Trends · 研究趋势
数据来自 Hugging Face 论文的 AI 提取关键词,按月统计研究方向的增长与热度。
Rui-Jie Zhu, Zixuan Wang, Kai Hua +30 authors
LoopLM, a family of pre-trained Looped Language Models, enhances reasoning by integrating iterative computation and entropy regularization during pre-training, achieving superior performance with better knowledge manipulation.
Jonas Geiping, Sean McLeish, Neel Jain +6 authors
A novel language model scales test-time computation by reasoning in latent space, outperforming token-based models on reasoning benchmarks.
Xinlei Yu, Zhangquan Chen, Yongbo He +34 authors
Latent space is emerging as a fundamental computational substrate for language-based models, offering advantages over explicit token-level approaches through continuous representation that mitigates linguistic redundancy and sequential inefficiency.
Kangsheng Duan, Ziyang Xu, Wenyu Liu +3 authors
A lightweight image inpainting framework achieves high-fidelity results with significantly reduced parameters and inference time through novel local-global interaction blocks and adaptive distillation strategies.
Ruihang Chu, Yefei He, Zhekai Chen +10 authors
Wan-Move enhances motion control in video generative models by integrating motion-aware features into latent space, enabling high-quality and scalable video synthesis.
Jiaru Zou, Xiyuan Yang, Ruizhong Qiu +10 authors
LatentMAS enables efficient, lossless collaboration among LLM agents in latent space, improving performance and reducing computational costs compared to text-based methods.
Jingfeng Yao, Yuda Song, Yucong Zhou +1 authors
A unified visual tokenizer pre-training framework (VTP) improves generative performance by optimizing image-text contrastive, self-supervised, and reconstruction losses, leading to better scaling properties and higher zero-shot accuracy and faster convergence.
Justin Cui, Jie Wu, Ming Li +6 authors
A method is proposed to enhance long-horizon video generation by using sampled segments from self-generated long videos to guide student models, maintaining quality and consistency without additional supervision or retraining.
Shibo Hao, Sainbayar Sukhbaatar, DiJia Su +4 authors
A new reasoning paradigm, Coconut, utilizes continuous representations in latent space to enhance LLM performance on complex reasoning tasks, particularly those requiring backtracking.
Jiaxing Li, Kai Zou, Cindy Zhou +7 authors
Joint distillation aligns initialization and refinement distributions to improve coverage and diversity in autoregressive video generation.
Yue Liao, Pengfei Zhou, Siyuan Huang +11 authors
Genie Envisioner integrates policy learning, evaluation, and simulation using a video diffusion model and neural simulator for instruction-driven robotic manipulation.
Weichen Fan, Haiwen Diao, Quan Wang +2 authors
Unified Autoencoding combines semantic and pixel-level information through a frequency-band modulator, resulting in a latent space with state-of-the-art performance on image benchmarks.
Sensen Gao, Zhaoqing Wang, Qihang Cao +3 authors
PixWorld presents a unified pixel-space diffusion approach for 3D reconstruction and generation that overcomes limitations of latent-space methods through direct image-level supervision and geometry-aware feature alignment.
Yuran Wang, Siqiao Huang, Mingleyang Li +21 authors
OpenWAM factorizes world-action pretraining into modular components to identify key design principles, yielding a scalable open model with strong simulation and real-robot performance.
Yoav HaCohen, Nisan Chiprut, Benny Brazowski +13 authors
LTX-Video, a transformer-based latent diffusion model, integrates Video-VAE and denoising transformer for efficient high-resolution video generation with temporal consistency.
Fu-Yun Wang, Zhaoyang Huang, Alexander William Bergman +9 authors
The Phased Consistency Model (PCM) addresses limitations in Latent Consistency Models (LCM) and outperforms them in high-resolution, text-conditioned image and few-step text-to-video generation.
Shenghai Yuan, Jinfa Huang, Xianyi He +5 authors
ConsisID is a tuning-free, DiT-based IPT2V model that uses frequency-aware identity control to generate high-quality, identity-preserving videos by decomposing facial features into low and high-frequency elements.
Quentin Garrido, Mahmoud Assran, Nicolas Ballas +3 authors
Image World Models extend Joint-Embedding Predictive Architecture to predict global photometric transformations, offering adaptable and high-performance representations through fine-tuning.
Koorosh Roohi, Javad Rajabi, Andrew Fleet +1 authors
PhotoQuilt is a training-free framework that generates high-resolution photomosaics by combining global layout composition with separate tile generation in latent space, overcoming limitations of diffusion models in balancing local detail and global structure.
Paul S. Scotti, Atmadeep Banerjee, Jimmie Goode +9 authors
MindEye, a novel fMRI-to-image approach, retrieves and reconstructs viewed images with high accuracy using specialized submodules and diffusion prior in latent space.
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