Llm-based edge intelligence: A comprehensive survey on architectures, applications, security and trustworthiness
The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …
A systematic survey and critical review on evaluating large language models: Challenges, limitations, and recommendations
Abstract Large Language Models (LLMs) have recently gained significant attention due to
their remarkable capabilities in performing diverse tasks across various domains. However …
their remarkable capabilities in performing diverse tasks across various domains. However …
The llama 3 herd of models
Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …
presents a new set of foundation models, called Llama 3. It is a herd of language models …
Llamafactory: Unified efficient fine-tuning of 100+ language models
Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks.
However, it requires non-trivial efforts to implement these methods on different models. We …
However, it requires non-trivial efforts to implement these methods on different models. We …
Minicpm-v: A gpt-4v level mllm on your phone
The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally
reshaped the landscape of AI research and industry, shedding light on a promising path …
reshaped the landscape of AI research and industry, shedding light on a promising path …
Drivevlm: The convergence of autonomous driving and large vision-language models
A primary hurdle of autonomous driving in urban environments is understanding complex
and long-tail scenarios, such as challenging road conditions and delicate human behaviors …
and long-tail scenarios, such as challenging road conditions and delicate human behaviors …
RULER: What's the Real Context Size of Your Long-Context Language Models?
The needle-in-a-haystack (NIAH) test, which examines the ability to retrieve a piece of
information (the" needle") from long distractor texts (the" haystack"), has been widely …
information (the" needle") from long distractor texts (the" haystack"), has been widely …
Vlmevalkit: An open-source toolkit for evaluating large multi-modality models
We present VLMEvalKit: an open-source toolkit for evaluating large multi-modality models
based on PyTorch. The toolkit aims to provide a user-friendly and comprehensive framework …
based on PyTorch. The toolkit aims to provide a user-friendly and comprehensive framework …
Vision language models are blind
Large language models (LLMs) with vision capabilities (eg, GPT-4o, Gemini 1.5, and Claude
3) are powering countless image-text processing applications, enabling unprecedented …
3) are powering countless image-text processing applications, enabling unprecedented …
Livebench: A challenging, contamination-free llm benchmark
Test set contamination, wherein test data from a benchmark ends up in a newer model's
training set, is a well-documented obstacle for fair LLM evaluation and can quickly render …
training set, is a well-documented obstacle for fair LLM evaluation and can quickly render …