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。
MiniMax, Aonian Li, Bangwei Gong +87 authors
The MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01, offer superior long-context processing and match state-of-the-art model performance with longer context windows through lightning attention, Mixture of Experts (MoE), and efficient parallel strategies.
Wenyi Hong, Wenmeng Yu, Xiaotao Gu +74 authors
A vision-language model (VLM) named GLM-4.1V-Thinking, developed with a reasoning-centric training framework, achieves state-of-the-art performance across various tasks, including STEM problem solving, video understanding, and long document understanding, outperforming larger models on many benchmarks.
Weihao Tan, Xiangyang Li, Yunhao Fang +11 authors
Lumine, a vision-language model-based agent, completes complex missions in real-time across different 3D open-world environments with human-like efficiency and zero-shot cross-game generalization.
Dingyu Yao, Junhao Zhou, Chenxu Yang +12 authors
A vision-language model operates continuously in real-time, making autonomous decisions about when to respond or delegate, enabling interactive systems that perceive and act upon environmental changes without user prompting.
Junbo Niu, Zheng Liu, Zhuangcheng Gu +58 authors
MinerU2.5, a 1.2B-parameter document parsing vision-language model, achieves state-of-the-art recognition accuracy with computational efficiency through a coarse-to-fine parsing strategy.
Yuxiang Ji, Yong Wang, Ziyu Ma +6 authors
Large vision-language models are enhanced for image geolocalization by incorporating map-based reasoning and agent-in-the-map loop optimization, achieving superior accuracy compared to existing models.
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61 authors
Qwen3-VL, a vision-language model, excels in text and multimodal understanding through advanced architectures and larger contexts, achieving superior performance across benchmarks.
Ahmed Nassar, Andres Marafioti, Matteo Omenetti +10 authors
SmolDocling is a compact vision-language model that performs end-to-end document conversion with robust performance across various document types using 256M parameters and a new markup format.
Keyu Tu, Zhuowei Chen, Mengqi Huang +4 authors
Semantic task completion video generation evaluates whether generated videos achieve intended outcomes with semantic grounding, supported by a curated dataset and vision-language model-based benchmark.
Daxiang Dong, Mingming Zheng, Dong Xu +17 authors
Qianfan-OCR is a 4B-parameter vision-language model that unifies document parsing, layout analysis, and understanding while maintaining strong performance across multiple OCR benchmarks through its Layout-as-Thought mechanism.
Yu Wang, Yi Wang, Rui Dai +4 authors
Urban socio-semantic segmentation is achieved through a vision-language model framework that combines cross-modal recognition and multi-stage reasoning with reinforcement learning optimization.
Khalil Hennara, Muhammad Hreden, Mohamed Motasim Hamed +4 authors
Baseer, a vision-language model fine-tuned for Arabic document OCR, achieves state-of-the-art performance using a decoder-only strategy and a large-scale dataset, outperforming existing solutions with a WER of 0.25.
Cheng Cui, Ting Sun, Suyin Liang +15 authors
PaddleOCR-VL, a vision-language model combining NaViT-style dynamic resolution and ERNIE, achieves state-of-the-art performance in document parsing and element recognition with high efficiency.
Wei Shen, Jiangbo Pei, Yi Peng +7 authors
Skywork-R1V3, an open-source vision-language model, enhances visual reasoning through a post-training reinforcement learning framework, achieving state-of-the-art performance on multimodal reasoning tasks.
Yang Shen, Xiu-Shen Wei, Yifan Sun +6 authors
An auto-regressive vision-language model trained with explanatory instructions achieves instruction-level zero-shot capabilities and strong zero-shot generalization in computer vision tasks.
Lucas Beyer, Andreas Steiner, André Susano Pinto +32 authors
PaliGemma, a versatile Vision-Language Model based on SigLIP-So400m and Gemma-2B, demonstrates strong performance across numerous open-world tasks, including specialized areas like remote sensing and segmentation.
Sambal Shikhar, Mohammed Irfan Kurpath, Sahal Shaji Mullappilly +5 authors
LLMVoX is a lightweight, LLM-agnostic TTS system that decouples speech synthesis from model processing, ensuring high-quality speech with low latency and supporting seamless multimodal dialogue.
Haoqi Yuan, Yu Bai, Yuhui Fu +6 authors
Being-0, a hierarchical framework integrating Foundation Models with a modular skill library and a lightweight vision-language model, achieves efficient real-time performance on complex humanoid robot tasks by coordinating high-level cognition with low-level control.
Junsong Chen, Jincheng Yu, Chongjian Ge +8 authors
PIXART-$\alpha$ is a Transformer-based text-to-image diffusion model that achieves high-quality image synthesis with low training costs using advanced training strategies and efficient architecture.
Xiaoyi Dong, Pan Zhang, Yuhang Zang +20 authors
InternLM-XComposer2, a vision-language model, excels in free-form text-image creation and understanding using Partial LoRA, surpassing existing models and matching GPT-4V and Gemini Pro in multimodal benchmarks.
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