Graph neural networks: A review of methods and applications
2020
Lots of learning tasks require dealing with graph data which contains rich relation information among elements. Modeling physics systems, learning molecular fingerprints, predicting protein interface,...
A survey of transformers
2022
Transformers have achieved great success in many artificial intelligence fields, such as natural language processing, computer vision, and audio processing. Therefore, it is natural to attract lots...
TRiSM for Agentic AI: A review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems
2026
Agentic AI systems, built upon large language models (LLMs) and deployed in multi-agent configurations, are redefining intelligence, autonomy, collaboration, and decision-making across enterprise and...
Large language models in law: A survey
2024
The advent of artificial intelligence (AI) has significantly impacted the traditional judicial industry. Moreover, recently, with the development of AI-generated content (AIGC), AI and law have found...
Neural machine translation: A review of methods, resources, and tools
2020
Machine translation (MT) is an important sub-field of natural language processing that aims to translate natural languages using computers. In recent years, end-to-end neural machine translation (NMT)...
Pre-trained models: Past, present and future
2021
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI). Owing to sophisticated pre-training...
From tools to partners: How large language models are transforming urban planning
2025
Recent advances in large language models have transformed urban planning from passive tool-assisted workflows to active human–AI collaborative partnerships, enabling natural language-driven design generation,...
AI-generated content in landscape architecture: A survey
2025
Landscape design is a complex process that requires designers to engage in intricate planning, analysis, and decision-making. This process involves the integration and reconstruction of science, art,...
Advancing AI for science: From the revolution of tools to the tools for revolution
2025
Scientific research is not a linear pipeline but a dynamic system built upon the ever-shifting interactions among three elements — research objects, tools, and researchers. And sustained progress depends...
GPT understands, too
2024
Prompting a pretrained language model with natural language patterns has been proved effective for natural language understanding (NLU). However, our preliminary study reveals that manual discrete prompts...
Knowledge intensive agents
2026
Large Language Models (LLMs) have exhibited impressive capabilities in reasoning and language understanding. However, their reliance on memorized knowledge and tendency to generate hallucinated content...
Advances and challenges in conversational recommender systems: A survey
2021
Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. However, static recommendation models are difficult to...
Symbolic learning enables self-evolving agents
2025
The AI community has been exploring a pathway to artificial general intelligence (AGI) by developing “language agents”, which are complex large language models (LLMs) workflows involving both prompting...
Bio-inspired adaptive neurons for dynamic weighting in Artificial Neural Networks
2026
Traditional neural networks employ fixed weights during inference, limiting their ability to adapt to changing input conditions, unlike biological neurons that adjust signal strength dynamically based...
Optimal RoPE extension via Bayesian Optimization for training-free length generalization
2025
Transformers are designed to process input of variable length without resource constraints. However, their performance significantly deteriorates when the input surpasses a threshold slightly larger...
Deep learning for fake news detection: A comprehensive survey
2022
The information age enables people to obtain news online through various channels, yet in the meanwhile making false news spread at unprecedented speed. Fake news exerts detrimental effects for it impairs...
Data augmentation approaches in natural language processing: A survey
2022
As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where deep learning techniques may fail. It is widely applied in computer vision then introduced to natural language...
Neural, symbolic and neural-symbolic reasoning on knowledge graphs
2021
Knowledge graph reasoning is the fundamental component to support machine learning applications such as information extraction, information retrieval, and recommendation. Since knowledge graphs can...
A comprehensive review on resolving ambiguities in natural language processing
2021
Natural language processing is a known technology behind the development of some widely known AI assistants such as: SIRI, Natasha, and Watson. However, NLP is a diverse technology used for numerous...
Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection
2025
This study presents a comprehensive review of the potential of multimodal deep learning (DL) in medical diagnosis, using COVID-19 as a case example. Motivated by the success of artificial intelligence...
ChatLLM network: More brains, more intelligence
2025
Dialogue-based language models mark a huge milestone in the field of artificial intelligence, by their impressive ability to interact with users, as well as a series of challenging tasks prompted by...
Sarcasm detection using news headlines dataset
2023
Sarcasm has been an elusive concept for humans. Due to interesting linguistic properties, sarcasm detection has gained traction of the Natural Language Processing (NLP) research community in the past...
A comprehensive survey of entity alignment for knowledge graphs
2021
Knowledge Graphs (KGs), as a structured human knowledge, manage data in an ease-of-store, recognizable, and understandable way for machines and provide a rich knowledge base for different artificial...