From the 1 of 5 linked papers with an AI index.
5 papers
Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis
Wei Chen, Junkai Li, Tongguan Wang +4
The paper introduces SentiLLM, a framework that converts non‑verbal signals into text‑like semantic tokens using a dual‑stream salience‑context mechanism, enabling large language m…
PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling
Xudong Xie, Hao Yan, Liang Yin +6
Multimodal document understanding is a challenging task to process and comprehend large amounts of textual and visual information. Recent advances in Large Language Models (LLMs) h…
Beyond Words: Enhancing Desire, Emotion, and Sentiment Recognition with Non-Verbal Cues
Wei Chen, Tongguan Wang, Feiyue Xue +3
Multimodal desire understanding, a task closely related to both emotion and sentiment that aims to infer human intentions from visual and textual cues, is an emerging yet underexpl…
VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning
Hao Yan, Xingchen Liu, Hao Wang +11
Recent strides in multimodal large language models (MLLMs) have significantly advanced their performance in many reasoning tasks. However, Abstract Visual Reasoning (AVR) remains a…
OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning
Ling Fu, Zhebin Kuang, Jiajun Song +21
Scoring the Optical Character Recognition (OCR) capabilities of Large Multimodal Models (LMMs) has witnessed growing interest. Existing benchmarks have highlighted the impressive p…