arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon…
Tag: AI
Bridging Modalities on the Cortex: Surface-based MRI to PET Translation with a Diffusion Bridge
arXiv:2609.20147v1 Announce Type: cross Abstract: Cortical hypometabolism measured by Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a…
Anthropic Taps Accenture’s Faculty for Embedded AI Model Evaluation
Anthropic said on September 18, 2026 that it is partnering with Accenture on independent evaluation of frontier AI, with each company expecting to invest…
QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization
arXiv:2609.20156v1 Announce Type: cross Abstract: Ubiquitous time series data across diverse domains enables critical applications in areas such as…
Partnering with Accenture on embedded evaluation
We’re partnering with Accenture on independent evaluation of frontier AI. This is an important step toward the commitment, made in our CEO’s essay “We…
VLN on the Fly: An Onboard Vision-Language Navigation Stack for Aerial Robots
arXiv:2609.20191v1 Announce Type: cross Abstract: Running vision-language navigation fully onboard an aerial robot is hard, since grounding, planning, and…
World model companies are keeping a lot of secrets
Everyone in the world-models space is sitting on a pile of cash and a ton of buzz, but good luck getting anyone — from the founders to their own data…
Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants
arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling.…
Local Sparsity Enables Unsupervised LLM Safety Detection
arXiv:2609.20129v1 Announce Type: cross Abstract: Deployment-time safety methods for large language models (LLMs) are predominantly supervised and assume…
Cross-Modal Attention Acts as a Frequency Filter: Why Verbose Prompts Improve Robustness in Vision-Language Models
arXiv:2609.20139v1 Announce Type: cross Abstract: Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the…