{"total":14,"rows":[{"id":"2409.14509","title":"Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Edits","created":"2024-09-22","cited_by_count":49,"area":null},{"id":"2412.13091","title":"LMUnit: Fine-grained Evaluation with Natural Language Unit Tests","created":"2024-12-17","cited_by_count":33,"area":null},{"id":"2502.07586","title":"We Can't Understand AI Using our Existing Vocabulary","created":"2025-02-11","cited_by_count":25,"area":null},{"id":"2503.15620","title":"Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings","created":"2025-03-19","cited_by_count":24,"area":null},{"id":"2510.06213","title":"Training Dynamics Impact Post-Training Quantization Robustness","created":"2025-10-07","cited_by_count":15,"area":null},{"id":"2412.14140","title":"GLIDER: Grading LLM Interactions and Decisions using Explainable Ranking","created":"2024-12-18","cited_by_count":14,"area":null},{"id":"2508.06482","title":"Post-training for Efficient Communication via Convention Formation","created":"2025-08-08","cited_by_count":7,"area":null},{"id":"2510.08506","title":"Neologism Learning for Controllability and Self-Verbalization","created":"2025-10-09","cited_by_count":6,"area":null},{"id":"2603.18806","title":"dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Models","created":"2026-03-19","cited_by_count":3,"area":null},{"id":"2603.16430","title":"EngGPT2: Sovereign, Efficient and Open Intelligence","created":"2026-03-17","cited_by_count":1,"area":null},{"id":"2509.26514","title":"BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs","created":"2025-09-30","cited_by_count":0,"area":null},{"id":"2512.18551","title":"Neologism Learning as a Parameter-Efficient Alternative to Fine-Tuning for Model Steering","created":"2025-12-21","cited_by_count":0,"area":null},{"id":"2603.19294","title":"Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2604.23855","title":"Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows","created":"2026-04-26","cited_by_count":0,"area":null}],"next_cursor":null}