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Zhihao Xie, Junfeng Wu, Xinting Hu, Junchao Huang, Li Jiang 7/15/2026 arxiv
natural language processingVideo generative models commonly rely on latent spaces learned by 3D Variational Autoencoders (3D-VAEs). However, conventional 3D-VAEs are mainly optimized for pixel-level reconstruction, which can limit the semantic and spatio-temporal structure captured by their latents. Meanwhile, Video Foundatio...
Ximeng Mao, Nanda H. Krishna, Avery Hee-Woon Ryoo, Matthew G. Perich, Guillaume Lajoie 7/15/2026 arxiv
computer visionRobust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has shown that tokenizing neural data at the spike level facilitates multi-session pretraining and delivers state-of-the-art decoding performance. However,...
Ashutosh Jha, Michel Besserve, Simon Buchholz 7/15/2026 arxiv
machine learningLinear Independent Component Analysis (ICA) recovers jointly independent source signals from their linear mixtures. To achieve this, classical ICA algorithms attempt to maximize non-Gaussianity, measured by negentropy, which is linked to independence by information theory. Because exact negentropy o...
Zhen Li, Zian Meng, Shuwei Shi, Mingliang Zhai, Jiaming Tan, Chuanhao Li, Kaipeng Zhang 7/15/2026 arxiv
computer visionBuilding interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligence. Recent video generative models provide a data-driven route toward this goal by predicting future observations conditioned on user actions, and a...
Mustafa Chasmai, Vincent Dumoulin, Jenny Hamer 7/15/2026 arxiv
computer visionBioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent work has shown that supervision alone can produce SotA species detection models when trained on this large-scale data -- however, there remains unutili...
Jeremy Guntoro, Alexander Dack, Dylan Danno, Michaela JanΔoviΔovΓ‘, KriΕΎan JurinoviΔ, Vanessa Smilansky 7/15/2026 arxiv
reinforcement learningGenomic foundation models such as Evo 2 learn rich sequence representations, but their value for biosecurity screening is largely unexplored. We ask how much biosecurity-relevant signal is linearly accessible in these representations by training minimal linear and attention probes on frozen Evo 2 la...
Xiao Ye, Jacob Dineen, Evan Zhu, Shijie Lu, Kevin Song, Ben Zhou 7/15/2026 arxiv
machine learningForecasters are evaluated by backtesting, which replays resolved questions and grades the probability the system would have assigned before the outcome was known. For LLMs, two channels leak the answer into this test. A model that retrieves can surface reports written after the event, turning foreca...
Hefeng Zhou, Jinxuan Zhang, Jiong Lou, Yuxin Liu, Chaochao Lu, Jingjing Qu, Jie Li 7/15/2026 arxiv
natural language processingThe emergence of Chain-of-Thought (CoT) reasoning has significantly enhanced the ability of large language models (LLMs) to tackle complex, multi-step tasks. However, when errors occur, current interaction approaches typically involve re-generating another response that may make mistakes again, or u...
Boyuan Wang, Zhenyuan Zhang, Zhiqin Yang, Peijun Gu, Shuya Wang, Xiaofeng Wang, Xianghui Ze, Yifan Chang, Guosheng Zhao, Jiangnan Shao, Guan Huang, Hengyu Liu, Yonggang Zhang, Wei Xue, Chunyuan Guan, Chenglin Pu, Yike Guo, Xingang Wang, Zheng Zhu 7/15/2026 arxiv
natural language processingAutonomous data collection governs the volume and quality of real-world trajectories for manipulation policy learning. Existing pipelines reduce human effort via self-resetting, VLM verification, or language-guided correction, yet episode-scoped fixes must be reissued whenever the same failure recur...
Xanthi Kokkinou, Chaido Mizeli, Nafsika Koulaxidou, Marina Delianidi, Konstantinos Diamantaras 7/15/2026 arxiv
reinforcement learningThis paper presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a conversational AI assistant based on Retrieval-Augmented Generation. It aims to enhance earthquake preparedness and conscious action among primary-s...
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