AI News

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
AI News

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

April 22, 2025 CryptoExpert

LLMs show impressive capabilities across numerous applications, yet they face challenges due to computational demands and memory requirements. This challenge is acute in scenarios requiring local deployment for privacy concerns, such as processing sensitive patient […]

LLMs Can Now Solve Challenging Math Problems with Minimal Data: Researchers from UC Berkeley and Ai2 Unveil a Fine-Tuning Recipe That Unlocks Mathematical Reasoning Across Difficulty Levels
AI News

LLMs Can Now Solve Challenging Math Problems with Minimal Data: Researchers from UC Berkeley and Ai2 Unveil a Fine-Tuning Recipe That Unlocks Mathematical Reasoning Across Difficulty Levels

April 19, 2025 CryptoExpert

Language models have made significant strides in tackling reasoning tasks, with even small-scale supervised fine-tuning (SFT) approaches such as LIMO and s1 demonstrating remarkable improvements in mathematical problem-solving capabilities. However, fundamental questions remain about these […]