Quantization of LLMs

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TileFuse: A Fused Mixed-Precision Kernel Library for Efficient Quantized LLM Inference on AMD NPUs

 🔧Systems-level optimizations for LLM serving  Content type: Academic
arxiv.org·
Less-relevant results

Train Models Faster with JAX and MaxText Using NVFP4 on NVIDIA Blackwell

 🧠Large Language Models (LLMs)  Content type: News  Content type: Blog
developer.nvidia.com·

Decision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents

 Model optimizations in LLMs  Content type: Academic
arxiv.org·

Holding the FP8 Quality Ceiling at 8-Bit Weights and Activations: INT8 and GGUF Post-Training Quantization of Ideogram 4.0 for Consumer GPUs

 Model optimizations in LLMs  Content type: Academic
arxiv.org·

Beyond Generative Decoding: Discriminative Hidden-State Readout from a Native Omni-Modal LLM for Multimodal Sentiment Analysis

 Model optimizations in LLMs  Content type: Academic
arxiv.org·

Automated IEP Generation from Traditional Chinese Parent-Teacher Interviews via Corpus-Grounded Feature Diffusion

 🧠Large Language Models (LLMs)  Content type: Academic
arxiv.org·

Semantic Grading of Written Answers in Low-Resource Language Bangla Using a Fine-Tuned Lightweight Language Model

 Model optimizations in LLMs  Content type: Academic
arxiv.org·

RedditPersona: A Modular Framework for Community-Conditioned LLM Adaptation from Reddit

 Model optimizations in LLMs  Content type: Academic
arxiv.org·

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