Vision-Language Models (VLMs) are increasingly used for generating responses to queries about visual content. Despite their progress, they often suffer from a major issue: generating plausible but incorrect responses, also known as hallucinations. These hallucinations can lead to a lack of trust in these systems, especially in real-world, high-stakes applications. Evaluating the helpfulness and truthfulness… →

In machine learning, embeddings are widely used to represent data in a compressed, low-dimensional vector space. They capture the semantic relationships well for performing tasks such as text classification, sentiment analysis, etc. However, they struggle to capture the intricate relationships in complex hierarchical structures within the data. This leads to suboptimal performances and increased computational… →

Utilizing Large Language Models (LLMs) through different prompting strategies has become popular in recent years. However, many current methods frequently offer very general frameworks that neglect to handle the particular difficulties involved in creating compelling urges. Differentiating prompts in multi-turn interactions, which involve several exchanges between the user and model, is a crucial problem that… →

Multi-modal entity alignment (MMEA) is a technique that leverages information from various data sources or modalities to identify corresponding entities across multiple knowledge graphs. By combining information from text, structure, attributes, and external knowledge bases, MMEA can address the limitations of single-modal approaches and achieve higher accuracy, robustness, and effectiveness in entity alignment tasks. However,… →

Sparse autoencoders (SAEs) are an emerging method for breaking down language model activations into linear, interpretable features. However, they fail to fully explain model behavior, leaving “dark matter” or unexplained variance. The ultimate aim of mechanistic interpretability is to decode neural networks by mapping their internal features and circuits. SAEs learn sparse representations to reconstruct… →

ElevenLabs just introduced Voice Design, a new AI voice generation that allows you to generate a unique voice from a text prompt alone. Text-to-speech is a very useful feature, but it has become very common, with few good options available. When we look at the AI voice generator market, we will see many different AI… →

Runway has announced a new feature called Act-One. One popular reason why Hollywood movies are so expensive is because of motion capturing, animations, and CGIs. A huge chunk of any movie these days goes toward the post-production. However, Hollywood and most people don’t realize there is no need for a massive budget anymore to create… →

Large language models (LLMs) have significantly advanced handling of complex tasks like mathematics, coding, and commonsense reasoning. However, improving the reasoning capabilities of these models remains a challenge. Researchers have traditionally focused on increasing the number of model parameters, but this approach has yet to hit a bottleneck, yielding diminishing returns and increasing computational costs.… →

AI-generated content is advancing rapidly, creating both opportunities and challenges. As generative AI tools become mainstream, the blending of human and AI-generated text raises concerns about authenticity, authorship, and misinformation. Differentiating human-authored content from AI-generated content, especially as AI becomes more natural, is a critical challenge that demands effective solutions to ensure transparency. SynthID: Open-Sourced… →

In the ever-evolving landscape of machine learning and artificial intelligence, developers are increasingly seeking tools that can integrate seamlessly into a variety of environments. One major challenge developers face is the ability to efficiently deploy machine learning models directly in the browser without relying heavily on server-side resources or extensive backend support. While JavaScript-based solutions… →