activity
20242026
most citedA Survey on Agentic Multimodal Large Language Models

1 citations · 1 across the 7 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.CV2025★ 1 cited

A Survey on Agentic Multimodal Large Language Models

Huanjin Yao, Ruifei Zhang, Jiaxing Huang +8

With the recent emergence of revolutionary autonomous agentic systems, research community is witnessing a significant shift from traditional static, passive, and domain-specific AI…

cs.AI2025

UltraHorizon: Benchmarking Agent Capabilities in Ultra Long-Horizon Scenarios

Haotian Luo, Huaisong Zhang, Xuelin Zhang +15

Autonomous agents have recently achieved remarkable progress across diverse domains, yet most evaluations focus on short-horizon, fully observable tasks. In contrast, many critical…

cs.CV2025

R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO

Huanjin Yao, Qixiang Yin, Jingyi Zhang +8

In this work, we aim to incentivize the reasoning ability of Multimodal Large Language Models (MLLMs) via reinforcement learning (RL) and develop an effective approach that mitigat…

cs.AI2025

Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization

Haotian Luo, Haiying He, Yibo Wang +6

Recently, long-thought reasoning models achieve strong performance on complex reasoning tasks, but often incur substantial inference overhead, making efficiency a critical concern.…

cs.CL2025

R1-Compress: Long Chain-of-Thought Compression via Chunk Compression and Search

Yibo Wang, Haotian Luo, Huanjin Yao +8

Chain-of-Thought (CoT) reasoning enhances large language models (LLMs) by enabling step-by-step problem-solving, yet its extension to Long-CoT introduces substantial computational…

cs.CL2025

O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning

Haotian Luo, Li Shen, Haiying He +6

Recently, long-thought reasoning LLMs, such as OpenAI's O1, adopt extended reasoning processes similar to how humans ponder over complex problems. This reasoning paradigm significa…

cs.CL2025

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation

Yibo Wang, Tiansheng Huang, Li Shen +6

Harmful fine-tuning attack introduces significant security risks to the fine-tuning services. Main-stream defenses aim to vaccinate the model such that the later harmful fine-tunin…