Psychology Today

Anomaly Puzzles: How the Brain Detects the Unexpected

These short anomaly-detection puzzles are designed to illustrate how reasoning often depends on identifying inconsistencies ...
Psychology Today

Very Awkward: AI Prompt Slips in the Age of 'Chatfishing'

People are increasing "chatfishing," using AI apps to generate texts to their romantic interests. Sometimes they'll slip up ...
Tech Times

Speech Recognition Accuracy Score Hides Its Worst Errors: Semantic Metrics Offer a Fix

Speech recognition accuracy benchmarks report low error rates while leaving the most critical words wrong. Researchers now ...

Dozens of states could face new costs because of high error rates in SNAP food aid

Several dozen states might need to pay millions for food aid if they don't reduce errors in the Supplemental Nutrition ...
Investopedia

Understanding Rounding Errors: Causes, Consequences, and Examples

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
GitHub

[CVPR 2026] Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients

Ziwei Xiang*, Fanhu Zeng*, Hongjian Fang*, Rui-Qi Wang, Renxing Chen, Yanan Zhu, Yi Chen, Peipei Yang, Xu-Yao Zhang TL;DR: We introduce a fine-grained post-training quantization method for large ...
IEEE

Towards Accurate Post-Training Quantization of Vision Transformers via Error Reduction

Abstract: Post-training quantization (PTQ) for vision transformers (ViTs) has received increasing attention from both academic and industrial communities due to its minimal data needs and high time ...