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Found 17 papers, 9 papers with code
A Corpus for Multilingual Analysis of Online Terms of Service
We present the first annotated corpus for multilingual analysis of potentially unfair clauses in online Terms of Service.
Multimodal Argument Mining: A Case Study in Political Debates
We propose a study on multimodal argument mining in the domain of political debates.
Detecting Arguments in CJEU Decisions on Fiscal State Aid
The successful application of argument mining in the legal domain can dramatically impact many disciplines related to law.
TWOLAR: a TWO-step LLM-Augmented distillation method for passage Reranking
In this paper, we present TWOLAR: a two-stage pipeline for passage reranking based on the distillation of knowledge from Large Language Models (LLM).
Fast Vocabulary Transfer for Language Model Compression
Real-world business applications require a trade-off between language model performance and size.
BANANA: a Benchmark for the Assessment of Neural Architectures for Nucleic Acids
Machine learning has always played an important role in bioinformatics and recent applications of deep learning have allowed solving a new spectrum of biologically relevant tasks.
Combining Transformers with Natural Language Explanations
Many NLP applications require models to be interpretable.
Tree-Constrained Graph Neural Networks For Argument Mining
By imposing a series of regularization constraints to the learning problem, we exploit a pooling mechanism that incorporates such notion of fragments within the node soft assignment function that produces the embeddings.
An Argumentative Dialogue System for COVID-19 Vaccine Information
Dialogue systems are widely used in AI to support timely and interactive communication with users.
Multi-Task Attentive Residual Networks for Argument Mining
We explore the use of residual networks and neural attention for multiple argument mining tasks.
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Cross-lingual Annotation Projection in Legal Texts
We study annotation projection in text classification problems where source documents are published in multiple languages and may not be an exact translation of one another.
Memory networks for consumer protection:unfairness exposed
Recent work has demonstrated how data-driven AI methods can leverage consumer protection by supporting the automated analysis of legal documents.
Parallelizing Machine Learning as a Service for the End-User
As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly available to a wide public, allowing end-users to submit queries with their own data, and to efficiently retrieve results.
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning
Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks.
Attention in Natural Language Processing
Attention is an increasingly popular mechanism used in a wide range of neural architectures.
Argumentative Link Prediction using Residual Networks and Multi-Objective Learning
We explore the use of residual networks for argumentation mining, with an emphasis on link prediction.
CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer.
