​[[{“value”:” Large language models (LLMs) have revolutionized various domains, including code completion, where artificial intelligence predicts and suggests code based on a developer’s previous inputs. This technology significantly enhances productivity, enabling developers to write code faster and with fewer errors. Despite the promise of LLMs,… Read More »aiXcoder-7B: A Lightweight and Efficient Large Language Model Offering High Accuracy in Code Completion Across Multiple Languages and Benchmarks Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have revolutionized the field of artificial intelligence by performing a wide range of tasks across different domains. These models are expected to work seamlessly in multiple languages, solving complex problems while ensuring safety. However, the challenge lies in maintaining safety… Read More »This AI Research from Cohere for AI Compares Merging vs Data Mixing as a Recipe for Building High-Performant Aligned LLMs Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Vision-Language-Action Models (VLA) for robotics are trained by combining large language models with vision encoders and then fine-tuning them on various robot datasets; this allows generalization to new instructions, unseen objects, and distribution shifts. However, various real-world robot datasets mostly require human control, which… Read More »Latent Action Pretraining for General Action models (LAPA): An Unsupervised Method for Pretraining Vision-Language-Action (VLA) Models without Ground-Truth Robot Action Labels Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A primary feature of sophisticated language models is In-Context Learning (ICL), which allows the model to produce answers based on input instances without being specifically instructed on how to complete the task. In ICL, a few examples that show the intended behavior or pattern… Read More »This Machine Learning Research Discusses How Task Diversity Shortens the In-Context Learning (ICL) Plateau Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The discovery of new materials is crucial to addressing pressing global challenges such as climate change and advancements in next-generation computing. However, existing computational and experimental approaches face significant limitations in efficiently exploring the vast chemical space. While AI has emerged as a powerful… Read More »Meta AI Releases Meta’s Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The growing reliance on large language models for coding support poses a significant problem: how best to assess real-world impact on programmer productivity? Current approaches, such as static bench-marking based on datasets such as HumanEval, measure the correctness of the code but cannot capture… Read More »RealHumanEval: A Web Interface to Measure the Ability of LLMs to Assist Programmers Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the rapidly evolving world of AI, challenges related to scalability, performance, and accessibility remain central to the efforts of research communities and open-source advocates. Issues such as the computational demands of large-scale models, the lack of diverse model sizes for different use cases,… Read More »Open Collective Releases Magnum/v4 Series Models From 9B to 123B Parameters Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” One of the most critical challenges of LLMs is how to align these models with human values and preferences, especially in generated texts. Most generated text outputs by models are inaccurate, biased, or potentially harmful—for example, hallucinations. This misalignment limits the potential usage of… Read More »CREAM: A New Self-Rewarding Method that Allows the Model to Learn more Selectively and Emphasize on Reliable Preference Data Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Human beings possess innate extraordinary perceptual judgments, and when computer vision models are aligned with them, model’s performance can be improved manifold. Various attributes such as scene layout, subject location, camera pose, color, perspective, and semantics help us have a clear picture of the… Read More »This AI Paper Explores If Human Visual Perception can Help Computer Vision Models Outperform in Generalized Tasks Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost