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英文字典中文字典相关资料:


  • Qwen-VL: A Versatile Vision-Language Model for Understanding . . .
    In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images Starting from the Qwen-LM as a
  • Gated Attention for Large Language Models: Non-linearity, Sparsity,. . .
    The authors response that they will add experiments in QWen architecture, give the hyperparameters, and promise to open-source one of the models Reviewer bMKL is the only reviewer to initially score the paper in the negative region (Borderline reject) They have some doubts on the experimental section
  • Q -VL: A VERSATILE V M FOR UNDERSTANDING, L ING AND EYOND QWEN-VL: A . . .
    In this paper, we explore a way out and present the newest members of the open-sourced Qwen fam-ilies: Qwen-VL series Qwen-VLs are a series of highly performant and versatile vision-language foundation models based on Qwen-7B (Qwen, 2023) language model We empower the LLM base-ment with visual capacity by introducing a new visual receptor including a language-aligned visual encoder and a
  • SAM-Veteran: An MLLM-Based Human-like SAM Agent for Reasoning. . .
    For Qwen+SAM, we report the results of generating boxes for SAM For Seg-Zero, the MLLM outputs both the bounding boxes and the points for SAM in a single step, whereas SegAgent adopts a fixed number of 7 refinement iterations for mask prediction
  • Mamba-3: Improved Sequence Modeling using State Space Principles
    This submission introduces Mamba-3, an “inference-first” state-space linear-time sequence model that aims to improve over prior sub-quadratic backbones (notably Mamba-2 and Gated DeltaNet) along three dimensions: modeling quality, state-tracking capability, and real-world decode efficiency The core methodological contributions are: Generalized trapezoidal discretization to improve
  • TwinFlow: Realizing One-step Generation on Large Models with. . .
    Qwen-Image-Lightning is 1 step leader on the DPG benchmark and should be marked like this in Table 2 Distillation Fine Tuning vs Full training method: Qwen-Image-TwinFlow (and possibly also TwinFlow-0 6B and TwinFlow-1 6B, see question below) leverages a pretrained model that is fine-tuned
  • Zihan Qiu - OpenReview
    Zihan Qiu Researcher, Qwen Team, Alibaba Group Joined May 2022
  • LLaVA-OneVision: Easy Visual Task Transfer | OpenReview
    We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the LLaVA-NeXT blog series Our
  • VL-JEPA: Joint Embedding Predictive Architecture for Vision-language
    We introduce VL-JEPA, a vision-language model built on a Joint Embedding Predictive Architecture (JEPA) Instead of autoregressively generating tokens as in classical VLMs, VL-JEPA predicts
  • Junyang Lin - OpenReview
    Junyang Lin Principal Researcher, Qwen Team, Alibaba Group Joined July 2019





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