8 citations · 15 across the 15 of their papers we have counts for
15 papers
PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control
Jingxuan Wei, Xi Bai, Shan Liu +8
Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet these gains largely rely on a f…
How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning
Xiangxiang Zhang, Caijun Jia, Siyuan Li +9
Solving complex geometric problems inherently requires interleaved reasoning: a tight alternation between constructing diagrams and performing logical deductions. Although recent M…
Thinking with Drafting: Optical Decompression via Logical Reconstruction
Jingxuan Wei, Honghao He, Caijun Jia +9
Existing multimodal large language models have achieved high-fidelity visual perception and exploratory visual generation. However, a precision paradox persists in complex reasonin…
GGBench: A Geometric Generative Reasoning Benchmark for Unified Multimodal Models
Jingxuan Wei, Caijun Jia, Xi Bai +7
The advent of Unified Multimodal Models (UMMs) signals a paradigm shift in artificial intelligence, moving from passive perception to active, cross-modal generation. Despite their…
Geoint-R1: Formalizing Multimodal Geometric Reasoning with Dynamic Auxiliary Constructions
Jingxuan Wei, Caijun Jia, Qi Chen +6
Mathematical geometric reasoning is essential for scientific discovery and educational development, requiring precise logic and rigorous formal verification. While recent advances…
LLaVA-NeuMT: Selective Layer-Neuron Modulation for Efficient Multilingual Multimodal Translation
Jingxuan Wei, Caijun Jia, Qi Chen +5
Multimodal Machine Translation (MMT) enhances translation quality by incorporating visual context, helping to resolve textual ambiguities. While existing MMT methods perform well i…
From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing
Jingxuan Wei, Cheng Tan, Qi Chen +6
We introduce the task of text-to-diagram generation, which focuses on creating structured visual representations directly from textual descriptions. Existing approaches in text-to-…
Retrieval Meets Reasoning: Even High-school Textbook Knowledge Benefits Multimodal Reasoning
Cheng Tan, Jingxuan Wei, Linzhuang Sun +5
Large language models equipped with retrieval-augmented generation (RAG) represent a burgeoning field aimed at enhancing answering capabilities by leveraging external knowledge bas…
Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation
Jingxuan Wei, Linzhuang Sun, Yichong Leng +3
Knowledge distillation, transferring knowledge from a teacher model to a student model, has emerged as a powerful technique in neural machine translation for compressing models or…
Unraveling Key Factors of Knowledge Distillation
Jingxuan Wei, Linzhuang Sun, Xu Tan +2
Knowledge distillation, a technique for model compression and performance enhancement, has gained significant traction in Neural Machine Translation (NMT). However, existing resear…
Rational Sensibility: LLM Enhanced Empathetic Response Generation Guided by Self-presentation Theory
Linzhuang Sun, Yao Dong, Nan Xu +3
The development of Large Language Models (LLMs) provides human-centered Artificial General Intelligence (AGI) with a glimmer of hope. Empathy serves as a key emotional attribute of…
Brain-inspired Computing Based on Deep Learning for Human-computer Interaction: A Review
Bihui Yu, Sibo Zhang, Lili Zhou +3
The continuous development of artificial intelligence has a profound impact on biomedicine and other fields, providing new research ideas and technical methods. Brain-inspired comp…
Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training
Cheng Tan, Jingxuan Wei, Zhangyang Gao +5
Multimodal reasoning is a challenging task that requires models to reason across multiple modalities to answer questions. Existing approaches have made progress by incorporating la…
A Survey on Image-text Multimodal Models
Ruifeng Guo, Jingxuan Wei, Linzhuang Sun +7
With the significant advancements of Large Language Models (LLMs) in the field of Natural Language Processing (NLP), the development of image-text multimodal models has garnered wi…
Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework
Jingxuan Wei, Cheng Tan, Zhangyang Gao +5
Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks. While t…