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Found 14 papers, 8 papers with code
On the Machine Learning of Ethical Judgments from Natural Language
Ethics is one of the longest standing intellectual endeavors of humanity.
Towards Explainability in Legal Outcome Prediction Models
Current legal outcome prediction models - a staple of legal NLP - do not explain their reasoning.
The Ethics of Automating Legal Actors
The introduction of large public legal datasets has brought about a renaissance in legal NLP.
The Architectural Bottleneck Principle
This shift in perspective leads us to propose a new principle for probing, the architectural bottleneck principle: In order to estimate how much information a given component could extract, a probe should look exactly like the component.
An Ordinal Latent Variable Model of Conflict Intensity
It is based only on the action category ("what") and disregards the subject ("who") and object ("to whom") of an event, as well as contextual information, like associated casualty count, that should contribute to the perception of an event's "intensity".
Prompting for a conversation: How to control a dialog model?
Dialog modelling faces a difficult trade-off.
On the Role of Negative Precedent in Legal Outcome Prediction
In contrast, we turn our focus to negative outcomes here, and introduce a new task of negative outcome prediction.
Benchmarking Compositionality with Formal Languages
Recombining known primitive concepts into larger novel combinations is a quintessentially human cognitive capability.
UniMorph 4.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
A Word on Machine Ethics: A Response to Jiang et al. (2021)
Ethics is one of the longest standing intellectual endeavors of humanity.
Analyzing Neural Discourse Coherence Models
In this work, we systematically investigate how well current models of coherence can capture aspects of text implicated in discourse organisation.
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.
A Tale of a Probe and a Parser
One such probe is the structural probe (Hewitt and Manning, 2019), designed to quantify the extent to which syntactic information is encoded in contextualised word representations.
Information-Theoretic Probing for Linguistic Structure
The success of neural networks on a diverse set of NLP tasks has led researchers to question how much these networks actually ``know'' about natural language.
