{"total":13,"rows":[{"id":"2311.09335","title":"Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization","created":"2023-11-15","cited_by_count":16,"area":null},{"id":"2504.12691","title":"Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations","created":"2025-04-17","cited_by_count":15,"area":null},{"id":"2404.12545","title":"Latent Concept-based Explanation of NLP Models","created":"2024-04-18","cited_by_count":13,"area":null},{"id":"2402.00794","title":"ReAGent: A Model-agnostic Feature Attribution Method for Generative Language Models","created":"2024-02-01","cited_by_count":12,"area":null},{"id":"2408.08137","title":"Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attribution Explainability","created":"2024-08-15","cited_by_count":10,"area":null},{"id":"2403.12809","title":"Comparing Explanation Faithfulness between Multilingual and Monolingual Fine-tuned Language Models","created":"2024-03-19","cited_by_count":6,"area":null},{"id":"2504.02911","title":"Noiser: Bounded Input Perturbations for Attributing Large Language Models","created":"2025-04-03","cited_by_count":4,"area":null},{"id":"2505.01198","title":"Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods","created":"2025-05-02","cited_by_count":3,"area":null},{"id":"2411.12643","title":"DLBacktrace: A Model Agnostic Explainability for any Deep Learning Models","created":"2024-11-19","cited_by_count":2,"area":null},{"id":"2505.01238","title":"EvalxNLP: A Framework for Benchmarking Post-Hoc Explainability Methods on NLP Models","created":"2025-05-02","cited_by_count":2,"area":null},{"id":"2604.13258","title":"Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs","created":"2026-04-14","cited_by_count":2,"area":null},{"id":"2510.21884","title":"Support-Contra Asymmetry in LLM Explanations","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2406.15443","title":"ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread","created":"2024-05-30","cited_by_count":0,"area":null}],"next_cursor":null}