1 citations · 1 across the 3 of their papers we have counts for
5 papers
SIGMA: Self-Improving Alignment Generalization from a Model Spec
Jingyu Zhang, Shruti Palaskar, Daniel Khashabi +3
LLM agents are increasingly capable of executing complex tasks and of recursively improving themselves on easy-to-verify objectives such as software engineering and mathematics. Si…
Visual Grounding Safety in Vision-Language Models
Erfan Shayegani, Kundan Krishna, Yue Dong +3
Vision-language models (VLMs) are increasingly trained to generate structured outputs like points and bounding boxes that downstream interfaces, agents, and robots can act on, yet…
SafetyPairs: Isolating Safety Critical Image Features with Counterfactual Image Generation
Alec Helbling, Shruti Palaskar, Kundan Krishna +3
What exactly makes a particular image unsafe? Systematically differentiating between benign and problematic images is a challenging problem, as subtle changes to an image, such as…
VLSU: Mapping the Limits of Joint Multimodal Understanding for AI Safety
Shruti Palaskar, Leon Gatys, Mona Abdelrahman +9
Safety evaluation of multimodal foundation models often treats vision and language inputs separately, missing risks from joint interpretation where benign content becomes harmful i…
Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection
Shruti Palaskar, Oggi Rudovic, Sameer Dharur +7
Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performanc…