{"total":18,"rows":[{"id":"2404.01349","title":"Fairness in Large Language Models: A Taxonomic Survey","created":"2024-03-31","cited_by_count":58,"area":null},{"id":"2312.09203","title":"Measurement in the Age of LLMs: An Application to Ideological Scaling","created":"2023-12-14","cited_by_count":11,"area":null},{"id":"2407.08989","title":"Robustness of Large Language Models to Perturbations in Text","created":"2024-07-12","cited_by_count":11,"area":null},{"id":"2502.01349","title":"Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations","created":"2025-02-03","cited_by_count":11,"area":null},{"id":"2403.03788","title":"PPTC-R benchmark: Towards Evaluating the Robustness of Large Language Models for PowerPoint Task Completion","created":"2024-03-06","cited_by_count":9,"area":null},{"id":"2510.09536","title":"Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors","created":"2025-10-10","cited_by_count":9,"area":null},{"id":"2404.12145","title":"From Form(s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense Consistency","created":"2024-04-18","cited_by_count":7,"area":null},{"id":"2404.08517","title":"Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward","created":"2024-04-12","cited_by_count":6,"area":null},{"id":"2501.08322","title":"Exploring Robustness of Multilingual LLMs on Real-World Noisy Data","created":"2025-01-14","cited_by_count":6,"area":null},{"id":"2601.06341","title":"Evaluating Robustness of Large Language Models in Enterprise Applications: Benchmarks for Perturbation Consistency Across Formats and Languages","created":"2026-01-09","cited_by_count":5,"area":null},{"id":"2410.12924","title":"Interpreting token compositionality in LLMs: A robustness analysis","created":"2024-10-16","cited_by_count":4,"area":null},{"id":"2502.16781","title":"Evaluating Robustness of LLMs in Question Answering on Multilingual Noisy OCR Data","created":"2025-02-24","cited_by_count":2,"area":null},{"id":"2604.18835","title":"Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring","created":"2026-04-20","cited_by_count":2,"area":null},{"id":"2402.17671","title":"Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Models","created":"2024-02-27","cited_by_count":1,"area":null},{"id":"2605.01605","title":"Where Do Prompt Perturbations Break Generation? A Segment-Level View of Robustness in LoRA-Tuned Language Models","created":"2026-05-02","cited_by_count":1,"area":null},{"id":"2404.19708","title":"Harmonic LLMs are Trustworthy","created":"2024-04-30","cited_by_count":0,"area":null},{"id":"2607.07915","title":"Validating LLMs in social science: Epistemic threats and emerging norms","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2607.10855","title":"Reliability Scaling Laws for Quantized Large Language Models","created":"2026-07-12","cited_by_count":0,"area":null}],"next_cursor":null}