ASAP: Automatic Semantic Alignment for Phrases

ASAP-II: From the Alignment of Phrases to Textual Similarity

ASAP: Advancing Semantic Alignment Promotes Multi-Modal Manipulation Detecting and Grounding

We present ASAP, a new framework for detecting and grounding multi-modal media manipulation (DGM4).Upon thorough examination, we observe that accurate fine-grained cross-modal semantic alignment between the image and tex…

Icing on the Cake: Automatic Code Summarization at Ericsson

This paper presents our findings on the automatic summarization of Java methods within Ericsson, a global telecommunications company. We evaluate the performance of an approach called Automatic Semantic Augmentation of P…

ASAP: Automated Sequence Planning for Complex Robotic Assembly with Physical Feasibility

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based plann…

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training

Learning transferable and interpretable representations from medical volumetric scans remains challenging due to complex anatomical structures and weak, heterogeneous supervision provided by radiology reports. In this pa…