AI safety and alignment

Alignment, interpretability, red-teaming, bias and privacy: the research on what these systems do when they misbehave.

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arXiv Computer Vision
Sep 15

Weakly Supervised Spatial Grounding for Discriminative Attention-Based Ultrasound-Histopathology Alignment in Prostate Cancer Grading

arXiv:2609.15150v1 Announce Type: new Abstract: Unpaired cross-modal distillation transfers grade structure from histopathology into a micro-ultrasound (micro-US) encoder by aligning a pooled needle-...

By Obed Korshie Dzikunu, Emma Willis, Mohammad Mahdi Abootorabi, Mohamed Harmanani, Zhuoxin Guo, Ferdinand Luger, Adam Kinnaird, Brian Wodlinger, Parvin Mousavi, Purang Abolmaesumi
arXiv Computer Vision
Sep 15

Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment

arXiv:2510.23224v2 Announce Type: replace Abstract: The rapid digitization of histopathology slides has opened new opportunities for computational tools in clinical and research workflows. Content-ba...

By Hongyi Wang, Zhengjie Zhu, Junlin Hou, Jiabo Ma, Fang Wang, Yue Shi, Qiuyu Cai, Jili Wang, Bo Luo, Zhizhong Chai, Zhengyu Zhang, Li Liang, Xiuming Zhang, Yen-Wei Chen, Lanfen Lin, Hao Chen
arXiv AI
Sep 15

An Efficient and Modular Framework for Targeted Harm Mitigation in LLMS

The paper introduces a modular correction framework for large language models that uses Activated LoRA adapters and a context-aware routing mechanism to mitigate harmful outputs. By allowing expert adapters to activate mid-sequence without invalidating the KV cache, the system achieves low-latency, targeted correction during generation. Experiments show improved alignment on safety benchmarks while maintaining task performance, presenting a lightweight, scalable approach to safer LLM deployments.

By Roberto Campbell, Momin Abbass, Muneeza Azmat, Michal Ulewicz, Raya Horesh, Kristjan Greenewald, Rog\'erio Abreu de Paula, Nathalie Baracaldo
arXiv AI
Sep 15

Toward a Decision-Assurance Layer for AI-Assisted Flight Planning in Air Traffic Management

arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation...

By Alexandre Barreto (George Mason University), Shou Matsumoto (George Mason University), Jorge Valverde-Rebaza (Tecnol\'ogico de Monterrey), Cleiton Ataide (DECEA: Department of Airspace Control), Paulo Costa (George Mason University)