7 accepted papers
Understanding mid-level road semantics, which capture the structural and contextual cues that link low-level perception to high-level planning, is essential for reliable autonomous driving and digital map construction. However, existing benchmarks primarily target perception tasks such as detection
Multiple-choice question answering (MCQA) requires the model to select the correct answer from a set of candidate options when given a passage and a question. Previous research has achieved promising results with the assistance of Pre-trained Language Models(PrLMs). However, it has been observed tha…
Mitigating linguistic bias and attaining modal equilibrium in Visual Question Answering (VQA) tasks constitute a pivotal concern. Previous work has mainly focused on data augmentation or a uni-modal approach, which is insufficient to fully utilize bi-modal information. In this work, we propose a new…
Cross-domain Relation Extraction aims to transfer knowledge from a source domain to a different target domain to address low-resource challenges. However, the semantic gap caused by data bias between domains is a major challenge, especially in few-shot scenarios. Previous work has mainly focused on…
Machine Reading Comprehension (MRC) is a challenging task in natural language understanding, especially multi-hop question answering (QA) in long texts. One of the challenges in multi-hop QA requires models to produce interpretable answers based on evidence that is selected from a given long text. B…
Humans are proficient at continuously acquiring and integrating new knowledge. By contrast, deep models forget catastrophically, especially when tackling highly long task sequences. Inspired by the way our brains constantly rewrite and consolidate past recollections, we propose a novel Bilateral Mem…
Multiple-choice question answering (MCQA) is a challenging task that requires selecting the correct answer from a set of options based on a given question. There is a trend to use pre-trained encoder-decoder models to solve MCQA. Previous works concentrate on the decoder and adopt the generated text…