The article introduces DIALIGHT, a toolkit for developing and evaluating multilingual Task-Oriented Dialogue (TOD) systems. The toolkit facilitates systematic evaluations and comparisons between TOD systems that use fine-tuning of Pretrained…
Continue readingThe study addresses the challenge of efficiently combining foundational models with more specific models to enhance their capabilities. CALM Composition is proposed, which introduces cross-attention between models to compose their…
Continue readingThe study explores the use of Large Language Models (LLMs) in the medical domain, particularly their effectiveness and robustness in semantic search tasks. It constructs a textual dataset based on…
Continue readingThis academic article by Anshuman Chhabra, Hadi Askari, and Prasant Mohapatra explores the concept of position bias in large language models (LLMs) and its influence on zero-shot abstractive summarization. The…
Continue readingThe article presents a novel task, Text2MDT, which aims to automatically extract medical decision trees from medical texts such as guidelines and textbooks. Two methods for the task are investigated:…
Continue readingThis study provides an in-depth review of the evolution of large language model (LLM) training techniques and inference deployment technologies. The paper discusses various aspects of training, including data preprocessing,…
Continue readingThe paper presents ICE-GRT, a model developed to enhance the performance of Large Language Models (LLMs) in domain-specific tasks. LLMs like ChatGPT and LLaMA often lack depth and accuracy in…
Continue readingThe article presents a research on evaluating the quality and variability of text generated by Large Language Models (LLMs). Conventional evaluation methods often fail to capture the holistic semantic equivalence,…
Continue readingThe article presents DIALIGHT, a toolkit for developing and evaluating multilingual Task-Oriented Dialogue (TOD) systems. It’s designed to facilitate systematic evaluations and comparisons between TOD systems using Pretrained Language Models…
Continue readingThe article introduces LLaMA Pro, a novel post-pretraining method for Large Language Models (LLMs) that expands Transformer blocks. Unlike other LLMs, which can forget old skills when acquiring new ones,…
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