11 citations · 12 across the 9 of their papers we have counts for
10 papers
Dolphin-v2: Universal Document Parsing via Scalable Anchor Prompting
Hao Feng, Wei Shi, Ke Zhang +9
Document parsing has garnered widespread attention as vision-language models (VLMs) advance OCR capabilities. However, the field remains fragmented across dozens of specialized mod…
Revis: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
Jialin Wu, Wei Shi, Han Shen +5
Despite the advanced capabilities of Large Vision-Language Models (LVLMs), they frequently suffer from object hallucination. One reason is that visual features and pretrained textu…
UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters
Yongkun Du, Zhineng Chen, Yazhen Xie +6
Text and formulas constitute the core informational components of many documents. Accurately and efficiently recognizing both is crucial for developing robust and generalizable doc…
Post-Completion Learning for Language Models
Xiang Fei, Siqi Wang, Shu Wei +5
Current language model training paradigms typically terminate learning upon reaching the end-of-sequence (<eos>) token, overlooking the potential learning opportunities in the post…
Advancing Sequential Numerical Prediction in Autoregressive Models
Xiang Fei, Jinghui Lu, Qi Sun +6
Autoregressive models have become the de facto choice for sequence generation tasks, but standard approaches treat digits as independent tokens and apply cross-entropy loss, overlo…
Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting
Hao Feng, Shu Wei, Xiang Fei +10
Document image parsing is challenging due to its complexly intertwined elements such as text paragraphs, figures, formulas, and tables. Current approaches either assemble specializ…
MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark
Bin Shan, Xiang Fei, Wei Shi +6
The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchma…
ParGo: Bridging Vision-Language with Partial and Global Views
An-Lan Wang, Bin Shan, Wei Shi +7
This work presents ParGo, a novel Partial-Global projector designed to connect the vision and language modalities for Multimodal Large Language Models (MLLMs). Unlike previous work…
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Jingqun Tang, Chunhui Lin, Zhen Zhao +15
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of lea…
Gecko: Versatile Text Embeddings Distilled from Large Language Models
Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren +17
We present Gecko, a compact and versatile text embedding model. Gecko achieves strong retrieval performance by leveraging a key idea: distilling knowledge from large language model…