{"total":29,"rows":[{"id":"2402.00530","title":"Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning","created":"2024-02-01","cited_by_count":138,"area":null},{"id":"2402.05123","title":"A Survey on Data Selection for LLM Instruction Tuning","created":"2024-02-04","cited_by_count":77,"area":null},{"id":"2403.15042","title":"LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement","created":"2024-03-22","cited_by_count":70,"area":null},{"id":"2310.10072","title":"Fine-tuning ChatGPT for Automatic Scoring","created":"2023-10-16","cited_by_count":51,"area":null},{"id":"2310.16809","title":"Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth Evaluation","created":"2023-10-25","cited_by_count":46,"area":null},{"id":"2401.17139","title":"Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models","created":"2024-01-30","cited_by_count":35,"area":null},{"id":"2403.03129","title":"CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following","created":"2024-03-05","cited_by_count":33,"area":null},{"id":"2312.02436","title":"MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following","created":"2023-12-05","cited_by_count":30,"area":null},{"id":"2311.04124","title":"Unveiling Safety Vulnerabilities of Large Language Models","created":"2023-11-07","cited_by_count":27,"area":null},{"id":"2311.13246","title":"CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning","created":"2023-11-22","cited_by_count":19,"area":null},{"id":"2405.00705","title":"SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning","created":"2024-04-23","cited_by_count":19,"area":null},{"id":"2401.16553","title":"SelectLLM: Can LLMs Select Important Instructions to Annotate?","created":"2024-01-29","cited_by_count":16,"area":null},{"id":"2310.09518","title":"Instruction Tuning with Human Curriculum","created":"2023-10-14","cited_by_count":15,"area":null},{"id":"2410.15225","title":"Chasing Random: Instruction Selection Strategies Fail to Generalize","created":"2024-10-19","cited_by_count":13,"area":null},{"id":"2404.16766","title":"Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model","created":"2024-04-25","cited_by_count":10,"area":null},{"id":"2412.00631","title":"ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning","created":"2024-12-01","cited_by_count":10,"area":null},{"id":"2310.16499","title":"Data Optimization in Deep Learning: A Survey","created":"2023-10-25","cited_by_count":6,"area":null},{"id":"2406.06140","title":"Can I understand what I create? Self-Knowledge Evaluation of Large Language Models","created":"2024-06-10","cited_by_count":6,"area":null},{"id":"2503.02359","title":"Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm","created":"2025-03-04","cited_by_count":6,"area":null},{"id":"2602.03677","title":"Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration","created":"2026-02-03","cited_by_count":6,"area":null},{"id":"2404.01713","title":"Generative AI for Immersive Communication: The Next Frontier in Internet-of-Senses Through 6G","created":"2024-04-02","cited_by_count":4,"area":null},{"id":"2410.02268","title":"Structural-Entropy-Based Sample Selection for Efficient and Effective Learning","created":"2024-10-03","cited_by_count":4,"area":null},{"id":"2504.07288","title":"MDIT: A Model-free Data Interpolation Method for Diverse Instruction Tuning","created":"2025-04-09","cited_by_count":3,"area":null},{"id":"2504.19742","title":"EcoWikiRS: Learning Ecological Representation of Satellite Images from Weak Supervision with Species Observations and Wikipedia","created":"2025-04-28","cited_by_count":3,"area":null},{"id":"2508.19996","title":"ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning","created":"2025-08-27","cited_by_count":3,"area":null},{"id":"2505.18115","title":"Instructify: Demystifying Metadata to Visual Instruction Tuning Data Conversion","created":"2025-05-23","cited_by_count":2,"area":null},{"id":"2601.12730","title":"Distribution-Centric Policy Optimization Dominates Exploration-Exploitation Trade-off","created":"2026-01-19","cited_by_count":1,"area":null},{"id":"2411.14121","title":"Learning from \"Silly\" Questions Improves Large Language Models, But Only Slightly","created":"2024-11-21","cited_by_count":0,"area":null},{"id":"2509.07909","title":"Uncovering Scaling Laws for Large Language Models via Inverse Problems","created":"2025-09-09","cited_by_count":0,"area":null}],"next_cursor":null}