Incorporating dynamic semantics into pre-trained language model for aspect-based sentiment analysis
Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towards a specific
aspect in the given sentence. While pre-trained language models such as BERT have …
aspect in the given sentence. While pre-trained language models such as BERT have …
Evaluating generative ad hoc information retrieval
Recent advances in large language models have enabled the development of viable
generative retrieval systems. Instead of a traditional document ranking, generative retrieval …
generative retrieval systems. Instead of a traditional document ranking, generative retrieval …
A survey on dynamic neural networks for natural language processing
Effectively scaling large Transformer models is a main driver of recent advances in natural
language processing. Dynamic neural networks, as an emerging research direction, are …
language processing. Dynamic neural networks, as an emerging research direction, are …
Measuring and improving user experience through artificial intelligence-aided design
B Yang, L Wei, Z Pu - Frontiers in Psychology, 2020 - frontiersin.org
This paper aims to propose a methodology for measuring user experience (UX) by using
artificial intelligence-aided design (AIAD) technology in mobile application design. Unlike …
artificial intelligence-aided design (AIAD) technology in mobile application design. Unlike …
Leveraging passage-level cumulative gain for document ranking
Document ranking is one of the most studied but challenging problems in information
retrieval (IR) research. A number of existing document ranking models capture relevance …
retrieval (IR) research. A number of existing document ranking models capture relevance …
Axiomatically regularized pre-training for ad hoc search
Recently, pre-training methods tailored for IR tasks have achieved great success. However,
as the mechanisms behind the performance improvement remain under-investigated, the …
as the mechanisms behind the performance improvement remain under-investigated, the …
Extractive explanations for interpretable text ranking
Neural document ranking models perform impressively well due to superior language
understanding gained from pre-training tasks. However, due to their complexity and large …
understanding gained from pre-training tasks. However, due to their complexity and large …
Towards a better understanding of human reading comprehension with brain signals
Reading comprehension is a complex cognitive process involving many human brain
activities. However, little is known about what happens in human brain during reading …
activities. However, little is known about what happens in human brain during reading …
Learning better representations for neural information retrieval with graph information
Neural ranking models have recently gained much attention in Information Retrieval
community and obtain good ranking performance. However, most of these retrieval models …
community and obtain good ranking performance. However, most of these retrieval models …
Ladra-net: Locally aware dynamic reread attention net for sentence semantic matching
Sentence semantic matching requires an agent to determine the semantic relation between
two sentences, which is widely used in various natural language tasks, such as natural …
two sentences, which is widely used in various natural language tasks, such as natural …