3 accepted papers
The past few years have witnessed the immense development of small object detection, which is aimed at detecting size-limited targets in high-resolution images. The prevailing methods focus on extracting fine-grained information by expanding the receptive fields and then generating the potential sma…
In federated learning (FL), multiple clients train a global model by sharing gradients. Since the client data remains locally, federated learning is considered privacy-safe. Although previous studies have demonstrated the feasibility of recovering client data from shared gradients, most studies assu…
Multi-hop question answering (QA) requires reasoning over multiple documents to answer a complex question and provide interpretable supporting evidence. However, providing supporting evidence is not enough to demonstrate that a model has performed the desired reasoning to reach the correct answer. M…