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 unveiled ChatEXAONE, an enterprise AI agent based on the open-source LLM EXAONE 3.0.
LG AI Research has unveiled ChatEXAONE, an AI agent based on EXAONE 3.0 that supports enterprise work innovation.
LG AI Research has released EXAONEPath, an open-source model specialized in pathology image analysis.
LG AI Research has unveiled EXAONEPath, an open-source model specialized for histopathology image analysis that achieves both high performance and cost efficiency.
LG AI Research presented a Binning-based Pretext Task study at ICML 2024 that improves self-supervised learning performance on tabular data.
LG AI Research presented a new methodology at ICML 2024 that improves learning performance on tabular data.
LG AI Research presented CADO research at ICML 2024, combining reinforcement learning and diffusion models to solve combinatorial optimization problems.
LG AI Research presented CADO, a study combining diffusion models with reinforcement learning to solve combinatorial optimization problems, at ICML 2024.
It introduces the latest research trends for overcoming the limitations of LLMs presented at ACL 2024 and LG AI Research's achievements.
Through the ACL 2024 tutorial session, we explore the latest research trends, including how to evaluate LLM-generated text and its vulnerabilities.
We introduce ChartInstruct, a general-purpose chart understanding model that comprehends the visual information in charts and performs complex reasoning.
We introduce ChartInstruct, a general-purpose chart vision-language model that applies Instruction Tuning to maximize chart understanding and reasoning capabilities.
This piece summarizes the trends and key methodologies of the latest AI-generated text detection technologies presented at ACL 2024.
This piece examines the methodologies for evaluating LLM faithfulness and the latest research trends for improving efficiency, as discussed at ACL 2024.
Through an ACL 2024 workshop, LG AI Research introduced the importance of developing LLMs that reflect cultural values and biases, along with related research.
This article looks at the latest research trends on how LLMs can reflect and measure diverse cultural values and social biases.
LG AI Research proposed Projection Regret, a technique that leverages Diffusion models to reduce interference from background information and improve novelty detection performance.
LG AI Research proposed Projection Regret, a technique that uses a Diffusion model to reduce background noise and improve anomaly detection performance.
LG AI Research has introduced an AI Red Team that checks vulnerabilities from an offensive perspective to enhance the security and reliability of generative AI.
It introduces the concept of AI Red Team and its step-by-step attack strategies for detecting and defending against vulnerabilities in generative AI.
LG AI Research conducts research to define and systematically classify the practical risks that AI can cause through its AI Ethics Seminar.
This article analyzes Microsoft's and Google's AI toolkits to design trustworthy AI experiences and presents practical application methods.
To design trustworthy AI experiences, this analyzes Microsoft's and Google's AI Toolkits and presents practical application guidelines.
It analyzes the autonomous decision-making and cooperation patterns of AI Agents through simulations and presents the need for ethical mechanisms.