Qwen Mtqwen Mt Turbo

qwen mtqwen mt turbo represents a topic that has garnered significant attention and interest. 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... Q -VL: A VERSATILE V M FOR UNDERSTANDING, L ING AND EYOND QWEN-VL: A ....

(iii) 3-stage training pipeline, and (iv) multilingual multimodal cleaned corpus. Beyond the conventional image description and question-answering, we imple-ment the grounding and text-reading ability of Qwen-VLs by aligning image-caption-box tuples. The resulting models, including Qwen-VL and Qwen-VL-Chat, set new records for generalist models under similar model scales on a broad range of ...

You Know What I'm Saying: Jailbreak Attack via Implicit Reference. It's important to note that, the results indicate a significant increase in ASR across all models, from Qwen-2 0.5 to 72B. Another key aspect involves, (The smaller change in ASR is due to the target model's instruction understanding capability being close to that of GPT-4o, reducing the impact of GPT-4o) W2 The distinguishment between AIR and multi-turn attack is unclear. Towards Federated RLHF with Aggregated Client Preference for LLMs. Reinforcement learning with human feedback (RLHF) fine-tunes a pretrained large language model (LLM) using user preference data, enabling it to generate content aligned with human preferences.... From another angle, aDIFF: Explaining audio difference using natural language.

We evaluate our model using objective metrics and human evaluation and show our model enhancements lead to significant improvements in performance over naive baseline and SoTA Audio-Language Model (ALM) Qwen Audio. Junyang Lin - OpenReview. This perspective suggests that, junyang Lin Pronouns: he/him Principal Researcher, Qwen Team, Alibaba Group Joined July 2019

MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context .... We have added evaluations for Mistral and Qwen series models to show the trends seen for Llama models also translate to the former (Appendix A.5, Page 15). MagicDec achieves impressive speedups for Mistral-7B-v0.3, Qwen-2.5-7B and Qwen2.5-32B even at large batch sizes

Exchange of Perspective Prompting Enhances Reasoning in Large.... Equally important, large language models (LLMs) have made significant advancements in addressing diverse natural language processing (NLP) tasks. However, their performance is often limited by inherent comprehension... Retraining-Free Merging of Sparse Mixture-of-Experts via.... TL;DR: Our method (HC-SMoE) offers an efficient method for merging experts of large Sparse Activated Mixture of Experts (SMoE) models without retraining under task-agnostic settings.

Additionally, liveVQA: Assessing Models with Live Visual Knowledge. We introduce LiveVQA, an automatically collected dataset of latest visual knowledge from the Internet with synthesized VQA problems. LiveVQA consists of 3,602 single- and multi-hop visual questions from 6 news websites across 14 news categories, featuring high-quality image-text coherence and authentic information.

Additionally, our evaluation across 15 MLLMs (e.g., GPT-4o, Gemma-3, and Qwen-2.5-VL family ...