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Found 18 papers, 9 papers with code
Few-Shot Fairness: Unveiling LLM's Potential for Fairness-Aware Classification
Employing Large Language Models (LLM) in various downstream applications such as classification is crucial, especially for smaller companies lacking the expertise and resources required for fine-tuning a model.
Automated Attribute Extraction from Legal Proceedings
The escalating number of pending cases is a growing concern world-wide.
Nonet at SemEval-2023 Task 6: Methodologies for Legal Evaluation
This paper describes our submission to the SemEval-2023 for Task 6 on LegalEval: Understanding Legal Texts.
Exemplar-Free Continual Transformer with Convolutions
Although there have been some recent CL approaches for vision transformers, they either store training instances of previous tasks or require a task identifier during test time, which can be limiting.
How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?
In addition to standard metrics for summary quality, we check for inconsistencies and hallucinations in the summaries.
Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation
Summarization of legal case judgement documents is a challenging problem in Legal NLP.
Legal Case Document Similarity: You Need Both Network and Text
Our experiments establish that our proposed network-based methods significantly improve the correlation with domain experts' opinion when compared to the existing methods for network-based legal document similarity.
Incorporating Domain Knowledge for Extractive Summarization of Legal Case Documents
Automatic summarization of legal case documents is an important and practical challenge.
Fairness for Whom? Understanding the Reader's Perception of Fairness in Text Summarization
Moreover, standard ROUGE evaluation metrics are unable to quantify the perceived (un)fairness of the summaries.
An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection
To enable tasks such as search/retrieval and classification over all the available data, we need robust algorithms for text normalization, i. e., for cleaning different kinds of noise in the text.
Information Retrieval
Optical Character Recognition (OCR)
+2
ZSCRGAN: A GAN-based Expectation Maximization Model for Zero-Shot Retrieval of Images from Textual Descriptions
Most existing algorithms for cross-modal Information Retrieval are based on a supervised train-test setup, where a model learns to align the mode of the query (e. g., text) to the mode of the documents (e. g., images) from a given training set.
Utilizing Microblogs for Assisting Post-Disaster Relief Operations via Matching Resource Needs and Availabilities
The few prior works that attempted matching only considered the resources, and no attempt has been made to understand other aspects of needs/availabilities that are essential for matching in practice.
Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity
We propose to augment the PCNet with the hierarchy of legal statutes, to form a heterogeneous network Hier-SPCNet, having citation links between case documents and statutes, as well as citation and hierarchy links among the statutes.
NARMADA: Need and Available Resource Managing Assistant for Disasters and Adversities
Although a lot of research has been done on utilising Online Social Media during disasters, there exists no system for a specific task that is critical in a post-disaster scenario -- identifying resource-needs and resource-availabilities in the disaster-affected region, coupled with their subsequent matching.
Methods for Computing Legal Document Similarity: A Comparative Study
Computing similarity between two legal documents is an important and challenging task in the domain of Legal Information Retrieval.
Identification of Rhetorical Roles of Sentences in Indian Legal Judgments
Automatically understanding the rhetorical roles of sentences in a legal case judgement is an important problem to solve, since it can help in several downstream tasks like summarization of legal judgments, legal search, and so on.
Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries
Specifically, considering that an extractive summarization algorithm selects a subset of the textual units (e. g. microblogs) in the original data for inclusion in the summary, we investigate whether this selection is fair or not.
Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora
The proposed method is superior to the state-of-the-art method not only for IR evaluation measures but also in terms of time requirements.
