Language
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AI
EAGLE: Exploring the Design Space for Multimodal Large Language Models with a Mixture of Encoders
The ability to accurately interpret complex visual information is a crucial focus of multimodal large language models (MLLMs). Recent work…
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AI
AI Language Showdown: Comparing the Performance of C++, Python, Java, and Rust
The choice of programming language in Artificial Intelligence (AI) development plays a vital role in determining the efficiency and success…
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AI
Jamba: AI21 Labs’ New Hybrid Transformer-Mamba Language Model
Language models have witnessed rapid developments, with Transformer-based architectures leading the way in natural language processing. However, as models grow…
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AI
Improving Retrieval Augmented Language Models: Self-Reasoning and Adaptive Augmentation for Conversational Systems
Large language models often struggle with delivering precise and current information, particularly in complex knowledge-based tasks. To overcome these hurdles,…
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AI
SGLang: Efficient Execution of Structured Language Model Programs
Large language models (LLMs) are increasingly utilized for complex tasks requiring multiple generation calls, advanced prompting techniques, control flow, and…
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AI
Tracking Large Language Models (LLM) with MLflow : A Complete Guide
As Large Language Models (LLMs) grow in complexity and size, tracking their performance, experimentation, and implementations becomes increasingly challenging. This…
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