New computational chemistry techniques accelerate the prediction of molecules and materials | MIT News
In the old days, in the really old days, the task of designing materials was laborious. Researchers, for more than ...
Tag: Computational
A new computational model can predict the structures of antibodies with greater precision | MIT News
<img src="https://news.mit.edu/sites/default/files/styles/news_article__cover_image__original/public/images/202501/MIT-Antibodies-ai-01_0.jpg?itok=Y9SPR7l6" /> By adapting artificial intelligence models known as big language models, researchers have made great strides in their ...
Decoding hidden computational dynamics: A new machine learning framework for understanding large language model representations.
In the rapidly evolving landscape of machine learning and artificial intelligence, understanding the fundamental representations within transformer models has become ...
Meet DataLab: A Unified Business Intelligence Platform Using LLM-Based Agents and Computational Laptops
Business intelligence (BI) faces significant challenges in efficiently transforming large volumes of data into actionable insights. Today's workflows involve multiple ...
Computational bottlenecks in training large, small-scale language models
This paper was accepted into the Efficient Natural Speech and Language Processing (ENLSP) workshop at the NeurIPS 2024 Workshop. While ...
Relaxed Recursive Transformers with Layered Low-Rank Adaptation: Achieving High Performance and Low Computational Cost on Large Language Models
Large language models (LLMs) are based on deep learning architectures that capture complex linguistic relationships within layered structures. Primarily based ...
STGformer: A Spatiotemporal Graph Transformer Achieving Unmatched Computational Efficiency and Performance in Large-Scale Traffic Forecasting Applications
Traffic forecasting is a fundamental aspect of smart city management, essential for improving transportation planning and resource allocation. With the ...
Optimizing large-scale sentence comparisons: How Sentence-BERT (SBERT) reduces computational time while maintaining high accuracy in semantic textual similarity tasks
Researchers have focused on developing and building models to efficiently process and compare human language in natural language processing. A ...
BISCUIT: Scaffolding LLM-generated code with ephemeral user interfaces in computational notebooks
This article was accepted at the IEEE Symposium on Visual Languages and Human-Centered Computing (VL/HCC) 2024 Programmers frequently interact with ...
Improving Transformer Models with Filler Tokens: A New AI Approach to Boost Computational Capabilities in Solving Complex Problems
Transformer-based language models are critical to advancing the field of ai. Traditionally, these models have been implemented to interpret and ...
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