activity
20232026
most citedA Survey on Image-text Multimodal Models

8 citations · 22 across the 40 of their papers we have counts for

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14 papers · 1 filter

cs.AI2026

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…

cs.AI2026

NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation

Jinhang Xu, Qiyuan Zhu, Yujun Wu +11

LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automation for whom? Researchers ope…

cs.AI2026

PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents

Bihui Yu, Xinglong Xu, Junjie Jiang +6

A LaTeX manuscript that compiles without error is not necessarily publication-ready. The resulting PDFs frequently suffer from misplaced floats, overflowing equations, inconsistent…

cs.AI2026

Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

Yujun Wu, Dongxu Zhang, Xinchen Li +11

Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In par…

cs.AI2026

The Trinity of Consistency as a Defining Principle for General World Models

Jingxuan Wei, Siyuan Li, Yuhang Xu +21

The construction of World Models capable of learning, simulating, and reasoning about objective physical laws constitutes a foundational challenge in the pursuit of Artificial Gene…

cs.AI2025

Decouple to Generalize: Context-First Self-Evolving Learning for Data-Scarce Vision-Language Reasoning

Tingyu Li, Zheng Sun, Jingxuan Wei +4

Recent vision-language models (VLMs) achieve remarkable reasoning through reinforcement learning (RL), which provides a feasible solution for realizing continuous self-evolving lar…

cs.AI2025

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…

cs.AI2025

StructVRM: Aligning Multimodal Reasoning with Structured and Verifiable Reward Models

Xiangxiang Zhang, Jingxuan Wei, Donghong Zhong +31

Existing Vision-Language Models often struggle with complex, multi-question reasoning tasks where partial correctness is crucial for effective learning. Traditional reward mechanis…

cs.AI2025

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…

cs.AI2025

SketchAgent: Generating Structured Diagrams from Hand-Drawn Sketches

Cheng Tan, Qi Chen, Jingxuan Wei +6

Hand-drawn sketches are a natural and efficient medium for capturing and conveying ideas. Despite significant advancements in controllable natural image generation, translating fre…

cs.AI2023★ 1 cited

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…

cs.AI2023★ 5 cited

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…

cs.AI2023

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…

cs.AI2023★ 1 cited

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…