LLMs Can Now Retain High Accuracy at 2-Bit Precision: Researchers from UNC Chapel Hill Introduce TACQ, a Task-Aware Quantization Approach that Preserves Critical Weight Circuits for Compression Without Performance Loss

LLMs show impressive capabilities across numerous applications, yet they face challenges due to computational demands and memory requirements. This challenge […]

Long-Context Multimodal Understanding No Longer Requires Massive Models: NVIDIA AI Introduces Eagle 2.5, a Generalist Vision-Language Model that Matches GPT-4o on Video Tasks Using Just 8B Parameters

In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation […]