Retrieval-augmented generation (RAG) has been shown to improve knowledge capabilities and reduce the hallucination problem of LLMs. The Web is a major source of external knowledge used in RAG and many commercial systems such as ChatGPT. However, current RAG implementations face a fundamental challenge in their knowledge-processing approach. The conventional method of converting HTML documents… →

In today’s world, Graph similarity computation (GSC) plays an important role in various applications such as code detection, molecular graph similarity, image matching, etc., by evaluating the similarity between two graphs, and it is based on Graph similarity learning. Graph Edit Distance (GED) and Maximum Common Subgraph (MCS) are widely used to measure graph similarity.… →

Document Visual Question Answering (DocVQA) represents a rapidly advancing field aimed at improving AI’s ability to interpret, analyze, and respond to questions based on complex documents that integrate text, images, tables, and other visual elements. This capability is increasingly valuable in finance, healthcare, and law settings, as it can streamline and support decision-making processes that… →

In recent years, Automatic Speech Recognition (ASR) technology has gained significant traction, transforming industries ranging from healthcare to customer support. However, achieving accurate transcription across diverse languages, accents, and noisy environments remains challenging. Current speech-to-text models often face issues like inaccuracies in understanding complex accents, handling domain-specific terminology, and dealing with background noise. The need… →

Adam is widely used in deep learning as an adaptive optimization algorithm, but it struggles with convergence unless the hyperparameter β2 is adjusted based on the specific problem. Attempts to fix this, like AMSGrad, require the impractical assumption of uniformly bounded gradient noise, which doesn’t hold in cases with Gaussian noise, as seen in variational… →

In an exciting update for developers, Google has launched Gemini, a new AI model that promises to be more accessible and developer-friendly. Gemini, designed to rival models like OpenAI’s GPT-4, has been made easier to access and integrate into various applications, thanks to Google’s recent initiatives. If you’re a developer exploring powerful alternatives or complementary… →

Microsoft Paint, the nostalgic art tool that has been a part of countless childhood memories, is stepping boldly into the future. Microsoft has announced that the beloved drawing application is getting an impressive AI makeover, integrating features that make it easier than ever to create stunning digital art. These new features promise to turn even… →

Language models have demonstrated remarkable capabilities in processing diverse data types, including multilingual text, code, mathematical expressions, images, and audio. However, a fundamental question arises: how do these models effectively handle such heterogeneous inputs using a single parameter set? While one approach suggests developing specialized subspaces for each data type, this overlooks the inherent semantic… →

AI has made significant strides in developing large language models (LLMs) that excel in complex tasks such as text generation, summarization, and conversational AI. Models like LaPM 540B and Llama-3.1 405B demonstrate advanced language processing abilities, yet their computational demands limit their applicability in real-world, resource-constrained environments. These LLMs are often cloud-based, requiring extensive GPU… →

The rapid scaling of diffusion models has led to memory usage and latency challenges, hindering their deployment, particularly in resource-constrained environments. Such models have manifested impressive ability in rendering highly-fidelity images but are demanding in both memory and computation, which limits their availability in consumer-grade devices and applications that require low latencies. Therefore, these challenges… →