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Found 8 papers, 3 papers with code
Large Language Model Prompt Chaining for Long Legal Document Classification
Prompting is used to guide or steer a language model in generating an appropriate response that is consistent with the desired outcome.
Legal Prompt Engineering for Multilingual Legal Judgement Prediction
Legal Prompt Engineering (LPE) or Legal Prompting is a process to guide and assist a large language model (LLM) with performing a natural legal language processing (NLLP) skill.
Active Learning for Argument Mining: A Practical Approach
Despite considerable recent progress, the creation of well-balanced and diverse resources remains a time-consuming and costly challenge in Argument Mining.
Aspect-Based Argument Mining
In this work, we are presenting the task of Aspect-Based Argument Mining (ABAM), with the essential subtasks of Aspect Term Extraction (ATE) and Nested Segmentation (NS).
Multipurpose Intelligent Process Automation via Conversational Assistant
Such intelligent agents can assist the user by answering specific questions and executing routine tasks that are ordinarily performed in a natural language (i. e., customer support).
Domain adaptation for part-of-speech tagging of noisy user-generated text
We propose an architecture that trains an out-of-domain model on a large newswire corpus, and transfers those weights by using them as a prior for a model trained on the target domain (a data-set of German Tweets) for which there is very little an-notations available.
Fine-Grained Argument Unit Recognition and Classification
In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.
