Synapse
⌘+K
Synapse
PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
June 3, 2024Open Access

Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding

View Full Paper
Ask AI
Bookmark
Share

Authors

FQFanyi QuHSHao SunYWYunfang Wu

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Qu et al. (2024) studied this question.

synapsesocial.com/papers/68e66845b6db6435875f45cchttps://doi.org/10.48550/arxiv.2406.01306
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1DGRC: An Effective Fine-tuning Framework for Distractor Generation in Chinese Multi-choice Reading Comprehension2024 · 1 citations
  2. 2Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models2024 · 1 citations
  3. 3Enhancing Contextual Understanding in Large Language Models through Contrastive Decoding2024
  4. 4Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and Distillation2024
  5. 5DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions2024 · 2 citations