MRHF: Multi-stage Retrieval and Hierarchical Fusion for Textbook Question Answering

Textbook question answering is challenging as it aims to automatically answer various questions on textbook lessons with long text and complex diagrams, requiring reasoning across modalities. In this work, we propose MRHF, a novel framework that incorporates dense passage re-ranking and the mixture-of-experts architecture for TQA. MRHF...

FedNaWi: Selecting the Befitting Clients for Robust Federated Learning in IoT Applications

Federated Learning (FL) is an important privacy-preserving learning paradigm that is expected to play an essential role in the future Intelligent Internet of Things (IoT). However, model training in FL is vulnerable to noise and the statistical heterogeneity of local data across IoT clients. In this paper, we propose FedNaWi, a “Go Narrow, Then...

Answer Quality Aware Aggregation for Extractive QA Crowdsourcing

Quality control is essential for creating extractive question answering (EQA) datasets via crowdsourcing. Aggregation across answers, i.e. word spans within passages annotated, by different crowd workers is one major focus for ensuring its quality. However, crowd workers cannot reach a consensus on a considerable portion of questions. We...

Advances in chloride diffusion of concrete exposed to marine field environment

For elaborating the research significance, goal, content and representative results of the concrete marine field exposure experiments all over the world, we have collected a large number of research literature since 1905. The longest exposure test for concrete has reached 62 years and, most importantly, concrete exposure experiments have made...