LG AI Research presented the MAMA framework at ICASSP 2023, maximizing time series forecasting performance.
LG AI Research explored the latest vision research trends at CVPR 2023 and discussed the limitations of image captioning through the NICE workshop.
LG AI Research analyzed the computer vision research trends presented at CVPR 2023 and visual reasoning techniques leveraging LLMs.
LG AI Research proposed the QASA benchmark and a multi-step reasoning methodology for deep reasoning on scientific literature.
LG AI Research has released the QASA methodology and benchmark to address complex reasoning in scientific papers.
LG AI Research presented its latest research achievements, including Unlearning and Causal Inference for generative models, at ICML 2023.
LG AI Research unveiled an efficient unlearning technique to protect data privacy in generative models at ICML 2023.
We look at the types of training data and the multifaceted evaluation metrics that determine the performance of LLMs, the core of generative AI.
This provides a detailed analysis of data training, evaluation, and model architecture for Large Language Models (LLMs), the core of generative AI.
LG AI Research's EXAONE model ranked first on KorQuAD 2.0, a benchmark for evaluating Korean machine reading comprehension performance.
LG AI Research achieved the #1 ranking on the Korean machine reading comprehension benchmark KorQuAD 2.0 using EXAONE LM 1.0.
Introducing the latest trends in AI-driven materials database expansion and experimental automation technology presented at the MRS conference.
Google DeepMind expanded the inorganic materials database tenfold through active learning and discovered more than 380,000 new stable materials.
LG AI Research's demand forecasting squad achieved results winning awards in 3 categories at the M6 conference held in New York.
Introduces five major AI research trends and key papers in CV, LLM, and more that drew attention at NeurIPS 2023.
LG AI Research's demand forecasting squad achieved award-winning results in 3 categories at the M6 forecasting competition held in New York.
This introduces the latest research trends and key papers on RLHF and RLAIF presented at NeurIPS 2023.
This summarizes the latest research trends presented at NeurIPS 2023, covering the performance, safety, efficiency, and tool-use capabilities of LLMs.
LG AI Research presented a new training methodology at NeurIPS 2023 to improve deep learning performance on Tabular Data.
This introduces the audio and music generation technologies that drew attention at NeurIPS 2023, along with research achievements from LG AI Research.
Introduces the latest Computer Vision (CV) research trends and key papers from LG's participation in NeurIPS 2023.
Introduces the latest research trends in RLHF and RLAIF for improving LLM performance, along with the DPO and Fine-Grained RLHF methodologies.
This looks at the latest research trends in LLMs presented at NeurIPS 2023, including performance evaluation, safety, tool use, and efficient fine-tuning.
This summarizes research trends in general-purpose and domain-specific LLM-based autonomous agents presented at NeurIPS 2023.
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