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- 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
- Qwen2 Technical Report - OpenReview
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models We release a comprehensive suite of foundational and instruction-tuned
- 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
- LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation
Remarkably, LLaVA-MoD-2B surpasses Qwen-VL-Chat-7B with an average gain of 8 8\%, using merely $0 3\%$ of the training data and 23\% trainable parameters The results underscore LLaVA-MoD's ability to effectively distill comprehensive knowledge from its teacher model, paving the way for developing efficient MLLMs
- Qwen2. 5 Technical Report - OpenReview
In this report, we introduce Qwen2 5, a comprehensive series of large language models (LLMs) designed to meet diverse needs Compared to previous iterations, Qwen 2 5 has been significantly
- Junyang Lin - OpenReview
Junyang Lin Pronouns: he him Principal Researcher, Qwen Team, Alibaba Group Joined July 2019
- Alleviating Hallucination in Large Vision-Language Models with. . .
Despite the remarkable ability of large vision-language models (LVLMs) in image comprehension, these models frequently generate plausible yet factually incorrect responses, a phenomenon known as
- MedJourney: Benchmark and Evaluation of Large Language Models over . . .
A1: Thank you for your insightful suggestion In our manuscript, we evaluated several public large language models (LLMs) such as ChatGLM3 and QWen, as well as specialized LLMs like HuatuoGPT2 and DISC-MedLLM, which are primarily Chinese LLMs We fully acknowledge your point about the broader applicability of our benchmark
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