Topic: state

Researchers have developed a Modality Discrepancy Transformer to recognize ambivalence and hesitancy by detecting inconsistencies across facial, vocal, and linguistic cues in clinical videos, addressing the need for accurate multi-channel analysis in psychological assessments.

arxiv.org↗

The ggml/llama.cpp project released a new version addressing issues with split states and granularity for fused QKV gemm operations, crucial for models like Qwen35. This update ensures correct handling of attention layers when using specific configurations, enhancing the model's performance and accuracy.

LLMs process minor typographical errors without altering the intended meaning, but detection tools designed to spot potential malicious inputs fail to account for these common variations, highlighting a significant oversight in security probe methodologies.

arxiv.org↗

The study argues that while independent evaluation is crucial to rejecting harmful updates, it should not hinder the continual learning process for embodied agents. It suggests assessing update admission based on both error control and preserving learning opportunities within a set interaction limit.

arxiv.org↗

NousResearch released Hermes Agent v0.21.2 on September 11, 2026, addressing issues with the `state.db` file from a previous update that caused instability in some installations.

OpenAI and the General Services Administration are providing discounted access to AI tools and enhanced cyber defense support for government entities at reduced costs. This initiative aims to bolster cybersecurity and expand AI capabilities across federal, state, local, and tribal governments.

Nathan Lambert and Sebastian Raschka, machine learning experts, discuss the state of artificial intelligence in 2026, focusing on large language models, coding advancements, scaling laws, China's role, autonomous agents, GPU technology, and the potential for general AI. The discussion highlights key trends and challenges shaping AI development globally.