This review focuses on the Diffusion Model, one of the most-noticed generative models among the diverse works presented at NeurIPS 2021, and covers the key research on it.
This article examines deep clustering techniques using Variational Autoencoder and the latest research based on VaDE.
This analyzes the latest research trends and cost-reduction techniques for Neural Architecture Search (NAS) presented at NeurIPS 2021.
This introduces research that combines Reinforcement Learning (RL) with Graph Neural Networks (GNN) to process complex data and learn general-purpose policies.
Following NLP's success, the vision-language field is also accelerating large-scale model training leveraging massive data and infrastructure.
A review of research trends in language models combining knowledge information, centered on ACL 2022.
LG AI Research participated in CVPR 2022, showcasing multimodal representation learning and L-Verse research.
We analyze the concept of NeRF, which drew attention at CVPR 2022, and the latest research trends.
This introduces the Continual Learning research trends based on Transformers and self-supervised learning presented at CVPR 2022.
LG AI Research announced PSGI technology that efficiently infers hierarchical task structures.
Proposes a new methodology that improves Domain Generalization (DG) performance by using Natural Language Supervision to align visual representations with human reasoning.
This article covers the concept of Long-Tail Distribution (LTD) and various learning methodologies to address data imbalance problems.
LG AI Research introduced key research on self-supervised learning presented at ICML 2022.
This introduces Neural Combinatorial Optimization (NCO) research for efficiently solving combinatorial optimization problems in large-scale graph environments.
Through an NVIDIA GTC 2022 session, the growth of the digital avatar market and its core technology, Omniverse ACE, are introduced.
This explores the latest trends in personalized image/language models and NeRF technology through NVIDIA GTC 2022.
At the IJCAI 2022 conference, research trends emphasizing the importance of reinforcement learning, federated learning, and reasoning capabilities were confirmed.
LG AI Research collaborated with Elsevier to achieve the top performance in the ChEMU 2022 challenge, which extracts reaction information from chemical patents and journals.
It introduces UniCLIP, a unified contrastive learning framework that breaks down boundaries between domains to enhance data efficiency.
LG AI Research developed a new attention mechanism-based AI model that improves HLA-peptide binding prediction performance.
The paper proposes SBM-Transformer, which adjusts attention sparsity based on data to improve computational efficiency.
We propose a new algorithm that improves the stability of offline Learning from Observation (LfO), which imitates expert behavior using only state information.
LG AI Research is researching a loop-based music generation model to help with motif generation, which is at the core of music composition.
This work proposes BeamCLIP, a methodology for efficiently transferring the representational power of large-scale multimodal models to small target models.
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