arXiv NLP research summaries for January 30, 2024.

Today's Research Themes (AI-Generated):

• Scalable meta-evaluation framework ScaleEval leverages LLMs as evaluators through agent debate to ease the workload of human annotators.

• H2O-Danube-1.8B is a competitively performing 1.8B parameter language model trained on 1T tokens, made available under the Apache 2.0 license.

• SVAG, a state-of-the-art framework for low-resource dialogue state tracking, uses prompt learning and self-training to improve state value generation.

• Research on Maltese explores cross-lingual transfer for low-resource languages by training a classifier to process text based on word etymology.

• LLMEA framework integrates knowledge from KGs and LLMs for entity alignment, outperforming current methods on public datasets.