How DeepSeek’s DSpark Makes LLMs 85% Faster Without Retraining

DeepSeek has introduced DSpark, an open-source speculative decoding method that accelerates LLM inference by up to 85% ...
Tech Times

NVIDIA’s New LLM Decodes 6x More Tokens Without an Auxiliary Draft Model

NVIDIA Nemotron-Labs-Diffusion is a new tri-mode language model that eliminates the separate draft model in speculative ...
NBC Sports

Argentina 2-0 Austria: Messi breaks all-time scoring record with two more goals

Lionel Messi dazzled once again as Argentina beat Austria 2-0 in Dallas on Monday, as the legendary forward became the all-time leading goalscorer in World Cup history as he led Argentina into the ...
XDA Developers on MSN

I tested Google's new Gemma 4 12B on my 8GB GPU, and now I don't want to go back to smaller models

Not bad for limited hardware ...
GitHub

granulon_awakening_pixel-level_visual_encoders_with_adaptive_multi-granularity_s.md

Granulon enhances pixel-level visual encoders (represented by DINOv3)—which excel at details but lack coarse-grained semantic abstraction—with a "text-conditioned granularity controller + adaptive ...
GitHub

Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders

Penguin-VL is a compact vision-language model family built to study how far multimodal efficiency can be pushed by redesigning the vision encoder, rather than only scaling data or model size.
IEEE

A Systematic Comparison of Text and Image Encoders for Visual Question Answering: From RNN to LLM-Based Representations

Abstract: This study presents a systematic comparative analysis of text and image encoder combinations for Visual Question Answering (VQA) using the EasyVQA dataset. We evaluate six text encoders ...