Aligning factual consistency for clinical studies summarization through reinforcement learning
In the rapidly evolving landscape of medical research, accurate and concise summarization
of clinical studies is crucial to support evidence-based practice. This paper presents a novel …
of clinical studies is crucial to support evidence-based practice. This paper presents a novel …
Knowcomp at semeval-2023 task 7: Fine-tuning pre-trained language models for clinical trial entailment identification
In this paper, we present our system for the textual entailment identification task as a subtask
of the SemEval-2023 Task 7: Multi-evidence Natural Language Inference for Clinical Trial …
of the SemEval-2023 Task 7: Multi-evidence Natural Language Inference for Clinical Trial …
A Novel Clinical Trial Prediction-Based Factual Inconsistency Detection Approach for Medical Text Summarization
S Li, J Xu - 2023 International Joint Conference on Neural …, 2023 - ieeexplore.ieee.org
Most existing works of factual inconsistency detection focus on text summarization of generic
articles. In this paper, a clinical trial prediction-based factual inconsistency detection …
articles. In this paper, a clinical trial prediction-based factual inconsistency detection …
An Overview of Research on Multi-Document Summarization
B Ritong, S Haichun - Data Analysis and Knowledge …, 2023 - manu44.magtech.com.cn
[Objective] This paper reviews the literature on multi-document summarization, aiming to
examine their research frameworks and mainstream models.[Coverage] We searched the AI …
examine their research frameworks and mainstream models.[Coverage] We searched the AI …