arXiv:2606. 00884v1 Announce Type: cross Abstract: We study cross-subject emotion recognition from EEG, a practically important yet challenging problem in brain-computer interfaces.
By Jiaxin Qing, Lexin Li
arXiv:2505. 12532v3 Announce Type: replace-cross Abstract: Efficiently adapting large pretrained models is critical under tight compute and memory budgets.
By Ahmet Bilican, M. Ak{\i}n Y{\i}lmaz, A. Murat Tekalp, R. G\"okberk Cinbi\c{s}
arXiv:2606. 02631v1 Announce Type: cross Abstract: This paper studies whether audio, images, and video can share a common wavelet token schema rather than relying on separate modality-specific latent grids.
By Shenghao Ding
arXiv:2509. 22259v4 Announce Type: replace-cross Abstract: We study the extent to which rotary position encodings (RoPE), a recent transformer position encoding algorithm broadly adopted in large language models (LLMs) and vision transformers (ViTs), can be applied to graph-structured data.
By Isaac Reid, Arijit Sehanobish, Cederik H\"ofs, Bruno Mlodozeniec, Leonhard Vulpius, Federico Barbero, Adrian Weller, Krzysztof Choromanski, Richard E. Turner, Petar Veli\v{c}kovi\'c
arXiv:2606. 00111v1 Announce Type: cross Abstract: State-of-the-art learned image compression (LIC) schemes are increasingly based on hybrid CNN-transformer architectures.
By Haisheng Fu, Runyu Yang, Feng Ding, Siyu Zhu, Jie Liang, Xiaoxiao Li, Zhenman Fang, Jingning Han
arXiv:2606. 17830v1 Announce Type: cross Abstract: Neural network parameter spaces are inherently non-injective, as distinct parameter configurations can realize identical functions through functional equivalence.
By Viet-Hoang Tran, Vinh Khanh Bui, Van-Hoan Trinh, Tan Lai Ngoc, Tan M. Nguyen