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- Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors494
The Recurrent Attended Variation Embedding Network (RAVEN) is proposed that models the fine-grained structure of nonverbal subword sequences and dynamically shifts word representations based on nonverbal cues to capture the dynamic nature of non verbal intents.
- A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems269
This article aims to elaborate recent advances in multi-turn dialogue systems, covering both LLM-based open-domain dialogue (ODD) and task-oriented dialogue (TOD) systems, along with datasets and evaluation metrics.
- A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers164
This survey provides a comprehensive review of existing deep learning techniques for Relation extraction and proposes a new taxonomy to categorize existing works from three perspectives, i.e., text representation, context encoding, and triplet prediction.
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- A Survey of Natural Language Generation149
This survey aims to give the latest synthesis of deep learning research on the NLG core tasks, as well as the architectures adopted in the field, and detail meticulously and comprehensively various NLG tasks and datasets.
- Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey138
This survey gives an up-to-date synthesis of natural language understanding of images and text, as well as the knowledge reasoning module based on image-question information on the core VQA tasks.
- Time-driven feature-aware jointly deep reinforcement learning for financial signal representation and algorithmic trading123
A time-driven feature-aware jointly deep reinforcement learning model (TFJ-DRL) that integrates deep learning model and reinforcementLearning model to improve the financial signal representation learning and action decision making in algorithmic trading is proposed.
- Generalized Adjusted Rand Indices for cluster ensembles107
Adjusted Rand Index is generalized to two new measures based on matrix comparison: (i) Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency of a set of clustering solutions with their corresponding consensus matrix in a cluster ensemble, and (ii) AdjustedRand Index between similarity matrices (ARImm), to evaluation the consistency between two similarity matrix.
- Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge96
A multi-grained lattice framework for Chinese relation extraction is proposed, which incorporates word-level information into character sequence inputs so that segmentation errors can be avoided and model multiple senses of polysemous words with the help of external linguistic knowledge to alleviate polysemy ambiguity.
- An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription86
This study attempted to bridge the patient/caregiver gap by building a sophisticated application that uses artificial intelligence and machine learning computational techniques to perform data-driven decision-making at the point of primary care.
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- Psychometric Properties of Patient-Reported Outcome Measures for Use in Patients with Anterior Cruciate Ligament Injuries79
The ACL-RSI is a reliable and valid scale to measure outcomes for patients with ACL injuries and further assessments with improved methodological quality are needed to determine the psychometric properties of other instruments.
- Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system78
This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support.
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- Knowledge-aware Attentive Neural Network for Ranking Question Answer Pairs70
A context-knowledge interactive learning architecture is developed, in which a context-guided attentive convolutional neural network is designed to integrate knowledge embeddings into sentence representations and a knowledge-aware attention mechanism is presented to attend interrelations between each segments of QA pairs.
- Investigating the transferring capability of capsule networks for text classification68
The transferring capability of the proposed cross-domain capsule network (TL-Capsule) is demonstrated by applying it to two transfer learning applications: single-label to multi-label text classification and cross- domain sentiment classification.
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- Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering65
A question-driven pointer-generator network is designed, which exploits the correlation information between question-answer pairs to aid in attending the essential information when generating answer summaries and a new large-scale CQA corpus is constructed, WikiHowQA, which contains long answers for answer selection as well as reference summaries for answer summarization.
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- FM-ECG: A fine-grained multi-label framework for ECG image classification60
Experimental results on two real-world large-scale ECG datasets prove the capability of FM-ECG comparing with other state-of-the-art methods in ECG abnormally detection, and visualization analyses on attention parts show that meaningful spatial attention can be effectively learned by FM- ECG.
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- Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering55
A novel multi-task learning scheme that utilizes multi-view attention learned from various perspectives to enable these tasks to interact with each other as well as learn more comprehensive sentence representations is proposed.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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