{"total":15,"rows":[{"id":"2411.16594","title":"From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge","created":"2024-11-25","cited_by_count":494,"area":null},{"id":"2502.11541","title":"MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training","created":"2025-02-17","cited_by_count":12,"area":null},{"id":"2505.16475","title":"ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection","created":"2025-05-22","cited_by_count":12,"area":null},{"id":"2505.19030","title":"RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data","created":"2025-05-25","cited_by_count":12,"area":null},{"id":"2502.17787","title":"AIR: Complex Instruction Generation via Automatic Iterative Refinement","created":"2025-02-25","cited_by_count":10,"area":null},{"id":"2506.17863","title":"LLMs for Customized Marketing Content Generation and Evaluation at Scale","created":"2025-06-22","cited_by_count":9,"area":null},{"id":"2510.25817","title":"A Survey on Efficient Large Language Model Training: From Data-centric Perspectives","created":"2025-10-29","cited_by_count":9,"area":null},{"id":"2501.09368","title":"Aligning Instruction Tuning with Pre-training","created":"2025-01-16","cited_by_count":7,"area":null},{"id":"2508.21589","title":"Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning","created":"2025-08-29","cited_by_count":7,"area":null},{"id":"2506.20274","title":"Enterprise Large Language Model Evaluation Benchmark","created":"2025-06-25","cited_by_count":5,"area":null},{"id":"2511.13333","title":"AutoMalDesc: Large-Scale Script Analysis for Cyber Threat Research","created":"2025-11-17","cited_by_count":1,"area":null},{"id":"2602.02991","title":"Large Language Models Can Take False First Steps at Inference-time Planning","created":"2026-02-03","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":"2606.01000","title":"Trust Functions: Near-Lossless Weak-to-Strong Generalization by Learning When to Trust the Weak Teacher","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2608.12062","title":"Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations","created":"2026-08-12","cited_by_count":0,"area":null}],"next_cursor":null}