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Jihao Wu

8 accepted papers

2026

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

CVPR 2026

Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document length increases. This stems from two fundamental challenges: 1) a low Signal-to-Noise Ratio (SNR), with crucial evidence buried in irrelevant pages;

Cited by 4SourcecodeScholar
2026

MMSearch-Plus: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents

ICLR 2026poster

Existing multimodal browsing benchmarks often fail to require genuine multimodal reasoning, as many tasks can be solved with text-only heuristics without vision-in-the-loop verification. We introduce MMSearch-Plus, a 311-task benchmark that enforces multimodal understanding by requiring extraction a…

Cited by 0SourcecodeScholar
2026

VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning

ICLR 2026poster

Recent strides in multimodal large language models (MLLMs) have demonstrated significant progress in many reasoning tasks, but they still fail in Abstract Visual Reasoning (AVR) tasks. Our experimental findings indicate that the core bottleneck lies not only in the reasoning capabilities of MLLMs bu…

Cited by 0SourcecodeScholar
2025

Cross-Lingual Text-Rich Visual Comprehension: An Information Theory Perspective

AAAI 2025technical

Recent Large Vision-Language Models (LVLMs) have shown promising reasoning capabilities on text-rich images from charts, tables, and documents. However, the abundant text within such images may increase the model's sensitivity to language. This raises the need to evaluate LVLM performance on cross-…

2025

UI-Hawk: Unleashing the Screen Stream Understanding for Mobile GUI Agents

EMNLP 2025

Graphical User Interface (GUI) agents are expected to precisely operate on the screens of digital devices. Existing GUI agents merely depend on current visual observations and plain-text action history, ignoring the significance of history screens. To mitigate this issue, we propose **UI-Hawk**, a m

2024

Android in the Zoo: Chain-of-Action-Thought for GUI Agents

EMNLP 2024finding

Large language model (LLM) leads to a surge of autonomous GUI agents for smartphone, which completes a task triggered by natural language through predicting a sequence of actions of API. Even though the task highly relies on past actions and visual observations, existing studies typically consider l…

2023

Efficient Image Captioning for Edge Devices

AAAI 2023technical

Recent years have witnessed the rapid progress of image captioning. However, the demands for large memory storage and heavy computational burden prevent these captioning models from being deployed on mobile devices. The main obstacles lie in the heavyweight visual feature extractors (i.e., object de…

Cited by 22SourcePDFScholar