Zobrazeno 1 - 10
of 907
pro vyhledávání: '"Li, Jiangnan"'
Micromagnetics has made significant strides, particularly due to its wide-ranging applications in magnetic storage design. Numerical simulation is a cornerstone of micromagnetics research, relying on first-principle rules to compute the dynamic evolu
Externí odkaz:
http://arxiv.org/abs/2410.14986
Autor:
Li, Jiangnan, Lin, Zheng, Wang, Lanrui, Si, Qingyi, Cao, Yanan, Yu, Mo, Fu, Peng, Wang, Weiping, Zhou, Jie
Humans convey emotions through daily dialogues, making emotion understanding a crucial step of affective intelligence. To understand emotions in dialogues, machines are asked to recognize the emotion for an utterance (Emotion Recognition in Dialogues
Externí odkaz:
http://arxiv.org/abs/2406.04758
Large Language Model (LLM) is a significant breakthrough in artificial intelligence (AI) and holds considerable potential for application within smart grids. However, as demonstrated in previous literature, AI technologies are susceptible to various
Externí odkaz:
http://arxiv.org/abs/2405.06237
This work introduces an original and practical paradigm for narrative comprehension, stemming from the characteristics that individual passages within narratives tend to be more cohesively related than isolated. Complementary to the common end-to-end
Externí odkaz:
http://arxiv.org/abs/2402.13551
Autor:
Li, Jiangnan, Wang, Qiujing, Xu, Liyan, Pang, Wenjie, Yu, Mo, Lin, Zheng, Wang, Weiping, Zhou, Jie
Similar to the "previously-on" scenes in TV shows, recaps can help book reading by recalling the readers' memory about the important elements in previous texts to better understand the ongoing plot. Despite its usefulness, this application has not be
Externí odkaz:
http://arxiv.org/abs/2402.07271
Identifying speakers of quotations in narratives is an important task in literary analysis, with challenging scenarios including the out-of-domain inference for unseen speakers, and non-explicit cases where there are no speaker mentions in surroundin
Externí odkaz:
http://arxiv.org/abs/2312.14590
Autor:
Wang, Lanrui, Li, Jiangnan, Yang, Chenxu, Lin, Zheng, Tang, Hongyin, Liu, Huan, Huang, Xiaolei, Cao, Yanan, Wang, Jingang, Wang, Weiping
Recently, there has been a heightened interest in building chatbots based on Large Language Models (LLMs) to emulate human-like qualities in dialogues, including expressing empathy and offering emotional support. Despite having access to commonsense
Externí odkaz:
http://arxiv.org/abs/2311.15316
Autor:
Xu, Shicheng, Pang, Liang, Li, Jiangnan, Yu, Mo, Meng, Fandong, Shen, Huawei, Cheng, Xueqi, Zhou, Jie
Retrieving relevant plots from the book for a query is a critical task, which can improve the reading experience and efficiency of readers. Readers usually only give an abstract and vague description as the query based on their own understanding, sum
Externí odkaz:
http://arxiv.org/abs/2311.01666
Autor:
Yang, Chenxu, Lin, Zheng, Wang, Lanrui, Tian, Chong, Pang, Liang, Li, Jiangnan, Ho, Qirong, Cao, Yanan, Wang, Weiping
Knowledge-grounded dialogue generation aims to mitigate the issue of text degeneration by incorporating external knowledge to supplement the context. However, the model often fails to internalize this information into responses in a human-like manner
Externí odkaz:
http://arxiv.org/abs/2310.08943
Text-based Visual Question Answering (TextVQA) aims at answering questions about the text in images. Most works in this field focus on designing network structures or pre-training tasks. All these methods list the OCR texts in reading order (from lef
Externí odkaz:
http://arxiv.org/abs/2308.16383