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Found 10 papers, 4 papers with code
Argumentation-Driven Evidence Association in Criminal Cases
Evidence association in criminal cases is dividing a set of judicial evidence into several non-overlapping subsets, improving the interpretability and legality of conviction.
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors
There is a positive correlation between PSR scores and ASR performance, suggesting that phonetic information extracted by monolingual SSL models can be used for downstream tasks in cross-lingual settings.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Formality Style Transfer with Shared Latent Space
Conventional approaches for formality style transfer borrow models from neural machine translation, which typically requires massive parallel data for training.
Identifying Principals and Accessories in a Complex Case based on the Comprehension of Fact Description
In this paper, we study the problem of identifying the principals and accessories from the fact description with multiple defendants in a criminal case.
Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer
Formality text style transfer plays an important role in various NLP applications, such as non-native speaker assistants and child education.
Interpretable Rationale Augmented Charge Prediction System
This paper proposes a neural based system to solve the essential interpretability problem existing in text classification, especially in charge prediction task.
CRST: a Claim Retrieval System in Twitter
For controversial topics, collecting argumentation-containing tweets which tend to be more convincing will help researchers analyze public opinions.
Joker at SemEval-2018 Task 12: The Argument Reasoning Comprehension with Neural Attention
This paper describes a classification system that participated in the SemEval-2018 Task 12: The Argument Reasoning Comprehension Task.
Interpretable Charge Predictions for Criminal Cases: Learning to Generate Court Views from Fact Descriptions
In this paper, we propose to study the problem of COURT VIEW GENeration from the fact description in a criminal case.
Jointly Extracting Relations with Class Ties via Effective Deep Ranking
Exploiting class ties between relations of one entity tuple will be promising for distantly supervised relation extraction.
