{"total":1,"items":[{"citing_arxiv_id":"2507.12126","ref_index":6,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis","primary_cat":"cs.CL","submitted_at":"2025-07-16T10:49:30+00:00","verdict":"REJECT","verdict_confidence":"HIGH","novelty_score":5.0,"formal_verification":"none","one_line_summary":"The paper evaluates four LLMs as text augmenters and reports GPT-3.5 Turbo as the best, and that combining augmentation with GPT topic labels increases BERTopic's discovered topics from 5 to 20 with zero overlap.","context_count":1,"top_context_role":"background","top_context_polarity":"unclear","context_text":"procedures were implemented with a focus on aggregate trends and model behavior rather than individual-level profiling. R EFERENCES [1] D. Khurana, A. Koli, K. Khatter, and S. Singh, \"Natural language processing: state of the art, current trends and challenges,\" Multimedia Tools and Applications, vol. 82, no. 3, pp. 3713- 3744, 2023/01/01 2023, doi: 10.1007/s11042-022-13428-4. [2] M. Wankhade, A. C. S. Rao, and C. Kulkarni, \"A survey on sentiment analysis methods, applications, and challenges,\" Artificial Intelligence Review, vol. 55, no. 7, pp. 5731- 5780, 2022/10/01 2022, doi: 10.1007/s10462- 022- 10144-1. [3] Dogra V, Verma S, Kavita, Chatterjee P, Shafi J, Choi J, Ijaz MF. A complete process of text classification system using state‐of‐the‐art NLP"}],"limit":50,"offset":0}