{"total":86,"rows":[{"id":"2410.15553","title":"Multi-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following","created":"2024-10-21","cited_by_count":102,"area":null},{"id":"2410.03608","title":"TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation","created":"2024-10-04","cited_by_count":68,"area":null},{"id":"2408.01122","title":"CFBench: A Comprehensive Constraints-Following Benchmark for LLMs","created":"2024-08-02","cited_by_count":67,"area":null},{"id":"2502.08745","title":"IHEval: Evaluating Language Models on Following the Instruction Hierarchy","created":"2025-02-12","cited_by_count":53,"area":null},{"id":"2511.10507","title":"AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following","created":"2025-11-13","cited_by_count":51,"area":null},{"id":"2411.07037","title":"LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context Scenarios","created":"2024-11-11","cited_by_count":33,"area":null},{"id":"2502.14494","title":"StructFlowBench: A Structured Flow Benchmark for Multi-turn Instruction Following","created":"2025-02-20","cited_by_count":29,"area":null},{"id":"2408.10943","title":"SysBench: Can Large Language Models Follow System Messages?","created":"2024-08-20","cited_by_count":28,"area":null},{"id":"2412.16429","title":"LearnLM: Improving Gemini for Learning","created":"2024-12-21","cited_by_count":25,"area":null},{"id":"2410.04197","title":"CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints","created":"2024-10-05","cited_by_count":24,"area":null},{"id":"2505.12025","title":"Spotlight Your Instructions: Instruction-following with Dynamic Attention Steering","created":"2025-05-17","cited_by_count":21,"area":null},{"id":"2507.11538","title":"How Many Instructions Can LLMs Follow at Once?","created":"2025-07-15","cited_by_count":20,"area":null},{"id":"2603.25133","title":"RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following","created":"2026-03-26","cited_by_count":20,"area":null},{"id":"2505.07591","title":"MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models","created":"2025-05-12","cited_by_count":15,"area":null},{"id":"2502.04362","title":"LLMs can be easily Confused by Instructional Distractions","created":"2025-02-05","cited_by_count":13,"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":"2502.17204","title":"Order Matters: Investigate the Position Bias in Multi-constraint Instruction Following","created":"2025-02-24","cited_by_count":12,"area":null},{"id":"2504.02904","title":"How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence","created":"2025-04-03","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":"2503.07539","title":"XIFBench: Evaluating Large Language Models on Multilingual Instruction Following","created":"2025-03-10","cited_by_count":11,"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":"2506.02672","title":"EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving","created":"2025-06-03","cited_by_count":10,"area":null},{"id":"2509.04292","title":"Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions?","created":"2025-09-04","cited_by_count":10,"area":null},{"id":"2511.14342","title":"ConInstruct: Evaluating Large Language Models on Conflict Detection and Resolution in Instructions","created":"2025-11-18","cited_by_count":10,"area":null},{"id":"2603.04738","title":"IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation","created":"2026-03-05","cited_by_count":10,"area":null},{"id":"2506.08375","title":"EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models","created":"2025-06-10","cited_by_count":9,"area":null},{"id":"2511.03508","title":"One Battle After Another: Probing LLMs' Limits on Multi-Turn Instruction Following with a Benchmark Evolving Framework","created":"2025-11-05","cited_by_count":9,"area":null},{"id":"2410.12207","title":"Divide-Verify-Refine: Can LLMs Self-Align with Complex Instructions?","created":"2024-10-16","cited_by_count":8,"area":null},{"id":"2506.03278","title":"FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes","created":"2025-06-03","cited_by_count":7,"area":null},{"id":"2506.06950","title":"What Makes a Good Natural Language Prompt?","created":"2025-06-07","cited_by_count":7,"area":null},{"id":"2510.13291","title":"Higher Satisfaction, Lower Cost: A Technical Report on How LLMs Revolutionize Meituan's Intelligent Interaction Systems","created":"2025-10-15","cited_by_count":7,"area":null},{"id":"2512.14754","title":"Revisiting the Reliability of Language Models in Instruction-Following","created":"2025-12-15","cited_by_count":7,"area":null},{"id":"2604.22937","title":"AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs","created":"2026-04-24","cited_by_count":7,"area":null},{"id":"2410.05824","title":"Multi-Session Client-Centered Treatment Outcome Evaluation in Psychotherapy","created":"2024-10-08","cited_by_count":5,"area":null},{"id":"2509.21051","title":"When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following","created":"2025-09-25","cited_by_count":5,"area":null},{"id":"2510.18892","title":"When Models Can't Follow: Testing Instruction Adherence Across 256 LLMs","created":"2025-10-18","cited_by_count":5,"area":null},{"id":"2602.07549","title":"When Is Enough Not Enough? Illusory Completion in Search Agents","created":"2026-02-07","cited_by_count":5,"area":null},{"id":"2510.08942","title":"SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures","created":"2025-10-10","cited_by_count":4,"area":null},{"id":"2511.01014","title":"IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation","created":"2025-11-02","cited_by_count":4,"area":null},{"id":"2601.17789","title":"Neuro-Symbolic Verification on Instruction Following of LLMs","created":"2026-01-25","cited_by_count":4,"area":null},{"id":"2504.21625","title":"Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capability","created":"2025-04-30","cited_by_count":3,"area":null},{"id":"2509.01787","title":"AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions","created":"2025-09-01","cited_by_count":3,"area":null},{"id":"2510.23558","title":"ISA-Bench: Benchmarking Instruction Sensitivity for Large Audio Language Models","created":"2025-10-27","cited_by_count":3,"area":null},{"id":"2603.17067","title":"Evaluating Ill-Defined Tasks in Large Language Models","created":"2026-03-17","cited_by_count":3,"area":null},{"id":"2609.04061","title":"When Models Edit Too Much: On the Fidelity of Minimal Code Edits","created":"2026-09-03","cited_by_count":3,"area":null},{"id":"2505.11922","title":"Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning","created":"2025-05-17","cited_by_count":2,"area":null},{"id":"2505.24803","title":"Guiding Generative Storytelling with Knowledge Graphs","created":"2025-05-30","cited_by_count":2,"area":null},{"id":"2506.02596","title":"EssayBench: Evaluating Large Language Models in Multi-Genre Chinese Essay Writing","created":"2025-06-03","cited_by_count":2,"area":null},{"id":"2511.15976","title":"TOD-ProcBench: Benchmarking Complex Instruction-Following in Task-Oriented Dialogues","created":"2025-11-20","cited_by_count":2,"area":null},{"id":"2511.17561","title":"LexInstructEval: Lexical Instruction Following Evaluation for Large Language Models","created":"2025-11-13","cited_by_count":2,"area":null},{"id":"2512.17387","title":"CIFE: Code Instruction-Following Evaluation","created":"2025-12-19","cited_by_count":2,"area":null},{"id":"2601.18554","title":"Deconstructing Instruction-Following: A New Benchmark for Granular Evaluation of Large Language Model Instruction Compliance Abilities","created":"2026-01-26","cited_by_count":2,"area":null},{"id":"2601.22047","title":"On the Paradoxical Interference between Instruction-Following and Task Solving","created":"2026-01-29","cited_by_count":2,"area":null},{"id":"2603.04857","title":"FireBench: Evaluating Instruction Following in Enterprise and API-Driven LLM Applications","created":"2026-03-05","cited_by_count":2,"area":null},{"id":"2607.09739","title":"Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks","created":"2026-07-02","cited_by_count":2,"area":null},{"id":"2505.18011","title":"Training with Pseudo-Code for Instruction Following","created":"2025-05-23","cited_by_count":1,"area":null},{"id":"2510.01688","title":"Format Inertia: A Failure Mechanism of LLMs in Medical Pre-Consultation","created":"2025-10-02","cited_by_count":1,"area":null},{"id":"2510.07892","title":"Metric Calculating Benchmark: Code-Verifiable Complicate Instruction Following Benchmark for Large Language Models","created":"2025-10-09","cited_by_count":1,"area":null},{"id":"2601.11783","title":"The Stability Trap: Evaluating the Reliability of LLM-Based Instruction Adherence Auditing","created":"2026-01-16","cited_by_count":1,"area":null},{"id":"2602.13033","title":"Buy versus Build an LLM: A Decision Framework for Governments","created":"2026-02-13","cited_by_count":1,"area":null},{"id":"2602.21556","title":"Power and Limitations of Aggregation in Compound AI Systems","created":"2026-02-25","cited_by_count":1,"area":null},{"id":"2603.18019","title":"BenchBrowser: Retrieving Evidence for Evaluating Benchmark Validity","created":"2026-02-25","cited_by_count":1,"area":null},{"id":"2604.13006","title":"One Token Away from Collapse: The Fragility of Instruction-Tuned Helpfulness","created":"2026-04-14","cited_by_count":1,"area":null},{"id":"2604.19071","title":"HoWToBench: Holistic Evaluation for LLM's Capability in Human-level Writing using Tree of Writing","created":"2026-04-21","cited_by_count":1,"area":null},{"id":"2605.08614","title":"DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2605.18073","title":"A-ProS: Towards Reliable Autonomous Programming Through Multi-Model Feedback","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2607.27912","title":"IFHierBench: Hierarchical Instruction Following for Large Language Models","created":"2026-07-30","cited_by_count":1,"area":null},{"id":"2412.11025","title":"From Simple to Professional: A Combinatorial Controllable Image Captioning Agent","created":"2024-12-15","cited_by_count":0,"area":null},{"id":"2506.21573","title":"Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMs","created":"2025-06-14","cited_by_count":0,"area":null},{"id":"2509.22715","title":"TRUEBench: Can LLM Response Meet Real-world Constraints as Productivity Assistant?","created":"2025-09-24","cited_by_count":0,"area":null},{"id":"2510.14842","title":"Boosting Instruction Following at Scale","created":"2025-10-16","cited_by_count":0,"area":null},{"id":"2512.08965","title":"Financial Instruction Following Evaluation (FIFE)","created":"2025-12-01","cited_by_count":0,"area":null},{"id":"2601.06431","title":"LsrIF: Enhancing Logic-Structured Instruction Following of Large Language Models","created":"2026-01-10","cited_by_count":0,"area":null},{"id":"2601.19923","title":"Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information Systems","created":"2026-01-09","cited_by_count":0,"area":null},{"id":"2603.15615","title":"Mechanistic Origin of Moral Indifference in Language Models","created":"2026-03-16","cited_by_count":0,"area":null},{"id":"2605.03858","title":"MCJudgeBench: A Benchmark for Constraint-Level Judge Evaluation in Multi-Constraint Instruction Following","created":"2026-05-05","cited_by_count":0,"area":null},{"id":"2605.20382","title":"Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs","created":"2026-05-19","cited_by_count":0,"area":null},{"id":"2607.23545","title":"Language Shapes Instruction Hierarchy Compliance in Multilingual LLMs","created":"2026-07-26","cited_by_count":0,"area":null},{"id":"2607.29196","title":"Hy-MultiTurn: A Six-Dimensional Benchmark for Deep Multi-Turn Dialogue Understanding","created":"2026-07-31","cited_by_count":0,"area":null},{"id":"2608.09154","title":"UNSPECIFIC: General Constraint Synthesis for Breaking Copy-and-Paste Shortcut in LLM Instruction Following","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.11584","title":"EnterpriseRAG: Benchmarking LLM Instruction Adherence and Robustness under Non-Ideal Enterprise Retrieval","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2609.26087","title":"The Architect, the Adversary, and the Judge: Closed-Loop Generation of Standards-Aligned Assessment Items at Scale","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2610.01674","title":"Invent a Dataset: Measuring dataset generation abilities with zero seed","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.05161","title":"Beyond Instruction Following: Learning Grounded Skill-Following with Skill Contracts","created":"2026-10-04","cited_by_count":0,"area":null},{"id":"2610.11015","title":"Prompts versus Rules: Auditing and Controlling Speech Naturalness Behaviors in Voice User Simulators","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.19693","title":"ReFormBench: Benchmarking the Stability of Response-Conditioned Format Correction in Large Language Models","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}