Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...
This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a ...
Small language models are typically trained or fine-tuned for specific enterprise tasks rather than open-ended conversations ...
This release is good for developers building long-context applications, real-time reasoning agents, or those seeking to ...
Artificial intelligence (AI) is rapidly transforming healthcare. AI systems can now detect diabetic eye disease from retinal photos and analyze CT images for signs of early-stage lung cancers and ...
Boeing engineers Kevin Kwak (foreground) and Klaus Okkelberg confer with fellow team members Arvel Chappell III and Andrew Riha (both on-screen), who worked together to prototype a large language ...
Similarly, high-quality datasets underpin the development and performance of large language models (LLMs). Among these, instruction-tuning datasets (ITDs) used for instruction fine-tuning have been ...
Pixazo launches Tracks at AI Impact Summit India 2026, an AI model for creating complete Hindi & Punjabi songs, available via API & Playground with free access. Tracks is a big step forward in making ...
In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We combine TRL’s DPOTrainer ...
In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...
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