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Found 17 papers, 4 papers with code
A Tale of Two Regulatory Regimes: Creation and Analysis of a Bilingual Privacy Policy Corpus
Over the past decade, researchers have started to explore the use of NLP to develop tools aimed at helping the public, vendors, and regulators analyze disclosures made in privacy policies.
Large Language Models: A New Approach for Privacy Policy Analysis at Scale
The number and dynamic nature of web and mobile applications presents significant challenges for assessing their compliance with data protection laws.
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
Traffic simulators are used to generate data for learning in intelligent transportation systems (ITSs).
ATLAS: Automatically Detecting Discrepancies Between Privacy Policies and Privacy Labels
Among apps that provide both, 88. 0% have at least one possible discrepancy between the text of their privacy policy and their privacy label, which could be indicative of a potential compliance issue.
Creation and Analysis of an International Corpus of Privacy Laws
To examine the status and evolution of this patchwork, we introduce the Government Privacy Instructions Corpus, or GPI Corpus, of 1, 043 privacy laws, regulations, and guidelines, covering 182 jurisdictions.
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality
Traffic signal control (TSC) is a high-stakes domain that is growing in importance as traffic volume grows globally.
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations
Through our evaluation, we observe that for a linear bag-of-words model, participants with access to the feature coefficients during training are able to cause a larger reduction in model confidence in the testing phase when compared to the no-explanation control.
Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
Privacy plays a crucial role in preserving democratic ideals and personal autonomy.
A Mixed Initiative Semantic Web Framework for Process Composition
Semantic Web technologies offer the prospect of significantly reducing the amount of effort required to integrate existing enterprise functionality in support of new composite processes; whether within a given organization or across multiple ones.
Question Answering for Privacy Policies: Combining Computational and Legal Perspectives
The PrivacyQA corpus offers a challenging corpus for question answering, with genuine real-world utility.
Supervised and Unsupervised Methods for Robust Separation of Section Titles and Prose Text in Web Documents
To remedy this, we present a flexible system for automatically extracting the hierarchical section titles and prose organization of web documents irrespective of differences in HTML representation.
Stress Test Evaluation for Natural Language Inference
Natural language inference (NLI) is the task of determining if a natural language hypothesis can be inferred from a given premise in a justifiable manner.
Natural Language Inference
Natural Language Understanding
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Toward Abstractive Summarization Using Semantic Representations
We present a novel abstractive summarization framework that draws on the recent development of a treebank for the Abstract Meaning Representation (AMR).
Abstractive Text Summarization
Abstract Meaning Representation
Identifying the Provision of Choices in Privacy Policy Text
Our techniques enable the creation of systems to help Internet users to learn about their choices, thereby effectuating notice and choice and improving Internet privacy.
