15 citations · 88 across the 61 of their papers we have counts for
75 papers
The Effect of Layer Ordering in Hybrid Architectures
John Cooper, Mingchen Ma, Jiaqi Mo +4
Hybrid attention is rapidly becoming the dominant architectural choice for frontier models. Despite their successes, such architectures complicate model design by introducing addit…
Training LLMs for Multi-Agent Collaboration with Verifiable Information Rewards
Keru Chen, Sen Lin, Yingbin Liang +2
Effective collaboration among large language model (LLM) agents in multi-agent systems requires sharing relevant evidence, requesting missing information, and incorporating teammat…
BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment
Kemal Davaslioglu, Nathan Conger, Sastry Kompella +2
We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavioral health settings such as sui…
Foundation Model-Aided Multi-Agent Reinforcement Learning for Wireless Random Access Network Optimization
Myeung Suk Oh, Zhiyao Zhang, Alvaro Velasquez +2
Random access (RA) is one of the most foundational medium access control (MAC) layer scheduling schemes for handling unpredictable data traffic from multiple terminals. While multi…
Towards Hierarchical Cyber Defense with Large Language Models: From Planning to Execution
Harshith Doppalapudi, Nathaniel D. Bastian, Ankit Shah
An autonomous cyber defender trained with reinforcement learning (RL) is typically tied to the network on which it was trained, limiting its ability to generalize as network scale…
No One Architecture Fits All: A Cross-Environment Evaluation of Hierarchical Red Team Agents
Ayan Javeed Shaikh, Arunesh Sinha, Nathaniel D. Bastian +1
Autonomous red team agents increasingly stress-test AI-enabled cyber defenses by planning strategy and executing multistage attacks. Reinforcement learning (RL) and large language…
Privacy Foundations for Multi-Institutional Scientific Artificial Intelligence
Olivera Kotevska, Sumit Jha, Aur'elien Bellet +6
Scientific artificial intelligence (AI), spanning foundation models (FMs) to federated data-analysis pipelines, is becoming shared infrastructure across national laboratories, univ…
To Solve Bilevel Optimization with Nonconvex Lower Levels, We Need Second-Order Stationarity
Zhiyao Zhang, Menglu Yu, Alvaro Velasquez +2
Although bilevel optimization (BLO) has emerged as a powerful framework for addressing many complex and nested machine learning problems in recent years, most existing studies are…
MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks
Keru Chen, Sen Lin, Yingbin Liang +2
Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality persistently degrades. Such gra…
CUSP: Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoning
Chung-En Johnny Yu, David Garcia, Brian Jalaian +1
Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the aggregated answer measures re…
Trust-Aware Sequential Decision Making and Rollout Planning for Resilient Multi-Robot Systems
Roee M. Francos, Daniel Garces, Orhan Eren Akgün +2
Sequential decision-making in multi-robot systems typically assumes that planning information is reliable and that agents execute the actions anticipated by the planner. Compromise…
Consilience: Conformally Calibrated Communication Control for Hidden-Profile Multi-Agent Reasoning
Abhijith Babu, Ramneet Kaur, Vishal Pramanik +7
Multi-agent LLM systems can improve reasoning by pooling diverse perspectives, but their effectiveness depends on coordinating communication, particularly in hidden-profile setting…
Vector Symbolic Policy Gradient
Ryozo Masukawa, Sanggeon Yun, SungHeon Jeong +6
We answer this question with Vector-Symbolic Policy Gradient (VSPG), a discrete-action actor that represents each action by a unit-norm hypervector and scores it by similarity to t…
Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)
Ryozo Masukawa, Ian Bryant, Armita Kazeminajafabadi +6
Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost exclusively against static, h…
Differentiable Policy Transport over Multi-Layer Network Feasibility Geometry
Zuyuan Zhang, Zeyu Fang, Mahdi Imani +2
Learning-based control is increasingly central to automating network operations. A learned policy, however, must satisfy cross-layer constraints on interference, power-rate couplin…
HiComm: Hierarchical Communication for Multi-agent Reinforcement Learning
Runze Zhao, Dongruo Zhou, Sumit Kumar Jha +2
Cooperative multi-agent reinforcement learning (MARL) often relies on communication to mitigate partial observability, yet most existing protocols treat messages as flat dense vect…
Synthetic Network Packet Generation through Statistical Learning and Genetic Algorithms
Mayank Raj, Nathaniel D. Bastian, Lance Fiondella +1
Developing robust intrusion detection systems (IDS) for IoT environments requires large, labeled datasets capturing realistic traffic distributions across both benign and malicious…
Categorical Robustness Assessment for Machine Learning based Network Intrusion Detection Systems
Mayank Raj, Nathaniel D. Bastian, Lance Fiondella +1
Network Intrusion Detection Systems (NIDS) heavily utlize Machine Learning (ML) but ML models can be manipulated via adversarial attacks. These attacks add carefully crafted pertur…
Closed-Loop Neural Activation Control in Vision-Language-Action Models
Abhijith Babu, Ramneet Kaur, Nathaniel D. Bastian +5
Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use a fixed steering coefficient…
A Red Teaming Framework for Evaluating Robustness of AI-enabled Security Orchestration, Automation, and Response Systems
Ayan Javeed Shaikh, Nathaniel D. Bastian, Ankit Shah
AI-enabled Security Orchestration, Automation, and Response (SOAR) systems increasingly employ autonomous agents for cyber defense, yet their resilience to adaptive adversaries is…
Interactive Critique-Revision Training for Reliable Structured LLM Generation
Fei Xu Yu, Zuyuan Zhang, Mahdi Imani +2
In structured decision-making workflows such as form filling, compliance checking, and maintenance reporting, LLM outputs must be locally correct, globally consistent, and auditabl…
Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization
Zhiqi Gao, Albert Ge, Alexander Berenbeim +2
Text-to-optimization requires two separable capabilities: modeling -- choosing the right optimization structure -- and binding -- grounding every coefficient, index, and parameter…
Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs
Vishal Pramanik, Maisha Maliha, Nathaniel D. Bastian +1
Attribution methods seek to explain language model predictions by quantifying the contribution of input tokens to generated outputs. However, most existing techniques are designed…
ShieldNet: Network-Level Guardrails against Emerging Supply-Chain Injections in Agentic Systems
Zhuowen Yuan, Zhaorun Chen, Zhen Xiang +5
Existing research on LLM agent security mainly focuses on prompt injection and unsafe input/output behaviors. However, as agents increasingly rely on third-party tools and MCP serv…