1 citations · 3 across the 6 of their papers we have counts for
6 papers
Llama-3.1-FoundationAI-SecurityLLM-Reasoning-8B Technical Report
Zhuoran Yang, Ed Li, Jianliang He +18
We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model (derived fro…
Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report
Sajana Weerawardhena, Paul Kassianik, Blaine Nelson +14
Large language models (LLMs) have shown remarkable success across many domains, yet their integration into cybersecurity applications remains limited due to a lack of general-purpo…
Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report
Paul Kassianik, Baturay Saglam, Alexander Chen +15
As transformer-based large language models (LLMs) increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts.…
Adversarial Attacks on Binary Image Recognition Systems
Eric Balkanski, Harrison Chase, Kojin Oshiba +3
We initiate the study of adversarial attacks on models for binary (i.e. black and white) image classification. Although there has been a great deal of work on attacking models for…
Predicting Choice with Set-Dependent Aggregation
Nir Rosenfeld, Kojin Oshiba, Yaron Singer
Providing users with alternatives to choose from is an essential component in many online platforms, making the accurate prediction of choice vital to their success. A renewed inte…
Robust Classification of Financial Risk
Suproteem K. Sarkar, Kojin Oshiba, Daniel Giebisch +1
Algorithms are increasingly common components of high-impact decision-making, and a growing body of literature on adversarial examples in laboratory settings indicates that standar…