2 citations · 5 across the 14 of their papers we have counts for
15 papers
Uncensored Open-weight Models: Redistribution as the Persistence Layer
10a Labs, :, Juliette Garcia +7
A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key producers, downstream reprod…
When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network
10a Labs, :, Grace Cheong +22
AI agents are increasingly interacting within shared online environments, creating new operational security risks. We analyze activity on Moltbook, a Reddit-style social platform w…
Personalized Face Privacy Protection From a Single Image
Zachary Yahn, Fatih Ilhan, Tiansheng Huang +5
Photos of faces uploaded online are vulnerable to malicious actors who can scrape facial images from online sources and intrude on personal privacy via unauthorized use of facial r…
TinyNina: A Resource-Efficient Edge-AI Framework for Sustainable Air Quality Monitoring via Intra-Image Satellite Super-Resolution
Prasanjit Dey, Zachary Yahn, Bianca Schoen-Phelan +1
Nitrogen dioxide (NO) is a primary atmospheric pollutant and a significant contributor to respiratory morbidity and urban climate-related challenges. While satellite platforms…
Attention-aware Inference Optimizations for Large Vision-Language Models with Memory-efficient Decoding
Fatih Ilhan, Gaowen Liu, Ramana Rao Kompella +5
Large Vision-Language Models (VLMs) have achieved remarkable success in multi-modal reasoning, but their inference time efficiency remains a significant challenge due to the memory…
A Multi-Agent Perception-Action Alliance for Efficient Long Video Reasoning
Yichang Xu, Gaowen Liu, Ramana Rao Kompella +6
This paper presents a multi-agent perception-action exploration alliance, dubbed A4VL, for efficient long-video reasoning. A4VL operates in a multi-round perception-action explorat…
Large Language Model based Smart Contract Auditing with LLMBugScanner
Yining Yuan, Yifei Wang, Yichang Xu +3
This paper presents LLMBugScanner, a large language model (LLM) based framework for smart contract vulnerability detection using fine-tuning and ensemble learning. Smart contract a…
Adversarial Attention Perturbations for Large Object Detection Transformers
Zachary Yahn, Selim Furkan Tekin, Fatih Ilhan +5
Adversarial perturbations are useful tools for exposing vulnerabilities in neural networks. Existing adversarial perturbation methods for object detection are either limited to att…
A Neurosymbolic Agent System for Compositional Visual Reasoning
Yichang Xu, Gaowen Liu, Ramana Rao Kompella +5
The advancement in large language models (LLMs) and large vision models has fueled the rapid progress in multi-modal vision-language reasoning capabilities. However, existing visio…
Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable
Tiansheng Huang, Sihao Hu, Fatih Ilhan +4
Safety alignment is an important procedure before the official deployment of a Large Language Model (LLM). While safety alignment has been extensively studied for LLM, there is sti…
Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents
Selim Furkan Tekin, Fatih Ilhan, Gaowen Liu +2
The advancement of LLMs and their accessibility have triggered renewed interest in multi-agent reinforcement learning as robust and adaptive frameworks for dynamically changing env…
Rapid Automated Mapping of Clouds on Titan With Instance Segmentation
Zachary Yahn, Douglas M Trent, Ethan Duncan +3
Despite widespread adoption of deep learning models to address a variety of computer vision tasks, planetary science has yet to see extensive utilization of such tools to address i…
H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMs
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +4
The alignment of pre-trained LLMs continues to draw significant attention from both industry and academia, aiming to ensure responses that are helpful, harmless, and honest. Howeve…
Data Poisoning and Leakage Analysis in Federated Learning
Wenqi Wei, Tiansheng Huang, Zachary Yahn +3
Data poisoning and leakage risks impede the massive deployment of federated learning in the real world. This chapter reveals the truths and pitfalls of understanding two dominating…
Feature Extraction and Classification from Planetary Science Datasets enabled by Machine Learning
Conor Nixon, Zachary Yahn, Ethan Duncan +9
In this paper we present two examples of recent investigations that we have undertaken, applying Machine Learning (ML) neural networks (NN) to image datasets from outer planet miss…