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Tong Zhang

6 papers indexed

arxivcs.CVcs.AI2026-07-24

dRAE: Representation Autoencoder with Hyper-Spherical Codes

Tianren Ma, Lin Long, Chuyan Chen, Mu Zhang, Junbo Zhao, Tong Zhang, et al.

In this work, we aim to discretize the high-dimensional visual representations to bridge the gap with language models - a non-trivial challenge, as existing quantization methods suffer from codebook collapse, failing to scale while preserving semantic coherence. We identify the r…

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arxivcs.LGcs.AIstat.ML2026-07-22

When Does Recurrence Become an Algorithm? Convergence Selection in Weight-Tied Looped Transformers

Tong Zhang, Junhao Hu, Yun Peng, Tao Xie

When does a weight-tied looped transformer -- one block applied T times -- implement an actual algorithm? We answer with four findings from controlled populations on group word problems. (1) The budget law: free training installs a linear computation frontier, a mechanism that so…

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arxivcs.SDcs.AI2026-07-20

Time-Frequency Consistency Learning for Robust Speech Deepfake Detection

Jun Xue, Zhuolin Yi, Yanzhen Ren, Yihuan Huang, Jiayu Xiong, Yi Chai, et al.

Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to controlled additive noise scenarios, lacking systematic investigation of the complex distortions introduced by acoustic front-end (AFE) proc…

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arxivcs.NI2026-07-14

High-Precision Hybrid FA-PSO Based Inversion of Building Material Parameters for Fundamental Wireless Performance Evaluation

Zhuowei Li, Yalei Zhu, Hanqing Zhang, Sui Li, Meng Chen, Tong Zhang, et al.

In this paper, we propose an inversion method based on the firefly particle swarm optimization (FA-PSO) algorithm to estimate the permittivity, conductivity, and thickness of building materials using the free-space method. To improve convergence efficiency and robustness, an adap…

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arxivcs.SDcs.AI2026-07-05

Auto-AEG: Scalable Data Construction for Open-Vocabulary Audio Event Grounding

Zihan Zhang, Xize Cheng, Wenhao Yan, Tong Zhang, Dongjie Fu, Boyun Zhang, et al.

Large Audio-Language Models (LALMs) reason fluently about sound yet struggle to localize precisely when events occur, while classical Sound Event Detection attains frame-level precision only over a closed label set. At the intersection of these paradigms lies the task of Open-Voc…

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