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From the 1 of 19 linked papers with an AI index.

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20242026
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cs.AI2025

ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning

Zhengzhuo Xu, SiNan Du, Yiyan Qi +4

Multimodal Large Language Models (MLLMs) have emerged as powerful tools for chart comprehension. However, they heavily rely on extracted content via OCR, which leads to numerical h…

cs.AI2025

Retrieval, Reasoning, Re-ranking: A Context-Enriched Framework for Knowledge Graph Completion

Muzhi Li, Cehao Yang, Chengjin Xu +5

The Knowledge Graph Completion~(KGC) task aims to infer the missing entity from an incomplete triple. Existing embedding-based methods rely solely on triples in the KG, which is vu…

cs.AI2025

ChartMoE: Mixture of Diversely Aligned Expert Connector for Chart Understanding

Zhengzhuo Xu, Bowen Qu, Yiyan Qi +4

Automatic chart understanding is crucial for content comprehension and document parsing. Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in chart…

cs.AI2024

MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Zhanpeng Chen, Chengjin Xu, Yiyan Qi +1

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in processing and generating content across multiple data modalities. However, a significant draw…

cs.AI2024

Context Graph

Chengjin Xu, Muzhi Li, Cehao Yang +4

Knowledge Graphs (KGs) are foundational structures in many AI applications, representing entities and their interrelations through triples. However, triple-based KGs lack the conte…