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Google DeepMind scientists have introduced ‘Gecko’; a flexible, space-efficient embedding model enhanced by the immense global knowledge offered by Language Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 3, 202434Views0Likes0Comments
Researchers from Google DeepMind have introduced Gecko, a groundbreaking text embedding model to transform text into a form that machines can comprehend and act upon. Gecko is unique in its use of large language models (LLMs) for knowledge distillation. As opposed to conventional models that depend on comprehensive labeled datasets, Gecko initiates its learning journey…

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DomainLab: A Versatile Python Module for Universal Application in Deep Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Python, Staff, Tech News, Technology, UncategorizedMarch 27, 202441Views0Likes0Comments
Artificial intelligence and deep learning models, despite their popularity and capacity, often struggle with generalization, particularly when they encounter data that differs from what they were trained on. This issue arises when the distribution of training and testing data varies, resulting in reduced model performance. The concept of domain generalization has been introduced to combat…

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The Concept of Feedback Generated by Compiler for Big Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMarch 27, 202438Views0Likes0Comments
Large Language Models (LLMs) have shown significant impact across various tasks within the software engineering space. Leveraging extensive open-source code datasets and Github-enabled models like CodeLlama, ChatGPT, and Codex, they can generate code and documentation, translate between programming languages, write unit tests, and identify and rectify bugs. AlphaCode is a pre-trained model that can help…

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MathVerse: A Comprehensive Visual Math Benchmark Crafted for Fair, Thorough Assessment of Multi-modal Extensive Language Models (MLLMs)

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedMarch 26, 202436Views0Likes0Comments
The ability of large Multimodal Language Models (MLLMs) to tackle visual math problems is currently the subject of intense interest. While MLLMs have performed remarkably well in visual scenarios, the extent to which they can fully understand and solve visual math problems remains unclear. To address these challenges, frameworks such as GeoQA and MathVista have…

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Scientists from GSK AI and Imperial College have launched RAmBLA, a machine learning tool created to assess the dependability of LLMs as auxiliary aids in the biomedical field.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedMarch 26, 202434Views0Likes0Comments
The increased adoption and integration of large Language Models (LLMs) in the biomedical sector for interpretation, summary and decision-making support has led to the development of an innovative reliability assessment framework known as Reliability AssessMent for Biomedical LLM Assistants (RAmBLA). This research, led by Imperial College London and GSK.ai, puts a spotlight on the critical…

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This AI article presents SafeEdit: An innovative standard for exploring the purification of LLMs through knowledge modification.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMarch 26, 202439Views0Likes0Comments
As the advancements in Large Language Models (LLMs) such as ChatGPT, LLaMA, and Mistral continue, there are growing concerns about their vulnerability to harmful queries. This has caused an immediate need to implement robust safeguards. Techniques such as supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and direct preference optimization (DPO) have been useful…

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Improving User Control in Generative Language Models: Algorithmic Solution for Filtering Toxicity

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMarch 26, 202437Views0Likes0Comments
Generative Language Models (GLMs) are now ubiquitous in various sectors, including customer service and content creation. Consequently, handling potential harmful content while keeping linguistic diversity and inclusivity has become important. Toxicity scoring systems aim to filter offensive or hurtful language, but often misidentify harmless language as harmful, especially from marginalized communities. This restricts access to…

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Reforming High-Dimensional Optimization: The Dimension-Free Convergence of the Krylov Subspace Cubic Regularized Newton Method.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedMarch 26, 202437Views0Likes0Comments
Optimizing efficiency in complex systems is a significant challenge for researchers, particularly in high-dimensional spaces commonly found in machine learning. Second-order methods like the cubic regularized Newton (CRN) method demonstrate rapid convergence; however, their application in high-dimensional problems has been limited due to substantial memory and computational requirements. To counter these challenges, scientists from UT…

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Researchers from EPFL have developed DenseFormer: A Tool for Boosting Transformer Efficiency using Depth-Weighted Averages to Improve Language Modeling Performance and Speed.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMarch 26, 202437Views0Likes0Comments
In recent years, natural language processing (NLP) has seen significant advancements due to the transformer architecture. However, as these models grow in size, so do their computational costs and memory requirements, limiting their practical use to a select few corporations. Increasing model depths also present challenges, as deeper models need larger datasets for training, which…

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EPFL Researchers’ DenseFormer: Improving Transformer Efficiency through Depth-Weighted Averages for Optimal Language Modeling Speed and Performance.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedMarch 26, 202434Views0Likes0Comments
Transformer architecture has greatly enhanced natural language processing (NLP); however, issues such as increased computational cost and memory usage have limited their utility, especially for larger models. Researchers from the University of Geneva and École polytechnique fédérale de Lausanne (EPFL) have addressed this challenge by developing DenseFormer, a modification to the standard transformer architecture, which…

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