbre spaces" map perceptual similarity ratings of instrument sounds onto low-dimensional embeddings via multidimensional scaling, but suffer from scalability issues and are incapable of generalization. Recent results from audio (music and speech) quality assessment as well as image similarity have shown that deep learning is able to produce embeddings that align well with human perception while being largely free from these constraints. Although the existing human-…