activity
20242026
most citedLongDocURL: a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating

1 citations · 2 across the 11 of their papers we have counts for

collaborators

14 papers

cs.LG2026

Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon

Sifan Yang, Hongyi Tao, Dingzhi Yu +5

Memory-efficient subspace optimization has emerged as a practical approach to reducing the memory cost of LLM training while preserving optimization performance. Previous algorithm…

cs.CV2026

Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal Language

Peijie Wang, Ming-Liang Zhang, Jun Cao +10

Multimodal Large Language Models (MLLMs) have achieved remarkable progress but continue to struggle with geometric reasoning, primarily due to the perception bottleneck regarding f…

cs.CV2026

SecAgent: Efficient Mobile GUI Agent with Semantic Context

Yiping Xie, Song Chen, Jingxuan Xing +7

Mobile Graphical User Interface (GUI) agents powered by multimodal large language models have demonstrated promising capabilities in automating complex smartphone tasks. However, e…

cs.AI2026

How Foundational Skills Influence VLM-based Embodied Agents:A Native Perspective

Bo Peng, Pi Bu, Keyu Pan +7

Recent advances in vision-language models (VLMs) have shown promise for human-level embodied intelligence. However, existing benchmarks for VLM-driven embodied agents often rely on…

cs.CV2025

AndroidLens: Long-latency Evaluation with Nested Sub-targets for Android GUI Agents

Yue Cao, Yingyao Wang, Pi Bu +10

Graphical user interface (GUI) agents can substantially improve productivity by automating frequently executed long-latency tasks on mobile devices. However, existing evaluation be…

cs.CV2025

Visual-CoG: Stage-Aware Reinforcement Learning with Chain of Guidance for Text-to-Image Generation

Yaqi Li, Peng Chen, Mingyang Han +7

Despite the promising progress of recent autoregressive models in text-to-image (T2I) generation, their ability to handle multi-attribute and ambiguous prompts remains limited. To…

cs.AI2025

DeepPHY: Benchmarking Agentic VLMs on Physical Reasoning

Xinrun Xu, Pi Bu, Ye Wang +7

Although Vision Language Models (VLMs) exhibit strong perceptual abilities and impressive visual reasoning, they struggle with attention to detail and precise action planning in co…

cs.AI2025

InquireMobile: Teaching VLM-based Mobile Agent to Request Human Assistance via Reinforcement Fine-Tuning

Qihang Ai, Pi Bu, Yue Cao +8

Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on human instructions. However, the c…

cs.AI2025

Mobile-R1: Towards Interactive Capability for VLM-Based Mobile Agent via Systematic Training

Jihao Gu, Qihang Ai, Yingyao Wang +10

Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinforcement learning paradigms like G…

cs.CV2025

CombatVLA: An Efficient Vision-Language-Action Model for Combat Tasks in 3D Action Role-Playing Games

Peng Chen, Pi Bu, Yingyao Wang +9

Recent advances in Vision-Language-Action models (VLAs) have expanded the capabilities of embodied intelligence. However, significant challenges remain in real-time decision-making…

cs.CL2025

"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models

Jihao Gu, Yingyao Wang, Pi Bu +17

The evaluation of factual accuracy in large vision language models (LVLMs) has lagged behind their rapid development, making it challenging to fully reflect these models' knowledge…

cs.AI2024★ 1 cited

LongDocURL: a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating

Chao Deng, Jiale Yuan, Pi Bu +8

Large vision language models (LVLMs) have improved the document understanding capabilities remarkably, enabling the handling of complex document elements, longer contexts, and a wi…

cs.CV2024

Token Preference Optimization with Self-Calibrated Visual-Anchored Rewards for Hallucination Mitigation

Jihao Gu, Yingyao Wang, Meng Cao +5

Direct Preference Optimization (DPO) has been demonstrated to be highly effective in mitigating hallucinations in Large Vision Language Models (LVLMs) by aligning their outputs mor…

cs.AI2024★ 1 cited

Can VLMs Play Action Role-Playing Games? Take Black Myth Wukong as a Study Case

Peng Chen, Pi Bu, Jun Song +2

Recently, large language model (LLM)-based agents have made significant advances across various fields. One of the most popular research areas involves applying these agents to vid…