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Found 8 papers, 3 papers with code
Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents
The FinCausal 2020 shared task aims to detect causality on financial news and identify those parts of the causal sentences related to the underlying cause and effect.
Generating Prototypes for Contradiction Detection Using Large Language Models and Linguistic Rules
We introduce a novel data generation method for contradiction detection, which leverages the generative power of large language models as well as linguistic rules.
Improving Zero-Shot Text Matching for Financial Auditing with Large Language Models
Auditing financial documents is a very tedious and time-consuming process.
Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training
This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contradiction Detection (CD).
sustain.AI: a Recommender System to analyze Sustainability Reports
We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies' sustainability reports.
Towards Linguistically Informed Multi-Objective Pre-Training for Natural Language Inference
We introduce a linguistically enhanced combination of pre-training methods for transformers.
Zero-Shot Text Matching for Automated Auditing using Sentence Transformers
Natural language processing methods have several applications in automated auditing, including document or passage classification, information retrieval, and question answering.
A Linguistic Investigation of Machine Learning based Contradiction Detection Models: An Empirical Analysis and Future Perspectives
We analyze two Natural Language Inference data sets with respect to their linguistic features.
