J Wu, W Gan, Z Chen, S Wan, H Lin - arXiv preprint arXiv:2304.06632, 2023 - arxiv.org
To address the challenges of digital intelligence in the digital economy, artificial intelligence- generated content (AIGC) has emerged. AIGC uses artificial intelligence to assist or replace …
For machine reading comprehension, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy passages and getting ride of the noises is …
Multi-turn conversation understanding is a major challenge for building intelligent dialogue systems. This work focuses on retrieval-based response matching for multi-turn conversation …
L Feng, Q Li, Z Peng, S Tan… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Diverse and realistic traffic scenarios are crucial for evaluating the AI safety of autonomous driving systems in simulation. This work introduces a data-driven method called TrafficGen …
Z He, Z Wang, W Wei, S Feng, X Mao… - arXiv preprint arXiv …, 2020 - arxiv.org
Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, eg, part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc …
Head-driven phrase structure grammar (HPSG) enjoys a uniform formalism representing rich contextual syntactic and even semantic meanings. This paper makes the first attempt to …
Explainable artificial intelligence (XAI) tools are used to enhance the applications of existing artificial intelligence (AI) technologies by explaining their execution processes and results. In …
Attention mechanisms have improved the performance of NLP tasks while allowing models to remain explainable. Self-attention is currently widely used, however interpretability is …
Emotion-cause pair extraction is a recently proposed task that aims at extracting all potential clause-level pairs of emotion and cause in text. To solve this task, researchers first proposed …