arXiv:2609.28940v1 Announce Type: cross Abstract: Autonomous penetration-testing harnesses use large language models (LLMs) for reconnaissance,…
Category: AI
Meta’s Muse just stole the AI spotlight from OpenAI and Anthropic
When AI leaders at OpenAI and Anthropic started talking about “pacing the frontier,” maybe someone should have asked: what pace? Now it’s turned into…
Design and Evaluation of LLM Chaining-Based Task Planning for General Purpose Service Robots
arXiv:2609.29043v1 Announce Type: cross Abstract: General Purpose Service Robot (GPSR) tasks, as defined in the RoboCup@Home benchmark, require robots to…
Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications
arXiv:2609.28843v1 Announce Type: cross Abstract: Blockchain and artificial intelligence (AI) are converging into a single infrastructural layer for…
Persuaded, Not Informed: Incentive-Misaligned Witnesses Defeat In-Context Grounding
arXiv:2609.28854v1 Announce Type: cross Abstract: Language-model agents increasingly answer questions over customer-relationship management (CRM) records,…
On the Effectiveness of Kernel-Level Evidence for Agent Security
arXiv:2609.28915v1 Announce Type: cross Abstract: LLM agents are deployed into infrastructure that grants them broad host authority, yet existing…
Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots
arXiv:2609.28910v1 Announce Type: cross Abstract: Effective robot assistance beyond narrow roles and repetitive tasks requires robots to be proactive – to…
Another Google Deepmind researcher quits, says building superintelligent AI soon is “inherently irresponsible”
Google Deepmind researcher Robert O’Callahan has quit, saying AI’s “current rate of change is far too high.” He worked on chip design tools that helped…
Broadening Uncertainty Estimation for Audio Question Answering Across Methods, Formats, and Inputs
arXiv:2609.28879v1 Announce Type: cross Abstract: Audio-language models can produce confident answers unsupported by the audio, motivating uncertainty…
M$^2$PFN: End-to-End Disentangled Alignment for Generalizable Multimodal In-Context Learning in Alzheimer’s Disease
arXiv:2609.28836v1 Announce Type: cross Abstract: While various multimodal methods combining imaging and tabular data for Alzheimer’s disease (AD)…