activity
20242026
most citedA Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers

6 citations · 14 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning

Fanhu Zeng, Zhicong Luo, Zefan Wang +3

Visual reasoning through reinforcement learning with verifiable rewards (RLVR) has achieved remarkable progress. However, when dealing with multi-source inputs, existing approaches…

cs.CL2026★ 1 cited

MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction

Junbo Cui, Bokai Xu, Chongyi Wang +33

Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming interaction, yet they still remai…

cs.CL2026

Imagination Helps Visual Reasoning, But Not Yet in Latent Space

You Li, Chi Chen, Yanghao Li +4

Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While recognized as a promising paradigm…

cs.CL2025

Think in Safety: Unveiling and Mitigating Safety Alignment Collapse in Multimodal Large Reasoning Model

Xinyue Lou, You Li, Jinan Xu +3

The rapid development of Multimodal Large Reasoning Models (MLRMs) has demonstrated broad application potential, yet their safety and reliability remain critical concerns that requ…

cs.AI2025★ 1 cited

OmniGeo: Towards a Multimodal Large Language Models for Geospatial Artificial Intelligence

Long Yuan, Fengran Mo, Kaiyu Huang +6

The rapid advancement of multimodal large language models (LLMs) has opened new frontiers in artificial intelligence, enabling the integration of diverse large-scale data types suc…

cs.CL2025

Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models

You Li, Heyu Huang, Chi Chen +8

The recent advancement of Multimodal Large Language Models (MLLMs) has significantly improved their fine-grained perception of single images and general comprehension across multip…

cs.RO2024★ 3 cited

Touch100k: A Large-Scale Touch-Language-Vision Dataset for Touch-Centric Multimodal Representation

Ning Cheng, Changhao Guan, Jing Gao +7

Touch holds a pivotal position in enhancing the perceptual and interactive capabilities of both humans and robots. Despite its significance, current tactile research mainly focuses…

cs.CL2024★ 6 cited

A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers

Kaiyu Huang, Fengran Mo, Xinyu Zhang +10

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia…

cs.CV2024★ 3 cited

Towards Comprehensive Multimodal Perception: Introducing the Touch-Language-Vision Dataset

Ning Cheng, You Li, Jing Gao +3

Tactility provides crucial support and enhancement for the perception and interaction capabilities of both humans and robots. Nevertheless, the multimodal research related to touch…