Papers with RCT

3 papers
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models’ Memories (2023.acl-long)

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Challenge: Pre-trained language models demonstrate excellent abilities to understand texts in the generic domain while struggling in a specific domain.
Approach: They propose to decouple the feed-forward networks of the Transformer architecture into two parts to maintain old-domain knowledge and a mixture-of-adapters gate to inject domain-specific knowledge in parallel.
Outcome: The proposed method achieves superior performance on in-domain, out-of-domain and knowledge-intensive tasks.
Inferring Which Medical Treatments Work from Reports of Clinical Trials (N19-1)

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Challenge: Ideally, one would consult all available evidence from relevant clinical trials. however, these results are primarily disseminated in natural language scientific articles.
Approach: They propose a task that involves inferring results from a full-text article describing randomized controlled trials with respect to a given intervention, comparator, and outcome of interest.
Outcome: The proposed task consists of 10,000+ prompts coupled with full-text articles describing randomized controlled trials.
GPT-4 as a Homework Tutor Can Improve Student Engagement and Learning Outcomes (2025.acl-long)

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Challenge: a recent study has shown that homework is never graded or is done superficially.
Approach: They propose a prompting strategy that enables GPT-4 to conduct interactive homework sessions for high school students learning English as a second language.
Outcome: The proposed solution improves homework in high school students learning English as a second language with minimal effort in content preparation, one of the key challenges of alternative methods.

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