{"total":58,"rows":[{"id":"2412.05579","title":"LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods","created":"2024-12-07","cited_by_count":465,"area":null},{"id":"2502.14127","title":"Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above","created":"2025-02-19","cited_by_count":52,"area":null},{"id":"2403.04786","title":"Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models","created":"2024-03-03","cited_by_count":44,"area":null},{"id":"2404.00492","title":"Multi-hop Question Answering under Temporal Knowledge Editing","created":"2024-03-30","cited_by_count":36,"area":null},{"id":"2502.12904","title":"Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements","created":"2025-02-18","cited_by_count":32,"area":null},{"id":"2409.14457","title":"Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends","created":"2024-09-22","cited_by_count":26,"area":null},{"id":"2405.15476","title":"Editable Concept Bottleneck Models","created":"2024-05-24","cited_by_count":23,"area":null},{"id":"2410.20197","title":"Transferable Adversarial Attacks on SAM and Its Downstream Models","created":"2024-10-26","cited_by_count":21,"area":null},{"id":"2402.18216","title":"LLM Task Interference: An Initial Study on the Impact of Task-Switch in Conversational History","created":"2024-02-28","cited_by_count":19,"area":null},{"id":"2404.16891","title":"Attacks on Third-Party APIs of Large Language Models","created":"2024-04-24","cited_by_count":15,"area":null},{"id":"2406.04755","title":"LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses","created":"2024-06-07","cited_by_count":15,"area":null},{"id":"2406.18400","title":"Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers","created":"2024-06-26","cited_by_count":15,"area":null},{"id":"2408.12942","title":"Causal-Guided Active Learning for Debiasing Large Language Models","created":"2024-08-23","cited_by_count":15,"area":null},{"id":"2406.15444","title":"Cutting Through the Noise: Boosting LLM Performance on Math Word Problems","created":"2024-05-30","cited_by_count":14,"area":null},{"id":"2405.19740","title":"PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations","created":"2024-05-30","cited_by_count":13,"area":null},{"id":"2405.15452","title":"Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top","created":"2024-05-24","cited_by_count":12,"area":null},{"id":"2406.02524","title":"CheckEmbed: Effective Verification of LLM Solutions to Open-Ended Tasks","created":"2024-06-04","cited_by_count":10,"area":null},{"id":"2410.20940","title":"Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models","created":"2024-10-28","cited_by_count":10,"area":null},{"id":"2409.12257","title":"MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Language","created":"2024-09-18","cited_by_count":9,"area":null},{"id":"2503.08708","title":"TH-Bench: Evaluating Evading Attacks via Humanizing AI Text on Machine-Generated Text Detectors","created":"2025-03-10","cited_by_count":8,"area":null},{"id":"2503.19540","title":"FLEX: A Benchmark for Evaluating Robustness of Fairness in Large Language Models","created":"2025-03-25","cited_by_count":8,"area":null},{"id":"2402.11271","title":"MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions","created":"2024-02-17","cited_by_count":7,"area":null},{"id":"2402.14837","title":"An Empirical Categorization of Prompting Techniques for Large Language Models: A Practitioner's Guide","created":"2024-02-18","cited_by_count":7,"area":null},{"id":"2503.18360","title":"J&H: Evaluating the Robustness of Large Language Models Under Knowledge-Injection Attacks in Legal Domain","created":"2025-03-24","cited_by_count":7,"area":null},{"id":"2506.00089","title":"TRAPDOC: Deceiving LLM Users by Injecting Imperceptible Phantom Tokens into Documents","created":"2025-05-30","cited_by_count":6,"area":null},{"id":"2502.04643","title":"Confidence Elicitation: A New Attack Vector for Large Language Models","created":"2025-02-07","cited_by_count":5,"area":null},{"id":"2512.23430","title":"C2PO: Diagnosing and Disentangling Bias Shortcuts in LLMs","created":"2025-12-29","cited_by_count":5,"area":null},{"id":"2311.08107","title":"SAIE Framework: Support Alone Isn't Enough -- Advancing LLM Training with Adversarial Remarks","created":"2023-11-14","cited_by_count":4,"area":null},{"id":"2409.02649","title":"OpenFact at CheckThat! 2024: Combining Multiple Attack Methods for Effective Adversarial Text Generation","created":"2024-09-04","cited_by_count":4,"area":null},{"id":"2412.00621","title":"Exposing LLM Vulnerabilities: Adversarial Scam Detection and Performance","created":"2024-12-01","cited_by_count":4,"area":null},{"id":"2502.15609","title":"On the Robustness of Transformers against Context Hijacking for Linear Classification","created":"2025-02-21","cited_by_count":4,"area":null},{"id":"2505.15386","title":"RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection","created":"2025-05-21","cited_by_count":4,"area":null},{"id":"2406.10802","title":"KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge Graphs","created":"2024-06-16","cited_by_count":3,"area":null},{"id":"2506.03627","title":"Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks","created":"2025-06-04","cited_by_count":3,"area":null},{"id":"2506.05286","title":"Stable Vision Concept Transformers for Medical Diagnosis","created":"2025-06-05","cited_by_count":3,"area":null},{"id":"2401.07441","title":"Stability Analysis of ChatGPT-based Sentiment Analysis in AI Quality Assurance","created":"2024-01-15","cited_by_count":2,"area":null},{"id":"2408.13985","title":"TF-Attack: Transferable and Fast Adversarial Attacks on Large Language Models","created":"2024-08-26","cited_by_count":2,"area":null},{"id":"2508.16267","title":"From Confidence to Collapse in LLM Factual Robustness","created":"2025-08-22","cited_by_count":2,"area":null},{"id":"2509.20321","title":"Conversational Speech Reveals Structural Robustness Failures in SpeechLLM Backbones","created":"2025-09-24","cited_by_count":2,"area":null},{"id":"2601.00451","title":"Controllable Concept Bottleneck Models","created":"2026-01-01","cited_by_count":2,"area":null},{"id":"2608.26701","title":"Accelerating Scientific Research with Gemini in the Real-World","created":"2026-08-27","cited_by_count":2,"area":null},{"id":"2402.15929","title":"Certifying Knowledge Comprehension in LLMs","created":"2024-02-24","cited_by_count":1,"area":null},{"id":"2412.13705","title":"Mitigating Adversarial Attacks in LLMs through Defensive Suffix Generation","created":"2024-12-18","cited_by_count":1,"area":null},{"id":"2509.10682","title":"LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems","created":"2025-09-12","cited_by_count":1,"area":null},{"id":"2511.05919","title":"Injecting Falsehoods: Adversarial Man-in-the-Middle Attacks Undermining Factual Recall in LLMs","created":"2025-11-08","cited_by_count":1,"area":null},{"id":"2601.16890","title":"LLM-Based Adversarial Persuasion Attacks on Fact-Checking Systems","created":"2026-01-23","cited_by_count":1,"area":null},{"id":"2604.19724","title":"Benign Overfitting in Adversarial Training for Vision Transformers","created":"2026-04-21","cited_by_count":1,"area":null},{"id":"2609.34457","title":"ZonoGPT: Towards An Abstract Domain for Verifying Large GPT Models","created":"2026-09-28","cited_by_count":1,"area":null},{"id":"2408.02814","title":"Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services","created":"2024-08-05","cited_by_count":0,"area":null},{"id":"2502.07101","title":"SMAB: MAB based word Sensitivity Estimation Framework and its Applications in Adversarial Text Generation","created":"2025-02-10","cited_by_count":0,"area":null},{"id":"2505.16888","title":"PARASITE: Conditional System Prompt Poisoning to Hijack LLMs","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2507.05565","title":"Search-based Selection of Metamorphic Relations for Optimized Robustness Testing of Large Language Models","created":"2025-07-08","cited_by_count":0,"area":null},{"id":"2511.03128","title":"From Insight to Exploit: Leveraging LLM Collaboration for Adaptive Adversarial Text Generation","created":"2025-11-05","cited_by_count":0,"area":null},{"id":"2601.10524","title":"Diagnosing Generalization Failures in Fine-Tuned LLMs: A Cross-Architectural Study on Phishing Detection","created":"2026-01-15","cited_by_count":0,"area":null},{"id":"2603.21155","title":"Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2605.29678","title":"Spurious Prompts: Can Irrelevant Prompts Steer Large Language Models?","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.30556","title":"Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task?","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2610.02841","title":"How Robust Is Multimodal Claim Verification to LLM Rewriting?","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}