2 citations · 3 across the 7 of their papers we have counts for
8 papers
TokenEconomizer: Experience-Driven Black-Box Cost Control for Coding Agents
Aaron J. Li, Weijia Xu, Chandan Singh +8
Advances in frontier coding agents have sharply increased the token costs of AI-assisted software engineering. Their token efficiency is typically evaluated on isolated tasks, wher…
Data-Efficient Adaptation of LLMs via Attention Head Reweighting
Tuomas Oikarinen, Zixiao Chen, Charlotte Siska +3
Learning effectively from limited data is critical in domains like security where labeled examples are scarce. Large language models (LLMs) have demonstrated some capabilities for…
Secret Scanner Agent: Extracting Secrets and Access Context from Unstructured Documents
Zixiao Chen, Mariko Wakabayashi, Charlotte Siska
Exposed documents such as emails, chat threads, tickets, and incident notes routinely leak credentials, but during incident response a leaked secret is only half the story. Respond…
CORPGEN: Simulating Corporate Environments with Autonomous Digital Employees in Multi-Horizon Task Environments
Abubakarr Jaye, Nigel Boachie Kumankumah, Chidera Biringa +8
Long-horizon reasoning is a key challenge for autonomous agents, yet existing benchmarks evaluate agents on single tasks in isolation. Real organizational work requires managing ma…
OMNIGUARD: An Efficient Approach for AI Safety Moderation Across Languages and Modalities
Sahil Verma, Keegan Hines, Jeff Bilmes +4
The emerging capabilities of large language models (LLMs) have sparked concerns about their immediate potential for harmful misuse. The core approach to mitigate these concerns is…
AttentionDefense: Leveraging System Prompt Attention for Explainable Defense Against Novel Jailbreaks
Charlotte Siska, Anush Sankaran
In the past few years, Language Models (LMs) have shown par-human capabilities in several domains. Despite their practical applications and exceeding user consumption, they are sus…
PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System
Gary D. Lopez Munoz, Amanda J. Minnich, Roman Lutz +17
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both s…
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks
Melissa Ailem, Katerina Marazopoulou, Charlotte Siska +1
Benchmarks have emerged as the central approach for evaluating Large Language Models (LLMs). The research community often relies on a model's average performance across the test pr…