{"total":18,"rows":[{"id":"2307.16630","title":"Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks","created":"2023-07-31","cited_by_count":34,"area":null},{"id":"2212.09254","title":"TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization","created":"2022-12-19","cited_by_count":21,"area":null},{"id":"2402.01806","title":"HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text","created":"2024-02-02","cited_by_count":16,"area":null},{"id":"2405.19098","title":"Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior","created":"2024-05-29","cited_by_count":11,"area":null},{"id":"2308.11284","title":"LEAP: Efficient and Automated Test Method for NLP Software","created":"2023-08-22","cited_by_count":6,"area":null},{"id":"2212.10258","title":"In and Out-of-Domain Text Adversarial Robustness via Label Smoothing","created":"2022-12-20","cited_by_count":5,"area":null},{"id":"2403.11833","title":"SSCAE -- Semantic, Syntactic, and Context-aware natural language Adversarial Examples generator","created":"2024-03-18","cited_by_count":4,"area":null},{"id":"2405.04346","title":"Revisiting Character-level Adversarial Attacks for Language Models","created":"2024-05-07","cited_by_count":4,"area":null},{"id":"2306.05659","title":"COVER: A Heuristic Greedy Adversarial Attack on Prompt-based Learning in Language Models","created":"2023-06-09","cited_by_count":3,"area":null},{"id":"2502.01936","title":"Query-Based and Unnoticeable Graph Injection Attack from Neighborhood Perspective","created":"2025-02-04","cited_by_count":3,"area":null},{"id":"2407.19216","title":"EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection","created":"2024-07-27","cited_by_count":2,"area":null},{"id":"2501.02654","title":"Tougher Text, Smarter Models: Raising the Bar for Adversarial Defence Benchmarks","created":"2025-01-05","cited_by_count":2,"area":null},{"id":"2506.03355","title":"Robustness in Both Domains: CLIP Needs a Robust Text Encoder","created":"2025-06-03","cited_by_count":2,"area":null},{"id":"2509.22393","title":"Text Adversarial Attacks with Dynamic Outputs","created":"2025-09-26","cited_by_count":2,"area":null},{"id":"2402.02695","title":"Exploiting Class Probabilities for Black-box Sentence-level Attacks","created":"2024-02-05","cited_by_count":1,"area":null},{"id":"2508.10039","title":"Multi-task Adversarial Attacks against Black-box Model with Few-shot Queries","created":"2025-08-10","cited_by_count":1,"area":null},{"id":"2402.16470","title":"Unveiling Vulnerability of Self-Attention","created":"2024-02-26","cited_by_count":0,"area":null},{"id":"2603.10842","title":"PivotAttack: Rethinking the Search Trajectory in Hard-Label Text Attacks via Pivot Words","created":"2026-03-11","cited_by_count":0,"area":null}],"next_cursor":null}