5 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
In-Context Compositional Learning via Sparse Coding Transformer
Wei Chen, Jingxi Yu, Zichen Miao +1
Transformer architectures have achieved remarkable success across language, vision, and multimodal tasks, and there is growing demand for them to address in-context compositional l…
TALENT: Table VQA via Augmented Language-Enhanced Natural-text Transcription
Guo Yutong, Wanying Wang, Yue Wu +2
Table Visual Question Answering (Table VQA) is typically addressed by large vision-language models (VLMs). While such models can answer directly from images, they often miss fine-g…
Sparse Fine-Tuning of Transformers for Generative Tasks
Wei Chen, Jingxi Yu, Zichen Miao +1
Large pre-trained transformers have revolutionized artificial intelligence across various domains, and fine-tuning remains the dominant approach for adapting these models to downst…
DiffOG: Differentiable Policy Trajectory Optimization with Generalizability
Zhengtong Xu, Zichen Miao, Qiang Qiu +2
Imitation learning-based visuomotor policies excel at manipulation tasks but often produce suboptimal action trajectories compared to model-based methods. Directly mapping camera d…
Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models
Zichen Miao, Wei Chen, Qiang Qiu
Transformer-based large pre-trained models have shown remarkable generalization ability, and various parameter-efficient fine-tuning (PEFT) methods have been proposed to customize…