| The Prompt Report: A Systematic Survey of Prompting Techniques S Schulhoff, M Ilie, N Balepur, K Kahadze, A Liu, C Si, Y Li, A Gupta, ... arXiv preprint arXiv:2406.06608, 2024 | 6 | 2024 |
| Expository Text Generation: Imitate, Retrieve, Paraphrase N Balepur, J Huang, KCC Chang EMNLP 2023, 2023 | 6 | 2023 |
| Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? N Balepur, A Ravichander, R Rudinger ACL 2024, 2024 | 4 | 2024 |
| It's Not Easy Being Wrong: Evaluating Process of Elimination Reasoning in Large Language Models N Balepur, S Palta, R Rudinger ACL Findings 2024, 2023 | 3 | 2023 |
| DynaMiTE: Discovering Explosive Topic Evolutions with User Guidance N Balepur, S Agarwal, KV Ramanan, S Yoon, D Yang, J Han ACL Findings 2023, 2023 | 2 | 2023 |
| Mastering the ABCDs of Complex Questions: Answer-Based Claim Decomposition for Fine-grained Self-Evaluation N Balepur, J Huang, S Moorjani, H Sundaram, KCC Chang arXiv preprint arXiv:2305.14750, 2023 | 2 | 2023 |
| KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students M Shu, N Balepur, S Feng, J Boyd-Graber arXiv preprint arXiv:2402.12291, 2024 | 1 | 2024 |
| Text Fact Transfer N Balepur, J Huang, KCC Chang EMNLP 2023, 2023 | 1 | 2023 |
| Is Your Large Language Model Knowledgeable or a Choices-Only Cheater? N Balepur, R Rudinger arXiv preprint arXiv:2407.01992, 2024 | | 2024 |
| A SMART Mnemonic Sounds like" Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick N Balepur, M Shu, A Hoyle, A Robey, S Feng, S Goldfarb-Tarrant, ... arXiv preprint arXiv:2406.15352, 2024 | | 2024 |
Rachel RudingerAssistant Professor, Department of Computer Science, University of Maryland在 umd.edu 的电子邮件经过验证
