{"total":25,"rows":[{"id":"2502.17521","title":"Recent Advances in Large Langauge Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation","created":"2025-02-23","cited_by_count":38,"area":null},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2412.15540","title":"MRAG: A Modular Retrieval Framework for Time-Sensitive Question Answering","created":"2024-12-20","cited_by_count":17,"area":null},{"id":"2503.16402","title":"The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination","created":"2025-03-20","cited_by_count":15,"area":null},{"id":"2506.21614","title":"LastingBench: Defend Benchmarks Against Knowledge Leakage","created":"2025-06-21","cited_by_count":14,"area":null},{"id":"2512.04578","title":"LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence","created":"2025-12-04","cited_by_count":4,"area":null},{"id":"2509.14448","title":"VCBench: Benchmarking LLMs in Venture Capital","created":"2025-09-17","cited_by_count":3,"area":null},{"id":"2511.18889","title":"CoreEval: Automatically Building Contamination-Resilient Datasets with Real-World Knowledge toward Reliable LLM Evaluation","created":"2025-11-24","cited_by_count":3,"area":null},{"id":"2507.16514","title":"The Ever-Evolving Science Exam","created":"2025-07-22","cited_by_count":2,"area":null},{"id":"2605.19999","title":"LLM Benchmark Datasets Should Be Contamination-Resistant","created":"2026-05-19","cited_by_count":2,"area":null},{"id":"2608.02985","title":"Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores","created":"2026-08-04","cited_by_count":2,"area":null},{"id":"2608.03764","title":"GDPevo: Evaluating Agent Self-Evolution on Real Business Tasks","created":"2026-08-04","cited_by_count":2,"area":null},{"id":"2510.05962","title":"MatheMagic: Generating Dynamic Mathematics Benchmarks Robust to Memorization","created":"2025-10-07","cited_by_count":1,"area":null},{"id":"2510.20252","title":"Individualized Cognitive Simulation in Large Language Models: Evaluating Different Cognitive Representation Methods","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2601.03570","title":"How Do Large Language Models Learn Concepts During Continual Pre-Training?","created":"2026-01-07","cited_by_count":1,"area":null},{"id":"2605.07268","title":"From 0-Order Selection to 2-Order Judgment: Combinatorial Hardening Exposes Compositional Failures in Frontier LLMs","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2609.18366","title":"Bad Genius: Counterfactual-Guided Harness Evolution Beyond Task-Specific Shortcuts","created":"2026-09-16","cited_by_count":1,"area":null},{"id":"2507.03617","title":"EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge","created":"2025-07-04","cited_by_count":0,"area":null},{"id":"2508.02045","title":"Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2603.02212","title":"GLEAN: Grounded Lightweight Evaluation Anchors for Contamination-Aware Tabular Reasoning","created":"2026-01-22","cited_by_count":0,"area":null},{"id":"2605.10810","title":"Likelihood scoring for continuations of mathematical text: a self-supervised benchmark with tests for shortcut vulnerabilities","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2606.01849","title":"ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2609.27510","title":"Uncheatable Eval: Dynamic Compression-Based Evaluation of Language Models","created":"2026-09-23","cited_by_count":0,"area":null},{"id":"2610.07614","title":"BioStudyBench: Evaluating Agents on Post-Cutoff Biomedical Studies","created":"2026-10-06","cited_by_count":0,"area":null},{"id":"2610.19399","title":"KoAGE: Do Large Language Models Know, Learn, and Coin Korean Neologisms?","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}