NLI Model

Natural Language Inference (NLI) models aim to determine the logical relationship (entailment, contradiction, or neutral) between pairs of sentences. Current research emphasizes improving model robustness and addressing biases, particularly through techniques like chain-of-thought prompting, continual learning, and causal effect estimation to understand model reasoning. This work is crucial for enhancing the reliability and trustworthiness of NLP systems across diverse applications, including healthcare and data analysis, where accurate and explainable inferences are paramount.