OpenAI published a framework for tracking, investigating, and disclosing instances of model misalignment on September 16, 2026, alongside six reports on…
Tag: AI
PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control
arXiv:2609.17521v1 Announce Type: cross Abstract: Interactive control for video generation is moving from coarse prompts toward fine-grained, physically…
Decomposition Buys Integrity, Not Yield
arXiv:2609.17464v1 Announce Type: cross Abstract: Multi-agent systems split a task across a tree of agents and justify the split with folklore: smaller…
Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection
arXiv:2609.17479v1 Announce Type: cross Abstract: Despite the rapid uptake of black-box object detectors in marine mammal research and monitoring,…
Evaluating Verified Autonomy in Quantum Engineering
arXiv:2609.17439v1 Announce Type: cross Abstract: Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As…
CareMirror: Bringing Caregiver Wellbeing into the Dementia Care Ecosystem
arXiv:2609.17434v1 Announce Type: cross Abstract: Family caregivers of people living with dementia shoulder emotional and practical responsibilities, yet…
Our framework for reporting model misalignment
OpenAI shares a framework for tracking, investigating, and disclosing model misalignment, alongside six reports of unexpected or concerning model behavior.
Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback
arXiv:2609.17474v1 Announce Type: cross Abstract: Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a…
Where Should a Document Live: Context, Representations, or Parameters?
arXiv:2609.17346v1 Announce Type: cross Abstract: To answer questions outside of their pre-training data, large language models (LLMs) need access to new…
Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging
arXiv:2609.17429v1 Announce Type: cross Abstract: Many learned sequential decision systems map the current state directly to an action. That shortcut…