LogLLM: Leveraging Large Language Models for Improved Log-Based Anomaly Detection
Log-based anomaly detection has become essential to improve software system reliability by identifying problems from log data. However, traditional deep ...
Tag: language
Duo-LLM: A Framework for Studying Adaptive Computing in Large Language Models
This paper was accepted into the Efficient Natural Speech and Language Processing (ENLSP) Workshop at NeurIPS 2024. Large language models ...
Meet LLaVA-o1: the first visual language model capable of systematic and spontaneous reasoning similar to GPT-o1
The development of vision-language models (VLM) has faced challenges in handling complex visual question answering tasks. Despite substantial advances in ...
Recurrent editor for fast speculative decoding on large language models
Introducing Recurrent Drafter (ReDrafter), an advanced speculative decoding approach that achieves state-of-the-art acceleration for large language model (LLM) inference. The ...
H-DPO: Advancing language model alignment through entropy control
Large language models (LLMs) have demonstrated exceptional capabilities in various applications, but their widespread adoption faces significant challenges. The main ...
Why AI language models remain vulnerable: Key insights from Kili Technology's report on large language model vulnerabilities
Kili technology recently published a detailed report report highlighting significant vulnerabilities in ai language modelsfocusing on their susceptibility to pattern-based ...
How modular bricks are revolutionizing the efficiency of large language models
Large language models (LLMs) have revolutionized natural language processing by offering sophisticated capabilities for a variety of applications. However, these ...
Nexa AI Launches OmniVision-968M – World's Smallest Vision Language Model with 9x Token Reduction for Edge Devices
Edge ai has long faced the challenge of balancing efficiency and effectiveness. Deploying vision language models (VLMs) on edge devices ...
Salesforce AI Research Introduces LaTRO: A Self-Rewarding Framework for Improving Reasoning Capabilities in Large Language Models
Large language models (LLMs), useful for answering questions and generating content, are now being trained to handle tasks that require ...
Snowflake and CMU researchers present SuffixDecoding: a new model-free approach to accelerate large language model (LLM) inference using speculative decoding
Large Language Models (LLM) have quickly become a critical component of today's consumer and enterprise applications. However, the need for ...
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