papers

Publications (28)

cs.CR2023

GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants

Aamir Hamid, Hemanth Reddy Samidi, Tim Finin +2

Privacy policies of websites are often lengthy and intricate. Privacy assistants assist in simplifying policies and making them more accessible and user friendly. The emergence of…

quant-ph2020

Quantum-Assisted Greedy Algorithms

Ramin Ayanzadeh, Milton Halem, John Dorband +1

We show how to leverage quantum annealers to better select candidates in greedy algorithms. Unlike conventional greedy algorithms that employ problem-specific heuristics for making…

cs.CR2022

CAPD: A Context-Aware, Policy-Driven Framework for Secure and Resilient IoBT Operations

Sai Sree Laya Chukkapalli, Anupam Joshi, Tim Finin +1

The Internet of Battlefield Things (IoBT) will advance the operational effectiveness of infantry units. However, this requires autonomous assets such as sensors, drones, combat equ…

quant-ph2020

An Ensemble Approach for Compressive Sensing with Quantum

Ramin Ayanzadeh, Milton Halem, Tim Finin

We leverage the idea of a statistical ensemble to improve the quality of quantum annealing based binary compressive sensing. Since executing quantum machine instructions on a quant…

cs.CL2017

Understanding the Logical and Semantic Structure of Large Documents

Muhammad Mahbubur Rahman, Tim Finin

Current language understanding approaches focus on small documents, such as newswire articles, blog posts, product reviews and discussion forum entries. Understanding and extractin…

cs.AI2015

Interactive Knowledge Base Population

Travis Wolfe, Mark Dredze, James Mayfield +4

Most work on building knowledge bases has focused on collecting entities and facts from as large a collection of documents as possible. We argue for and describe a new paradigm whe…

quant-ph2022

Quantum-Assisted Greedy Algorithms

Ramin Ayanzadeh, John E Dorband, Milton Halem +1

We show how to leverage quantum annealers (QAs) to better select candidates in greedy algorithms. Unlike conventional greedy algorithms that employ problem-specific heuristics for…

cs.CY2023

A Study of the Landscape of Privacy Policies of Smart Devices

Aamir Hamid, Hemanth Reddy Samidi, Tim Finin +2

As the adoption of smart devices continues to permeate all aspects of our lives, user privacy concerns have become more pertinent than ever. Privacy policies outline the data handl…

cs.IT2019

Quantum Annealing Based Binary Compressive Sensing with Matrix Uncertainty

Ramin Ayanzadeh, Seyedahmad Mousavi, Milton Halem +1

Compressive sensing is a novel approach that linearly samples sparse or compressible signals at a rate much below the Nyquist-Shannon sampling rate and outperforms traditional sign…

cs.IR2023

A Practical Entity Linking System for Tables in Scientific Literature

Varish Mulwad, Tim Finin, Vijay S. Kumar +3

Entity linking is an important step towards constructing knowledge graphs that facilitate advanced question answering over scientific documents, including the retrieval of relevant…

quant-ph2021

Multi-Qubit Correction for Quantum Annealers

Ramin Ayanzadeh, John Dorband, Milton Halem +1

We present \emph{multi-qubit correction} (MQC) as a novel postprocessing method for quantum annealers that views the evolution in an open-system as a Gibbs sampler and reduces a se…

cs.CR2021

Generating Fake Cyber Threat Intelligence Using Transformer-Based Models

Priyanka Ranade, Aritran Piplai, Sudip Mittal +2

Cyber-defense systems are being developed to automatically ingest Cyber Threat Intelligence (CTI) that contains semi-structured data and/or text to populate knowledge graphs. A pot…

quant-ph2020

Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach

Ramin Ayanzadeh, Milton Halem, Tim Finin

We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning…

cs.CL2019

Unfolding the Structure of a Document using Deep Learning

Muhammad Mahbubur Rahman, Tim Finin

Understanding and extracting of information from large documents, such as business opportunities, academic articles, medical documents and technical reports, poses challenges not p…

cs.CL2018

Understanding and representing the semantics of large structured documents

Muhammad Mahbubur Rahman, Tim Finin

Understanding large, structured documents like scholarly articles, requests for proposals or business reports is a complex and difficult task. It involves discovering a document's…

cs.AI2017

Thinking, Fast and Slow: Combining Vector Spaces and Knowledge Graphs

Sudip Mittal, Anupam Joshi, Tim Finin

Knowledge graphs and vector space models are robust knowledge representation techniques with individual strengths and weaknesses. Vector space models excel at determining similarit…

cs.CL2020

Improving Neural Named Entity Recognition with Gazetteers

Chan Hee Song, Dawn Lawrie, Tim Finin +1

The goal of this work is to improve the performance of a neural named entity recognition system by adding input features that indicate a word is part of a name included in a gazett…

cs.AI2026

Deontic Policies for Runtime Governance of Agentic AI Systems

Anupam Joshi, Tim Finin, Karuna Pande Joshi +1

Autonomous agentic AI systems driven by Large Language Models (LLMs) introduce a new class of security, privacy, and compliance challenges: an agent that can invoke tools, manipula…

cs.MA1998

Semantics and Conversations for an Agent Communication Language

Yannis Labrou, Tim Finin

We address the issues of semantics and conversations for agent communication languages and the Knowledge Query Manipulation Language (KQML) in particular. Based on ideas from speec…

cs.CL2018

SURFACE: Semantically Rich Fact Validation with Explanations

Ankur Padia, Francis Ferraro, Tim Finin

Judging the veracity of a sentence making one or more claims is an important and challenging problem with many dimensions. The recent FEVER task asked participants to classify inpu…

cs.CL2022

Recognizing and Extracting Cybersecurtity-relevant Entities from Text

Casey Hanks, Michael Maiden, Priyanka Ranade +2

Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as…

cs.LG2019

Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization

Ankur Padia, Kostantinos Kalpakis, Francis Ferraro +1

We present a family of novel methods for embedding knowledge graphs into real-valued tensors. These tensor-based embeddings capture the ordered relations that are typical in the kn…

cs.CL2023

Jointly Identifying and Fixing Inconsistent Readings from Information Extraction Systems

Ankur Padia, Francis Ferraro, Tim Finin

KGCleaner is a framework to identify and correct errors in data produced and delivered by an information extraction system. These tasks have been understudied and KGCleaner is the…

cs.CR2018

Cognitive Techniques for Early Detection of Cybersecurity Events

Sandeep Narayanan, Ashwinkumar Ganesan, Karuna Joshi +3

The early detection of cybersecurity events such as attacks is challenging given the constantly evolving threat landscape. Even with advanced monitoring, sophisticated attackers ca…

cs.IT2019

SAT-based Compressive Sensing

Ramin Ayanzadeh, Milton Halem, Tim Finin

We propose to reduce the original well-posed problem of compressive sensing to weighted-MAX-SAT. Compressive sensing is a novel randomized data acquisition approach that linearly s…

cs.AI2019

Cyber-All-Intel: An AI for Security related Threat Intelligence

Sudip Mittal, Anupam Joshi, Tim Finin

Keeping up with threat intelligence is a must for a security analyst today. There is a volume of information present in `the wild' that affects an organization. We need to develop…

cs.CL2018

Ontology-Grounded Topic Modeling for Climate Science Research

Jennifer Sleeman, Tim Finin, Milton Halem

In scientific disciplines where research findings have a strong impact on society, reducing the amount of time it takes to understand, synthesize and exploit the research is invalu…

cs.AI2026

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning

Aamir Hamid, Bharg Barot, Satvik Racharla +3

While large language models (LLMs) enable strong question answering (QA), budgeted deployment is complicated by nondeterminism and heterogeneous resource profiles (cost, latency, a…