Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Long, Siqu"'
Extracting meaningful drug-related information chunks, such as adverse drug events (ADE), is crucial for preventing morbidity and saving many lives. Most ADEs are reported via an unstructured conversation with the medical context, so applying a gener
Externí odkaz:
http://arxiv.org/abs/2308.06546
Natural language understanding typically maps single utterances to a dual level semantic frame, sentence level intent and slot labels at the word level. The best performing models force explicit interaction between intent detection and slot filling.
Externí odkaz:
http://arxiv.org/abs/2305.17729
Autor:
Ding, Yihao, Long, Siqu, Huang, Jiabin, Ren, Kaixuan, Luo, Xingxiang, Chung, Hyunsuk, Han, Soyeon Caren
Compared to general document analysis tasks, form document structure understanding and retrieval are challenging. Form documents are typically made by two types of authors; A form designer, who develops the form structure and keys, and a form user, w
Externí odkaz:
http://arxiv.org/abs/2304.01577
When a human communicates with a machine using natural language on the web and online, how can it understand the human's intention and semantic context of their talk? This is an important AI task as it enables the machine to construct a sensible answ
Externí odkaz:
http://arxiv.org/abs/2212.10728
Autor:
Zhang, Zhihao, Luo, Siwen, Chen, Junyi, Lai, Sijia, Long, Siqu, Chung, Hyunsuk, Han, Soyeon Caren
We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the full stack of visual question answering tasks, specifically data process
Externí odkaz:
http://arxiv.org/abs/2211.15940
Collaborative filtering problems are commonly solved based on matrix completion techniques which recover the missing values of user-item interaction matrices. In a matrix, the rating position specifically represents the user given and the item rated.
Externí odkaz:
http://arxiv.org/abs/2209.04154
Recognizing the layout of unstructured digital documents is crucial when parsing the documents into the structured, machine-readable format for downstream applications. Recent studies in Document Layout Analysis usually rely on computer vision models
Externí odkaz:
http://arxiv.org/abs/2208.10970
Attention mechanism has been used as an important component across Vision-and-Language(VL) tasks in order to bridge the semantic gap between visual and textual features. While attention has been widely used in VL tasks, it has not been examined the c
Externí odkaz:
http://arxiv.org/abs/2208.08104
For preventing youth suicide, social media platforms have received much attention from researchers. A few researches apply machine learning, or deep learning-based text classification approaches to classify social media posts containing suicidality r
Externí odkaz:
http://arxiv.org/abs/2206.08673
Pretrained models have produced great success in both Computer Vision (CV) and Natural Language Processing (NLP). This progress leads to learning joint representations of vision and language pretraining by feeding visual and linguistic contents into
Externí odkaz:
http://arxiv.org/abs/2204.07356