activity
20242026
most citedToken-level Correlation-guided Compression for Efficient Multimodal Document Understanding

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

collaborators

5 papers

cs.CV2026

Fuzzy-Geometric Branch-Point Modeling for Structure-Aware Augmentation of Handwritten Chinese Characters

Dongbin Jiao, Yibo Lyu, Qiulu Wei +3

Data scarcity and structural distortion significantly limit handwriting recognition in high-security authentication. Existing augmentation methods often cause topological and morph…

cs.LG2026

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning

Zhanyue Qin, Jia Feng, Yibo Lyu +4

Code reasoning refers to the task of predicting the output of a program given its source code and specific inputs. It can measure the reasoning capability of large language models…

cs.AI2026

PersonalAlign: Hierarchical Implicit Intent Alignment for Personalized GUI Agent with Long-Term User-Centric Records

Yibo Lyu, Gongwei Chen, Rui Shao +2

While GUI agents have shown strong performance under explicit and completion instructions, real-world deployment requires aligning with users' more complex implicit intents. In thi…

cs.MM2025

PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning

Yibo Lyu, Rui Shao, Gongwei Chen +3

As multimedia content expands, the demand for unified multimodal retrieval (UMR) in real-world applications increases. Recent work leverages multimodal large language models (MLLMs…

cs.CV20242 cited

Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding

Renshan Zhang, Yibo Lyu, Rui Shao +3

Cropping high-resolution document images into multiple sub-images is the most widely used approach for current Multimodal Large Language Models (MLLMs) to do document understanding…