D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model | Paper Citation Record

Observation afd9a866-e929-4385-acbc-0334dff439e0 · outbound

This paper cites Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluation

Reference 1

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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This paper cites Distractor generation for multiple-choice questions with predictive prompting and large language models.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Distractor generation for multiple-choice questions with predictive prompting and large language models

Reference 4

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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This paper cites Evaluating Large Language Models Trained on Code.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Evaluating Large Language Models Trained on Code

Reference 6

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This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 7

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This paper cites Training Verifiers to Solve Math Word Problems.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Training Verifiers to Solve Math Word Problems

Reference 8

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 10

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 11

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 12

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 13

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 14

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 15

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This paper cites The Llama 3 Herd of Models.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model The Llama 3 Herd of Models

Reference 16

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This paper cites Measuring Massive Multitask Language Understanding.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Measuring Massive Multitask Language Understanding

Reference 17

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This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Measuring Mathematical Problem Solving With the MATH Dataset

Reference 18

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This paper cites Teaching Machines to Read and Comprehend.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Teaching Machines to Read and Comprehend

Reference 19

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This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 21

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Mistral 7B

Reference 22

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This paper cites ManjulaShenoy, Shashank Goyal, and Chaitanya.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model ManjulaShenoy, Shashank Goyal, and Chaitanya

Reference 23

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This paper cites RACE: Large-scale ReAding Comprehension Dataset From Examinations.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model RACE: Large-scale ReAding Comprehension Dataset From Examinations

Reference 24

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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This paper cites Lee Giles.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Lee Giles

Reference 26

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 27

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This paper cites The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Reference 28

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This paper cites A Novel Multi-Stage Prompting Approach for Language Agnostic MCQ Generation using GPT.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model A Novel Multi-Stage Prompting Approach for Language Agnostic MCQ Generation using GPT

Reference 29

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 30

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 32

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This paper cites Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond

Reference 33

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering

Reference 36

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model GPT-4o System Card

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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This paper cites Qwen2.5 Technical Report.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Qwen2.5 Technical Report

Reference 42

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Know What You Don't Know: Unanswerable Questions for SQuAD

Reference 44

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Knowledge-Driven Distractor Generation for Cloze-style Multiple Choice Questions

Reference 46

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Burges, and Erin Renshaw

Reference 47

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 48

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

Reference 49

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Gemma 2: Improving Open Language Models at a Practical Size

Reference 50

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 51

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Finetuned Language Models Are Zero-Shot Learners

Reference 52

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 54

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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This paper cites ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension

Reference 57

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Unresolved cited work

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Multiple-Choice Questions are Efficient and Robust LLM Evaluators

Reference 59

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D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 60

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Observation 0e32a5a1-2516-417d-ae99-872ea3194195 · outbound

This paper cites Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:12:02.293352Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2f33d1f6-db95-4e61-85ca-538f69c63bc4 · outbound

This paper cites online" 'onlinestring :=.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model online" 'onlinestring :=

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T12:12:02.087833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39d88be2-9ad1-49d8-b32e-646b04356d74 · outbound

This paper cites write newline.

D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model write newline

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T12:12:02.092175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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