activity
20222025
most citedQwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

149 citations · 475 across the 14 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.CL2023★ 110 cited

Qwen Technical Report

Jinze Bai, Shuai Bai, Yunfei Chu +45

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…

cs.CL2023★ 9 cited

Scaling Relationship on Learning Mathematical Reasoning with Large Language Models

Zheng Yuan, Hongyi Yuan, Chengpeng Li +5

Mathematical reasoning is a challenging task for large language models (LLMs), while the scaling relationship of it with respect to LLM capacity is under-explored. In this paper, w…

cs.CV2023★ 7 cited

TouchStone: Evaluating Vision-Language Models by Language Models

Shuai Bai, Shusheng Yang, Jinze Bai +6

Large vision-language models (LVLMs) have recently witnessed rapid advancements, exhibiting a remarkable capacity for perceiving, understanding, and processing visual information b…

cs.CL2023★ 13 cited

#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models

Keming Lu, Hongyi Yuan, Zheng Yuan +5

Foundation language models obtain the instruction-following ability through supervised fine-tuning (SFT). Diversity and complexity are considered critical factors of a successful S…

cs.CV2023★ 149 cited

Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Jinze Bai, Shuai Bai, Shusheng Yang +6

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…

cs.CV2023★ 42 cited

ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities

Peng Wang, Shijie Wang, Junyang Lin +5

In this work, we explore a scalable way for building a general representation model toward unlimited modalities. We release ONE-PEACE, a highly extensible model with 4B parameters…

cs.CL2023★ 56 cited

ExpertPrompting: Instructing Large Language Models to be Distinguished Experts

Benfeng Xu, An Yang, Junyang Lin +4

The answering quality of an aligned large language model (LLM) can be drastically improved if treated with proper crafting of prompts. In this paper, we propose ExpertPrompting to…