Browsing: ML News
Large language models (LLMs) have demonstrated remarkable capabilities in language understanding, reasoning, and generation tasks. Researchers are now focusing on developing LLM-based autonomous agents to tackle…
With the recent advancement of deep generative models, the challenge of denoising has also become apparent. Diffusion models are trained and designed similarly to denoisers, and…
Concept-based learning (CBL) in machine learning emphasizes using high-level concepts from raw features for predictions, enhancing model interpretability and efficiency. A prominent type, the concept-based bottleneck…
The field of research focuses on optimizing algorithms for training large language models (LLMs), which are essential for understanding and generating human language. These models are…
A major challenge in computer vision and graphics is the ability to reconstruct 3D scenes from sparse 2D images. Traditional Neural Radiance Fields (NeRFs), while effective…
As artificial intelligence (AI) technology continues to advance and permeate various aspects of society, it poses significant challenges to existing legal frameworks. One recurrent issue is…
Large language models (LLMs) face a critical challenge in their training process: the impending scarcity of high-quality internet data. Predictions suggest that by 2026, the available…
Broadly neutralizing antibodies (bNAbs) are key in combating HIV-1. They target the virus’s envelope proteins and show promise in reducing viral loads and preventing infection. Despite…
Hugging Face has announced the release of Transformers version 4.42, which brings many new features and enhancements to the popular machine-learning library. This release introduces several…
Reinforcement learning from human feedback (RLHF) encourages generations to have high rewards, using a reward model trained on human preferences to align large language models (LLMs).…