AI Briefing#lg-ai-research
The latest AI and developer news about #lg-ai-research, with the original source and a short summary.
The latest AI and developer news about #lg-ai-research, with the original source and a short summary.
LG AI Research has developed SISE, a new image recognition explanation technology that overcomes the limitations of existing XAI models.
Introduces the latest trends in generative models, including the Score-based models and VAEBM that drew attention at ICLR 2021.
This introduces generative models and SDE-based Score-based Generative Modeling, key trends at ICLR 2021.
Introduces the latest reinforcement learning research trends for solving real-world problems, as discussed at ICLR 2021.
It covers the characteristics of combinatorial optimization problems and the complexity of integer programming, as introduced at ICML 2021.
LG AI Research used Contrastive Learning to build an unsupervised anomaly detection model with higher accuracy than supervised learning.
LG AI Research has revealed the technical principles of EXAONE, a multimodal model that understands text and images bidirectionally.
This piece analyzes the principles of Diffusion Models, a core component of generative models, and the differences among various generative models.
This reviews Variational Autoencoder-based Deep Clustering techniques and key papers presented at NeurIPS 2021.
This reviews the concept of Neural Architecture Search (NAS), which automatically searches for optimal neural network architectures, along with cost-reduction techniques.
This post examines various research cases that combine external knowledge and retrieval technology to improve the performance of language models.
Introduces various implementation methodologies for improving the computational efficiency of self-attention, the core of the Transformer.
Introduces the latest trends in multimodal representation learning and NeRF technology that drew attention at CVPR 2022.
Through Parameterized Subtask Graph Inference (PSGI), AI's generalization performance on untrained new entities and tasks has been improved.
They presented a methodology that leverages the commonsense knowledge embedded in LLMs to plan complex tasks step by step, improving planning accuracy through mutual information-based ranking and environment feedback.
Proposed a domain generalization (DG) technique that maintains performance even when the image domain changes, by leveraging human linguistic descriptions.
We examine the concept and various methodologies of Long-Tail Distribution learning to address the data imbalance problem.
This article introduces key techniques from papers on Self-supervised learning presented at ICML 2022, focusing on the ADIOS framework.
Introduces the LeNSE methodology for processing large-scale graph data through Neural Combinatorial Optimization (NCO) research presented at ICML 2022.
LG AI Research demonstrated its technical capabilities by achieving high performance in the ChEMU 2022 challenge, which extracts information from chemical patents.
UniCLIP is a technology that improves data efficiency by unifying intra-domain and inter-domain contrastive learning into a single framework.
LG AI Research presented research achievements related to continual learning and scale-invariant networks at ECCV 2022.
LG AI Research has developed a new AI model based on a Conditional Attention mechanism that effectively predicts the interaction between HLA and peptides.
LG AI Research has proposed SBM-Transformer, which captures both computational efficiency and performance at the same time.