Large Vision Language Models (LVLMs) have demonstrated significant advancements across various challenging multi-modal tasks over the past few years. Their ability to interpret visual information in figures, known as visual perception, relied on visual encoders and multimodal training. Even with these advancements, visual perception errors still cause many mistakes in LVLMs and impact their ability…
Training AI models today isn’t just about designing better architectures—it’s also about managing data efficiently. Modern models require vast datasets and need those datasets delivered quickly to GPUs and other accelerators. The problem? Traditional data loading systems often lag behind, slowing everything down. These older systems rely heavily on process-based methods that struggle to keep…
Quantum computing has long been seen as a promising avenue for advancing computational capabilities beyond those of classical systems. However, the field faces a persistent challenge: error rates. Quantum bits, or qubits, are inherently fragile, and minor disturbances can lead to computational errors. This sensitivity has limited the scalability and practical application of quantum systems.…
OpenAI has unveiled Sora, its new text-to-video generation tool, a major step forward in AI-powered content creation. However, the launch comes with a notable exception: users in the European Union and the United Kingdom won’t have access for now, highlighting ongoing challenges between innovation and regulation. Sora is OpenAI’s answer to simplifying video production. It…
Inspired by human cognitive processes, large language models (LLMs) possess an intriguing ability to interpret and represent abstract world states, which are specific snapshots of the situation or context (basically the environment) described in the text, such as the arrangement of objects or tasks in a virtual or real-world scenario. The research explores this potential…
Research in code embedding models has witnessed a significant breakthrough with the introduction of voyage-code-3, an advanced embedding model specifically designed for code retrieval tasks by researchers from Voyage AI. The model demonstrates remarkable performance, substantially outperforming existing state-of-the-art solutions like OpenAI-v3-large and CodeSage-large. Empirical evaluations across a comprehensive suite of 238 code retrieval datasets…
Medical question-answering (QA) systems are critical in modern healthcare, providing essential tools for medical practitioners and the public. Long-form QA systems differ significantly from simpler models by offering detailed explanations reflecting real-world clinical scenarios’ complexity. These systems must accurately interpret nuanced questions, often with incomplete or ambiguous information, and produce reliable, in-depth answers. With the…
In the rapidly evolving landscape of machine learning and artificial intelligence, understanding the fundamental representations within transformer models has emerged as a critical research challenge. Researchers are grappling with competing interpretations of what transformers represent—whether they function as statistical mimics, world models, or something more complex. The core intuition suggests that transformers might capture the…
In large language models (LLMs), “hallucination” refers to instances where models generate semantically or syntactically plausible outputs but are factually incorrect or nonsensical. For example, a hallucination occurs when a model provides erroneous information, such as stating that Addison’s disease causes “bright yellow skin” when, in fact, it causes fatigue and low blood pressure. This…
As AI systems become integral to daily life, ensuring the safety and reliability of LLMs in decision-making roles is crucial. While LLMs have shown impressive performance across various tasks, their ability to operate safely and cooperate effectively in multi-agent environments still needs to be explored. Cooperation is critical in scenarios where agents work together to…