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20202026
most citedMol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models

40 citations · 200 across the 45 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Learnable Token Sparsification for Efficient Gigapixel Whole Slide Image Reasoning

Jingzhi Chen, Landi He, Zhuo Chen +2

The processing of gigapixel whole slide images within vision language models faces a major difficulty due to an excessive number of visual tokens. Existing solutions typically rely…

cs.CV2025

Abstractive Visual Understanding of Multi-modal Structured Knowledge: A New Perspective for MLLM Evaluation

Yichi Zhang, Zhuo Chen, Lingbing Guo +4

Multi-modal large language models (MLLMs) incorporate heterogeneous modalities into LLMs, enabling a comprehensive understanding of diverse scenarios and objects. Despite the proli…

cs.CV2022★ 2 cited

Target-oriented Sentiment Classification with Sequential Cross-modal Semantic Graph

Yufeng Huang, Zhuo Chen, Jiaoyan Chen +3

Multi-modal aspect-based sentiment classification (MABSC) is task of classifying the sentiment of a target entity mentioned in a sentence and an image. However, previous methods fa…

cs.CV2022★ 1 cited

LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection

Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5

Visual question answering (VQA) often requires an understanding of visual concepts and language semantics, which relies on external knowledge. Most existing methods exploit pre-tra…

cs.CV2022★ 3 cited

DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning

Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5

Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training. One of the most effective and widely used semantic information for zero-s…

cs.CV2020★ 12 cited

Generative Adversarial Zero-shot Learning via Knowledge Graphs

Yuxia Geng, Jiaoyan Chen, Zhuo Chen +4

Zero-shot learning (ZSL) is to handle the prediction of those unseen classes that have no labeled training data. Recently, generative methods like Generative Adversarial Networks (…