activity
20232025
most citedmPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

50 citations · 221 across the 40 of their papers we have counts for

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Showing cs.CLShow all

14 papers · 1 filter

cs.CL2025

Tongyi DeepResearch Technical Report

Tongyi DeepResearch Team, Baixuan Li, Bo Zhang +54

We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous…

cs.CL2025

Perception-Aware Policy Optimization for Multimodal Reasoning

Zhenhailong Wang, Xuehang Guo, Sofia Stoica +8

Reinforcement Learning with Verifiable Rewards (RLVR) has proven to be a highly effective strategy for endowing Large Language Models (LLMs) with robust multi-step reasoning abilit…

cs.CL2025

SoLoPO: Unlocking Long-Context Capabilities in LLMs via Short-to-Long Preference Optimization

Huashan Sun, Shengyi Liao, Yansen Han +8

Despite advances in pretraining with extended context sizes, large language models (LLMs) still face challenges in effectively utilizing real-world long-context information, primar…

cs.CL2025★ 3 cited

Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks

Zhenhailong Wang, Haiyang Xu, Junyang Wang +5

Smartphones have become indispensable in modern life, yet navigating complex tasks on mobile devices often remains frustrating. Recent advancements in large multimodal model (LMM)-…

cs.CL2024

MaVEn: An Effective Multi-granularity Hybrid Visual Encoding Framework for Multimodal Large Language Model

Chaoya Jiang, Jia Hongrui, Haiyang Xu +6

This paper presents MaVEn, an innovative Multi-granularity Visual Encoding framework designed to enhance the capabilities of Multimodal Large Language Models (MLLMs) in multi-image…

cs.CL2024

ProFuser: Progressive Fusion of Large Language Models

Tianyuan Shi, Fanqi Wan, Canbin Huang +6

While fusing the capacities and advantages of various large language models offers a pathway to construct more powerful and versatile models, a fundamental challenge is to properly…

cs.CL2024★ 4 cited

SocialBench: Sociality Evaluation of Role-Playing Conversational Agents

Hongzhan Chen, Hehong Chen, Ming Yan +8

Large language models (LLMs) have advanced the development of various AI conversational agents, including role-playing conversational agents that mimic diverse characters and human…

cs.CL2024★ 13 cited

Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception

Junyang Wang, Haiyang Xu, Jiabo Ye +5

Mobile device agent based on Multimodal Large Language Models (MLLM) is becoming a popular application. In this paper, we introduce Mobile-Agent, an autonomous multi-modal mobile d…

cs.CL2023★ 29 cited

mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

Qinghao Ye, Haiyang Xu, Jiabo Ye +7

Multi-modal Large Language Models (MLLMs) have demonstrated impressive instruction abilities across various open-ended tasks. However, previous methods primarily focus on enhancing…

cs.CL2023★ 1 cited

ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

Chenliang Li, Hehong Chen, Ming Yan +11

Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further u…

cs.CL2023★ 13 cited

CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility

Guohai Xu, Jiayi Liu, Ming Yan +11

With the rapid evolution of large language models (LLMs), there is a growing concern that they may pose risks or have negative social impacts. Therefore, evaluation of human values…

cs.CL2023★ 17 cited

mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding

Jiabo Ye, Anwen Hu, Haiyang Xu +10

Document understanding refers to automatically extract, analyze and comprehend information from various types of digital documents, such as a web page. Existing Multi-model Large L…

cs.CL2023★ 2 cited

Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering

Qianglong Chen, Guohai Xu, Ming Yan +4

Existing knowledge-enhanced methods have achieved remarkable results in certain QA tasks via obtaining diverse knowledge from different knowledge bases. However, limited by the pro…

cs.CL2023★ 3 cited

ChatPLUG: Open-Domain Generative Dialogue System with Internet-Augmented Instruction Tuning for Digital Human

Junfeng Tian, Hehong Chen, Guohai Xu +14

In this paper, we present ChatPLUG, a Chinese open-domain dialogue system for digital human applications that instruction finetunes on a wide range of dialogue tasks in a unified i…