{"total":8,"rows":[{"id":"2509.21044","title":"Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs","created":"2025-09-25","cited_by_count":9,"area":null},{"id":"2303.04475","title":"RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning","created":"2023-03-08","cited_by_count":6,"area":null},{"id":"2307.15786","title":"SAFE: Saliency-Aware Counterfactual Explanations for DNN-based Automated Driving Systems","created":"2023-07-28","cited_by_count":5,"area":null},{"id":"2305.16532","title":"Counterfactual Explainer Framework for Deep Reinforcement Learning Models Using Policy Distillation","created":"2023-05-25","cited_by_count":3,"area":null},{"id":"2405.05295","title":"Relevant Irrelevance: Generating Alterfactual Explanations for Image Classifiers","created":"2024-05-08","cited_by_count":3,"area":null},{"id":"2405.02583","title":"Explainable Interface for Human-Autonomy Teaming: A Survey","created":"2024-05-04","cited_by_count":2,"area":null},{"id":"2506.15893","title":"Formal Models of Active Learning from Contrastive Examples","created":"2025-06-18","cited_by_count":2,"area":null},{"id":"2602.02080","title":"Learning Half-Spaces from Perturbed Contrastive Examples","created":"2026-02-02","cited_by_count":0,"area":null}],"next_cursor":null}