Microsoft

Detecting backdoored language models at scale

Learn how Microsoft research uncovers backdoor risks in language models and introduces a practical scanner to detect ...
Live Science

In the search for bees, Mozambique honey hunters and birds share a language with distinct, regional dialects

People searching for honey in Mozambique work with birds via a shared language in a rare case of cooperation between humans ...
IEEE

One-Stream Stepwise Decreasing for Vision-Language Tracking

Abstract: Based on the fixed language descriptions in the initial frames, a vision-language tracker typically adopts a two-stream model structure to align vision and language features at the feature ...
CounterPunch

Spotting Conspiracy Talk: A Linguistic Guide for the Digital Age

While we may be most familiar with modern-day conspiracy theories about government intelligence, unidentified flying objects, ...
GitHub

Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models

Sparse Autoencoders (SAEs) have recently gained attention as a means to improve the interpretability and steerability of Large Language Models (LLMs), both of which are essential for AI safety. In ...
U.S. News & World Report

Study Finds Human Language Processing Mirrors How AI Understands Words

Study Finds Human Language Processing Mirrors How AI Understands Words THURSDAY, Jan. 22, 2026 (HealthDay News) — The human brain may understand spoken language in a way that is surprisingly similar ...
IEEE

Exploiting Shared Adversarial Features for Dynamic Attacks in Large Vision-Language Models

Abstract: With the rapid development of Large Language Models (LLMs), an increasing number of Large Visual-Language Models (LVLMs) have achieved unprecedented performance in response generation.