mlsanityData to 14 Oct 2026

WalledEval: A Comprehensive Safety Evaluation Toolkit for Large Language Models

arXiv 2408.03837 ↗First posted 7 Aug 2024cs.CL cs.AIcited by 17

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Abstract (arXiv)

WalledEval is a comprehensive AI safety testing toolkit designed to evaluate large language models (LLMs). It accommodates a diverse range of models, including both open-weight and API-based ones, and features over 35 safety benchmarks covering areas such as multilingual safety, exaggerated safety, and prompt injections. The framework supports both LLM and judge benchmarking and incorporates custom mutators to test safety against various text-style mutations, such as future tense and paraphrasing. Additionally, WalledEval introduces WalledGuard, a new, small, and performant content moderation tool, and two datasets: SGXSTest and HIXSTest, which serve as benchmarks for assessing the exaggerated safety of LLMs and judges in cultural contexts. We make WalledEval publicly available at https://github.com/walledai/walledeval.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 21 of its 26 references that are in the map. First posted on arXiv 7 Aug 2024.

Builds on

21 of 26 references.

References · 21

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  5. 2023Qwen Technical Reportcited by 3,344
  6. 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 3,104
  7. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
  8. 2024Gemma 2: Improving Open Language Models at a Practical Sizecited by 1,998
  9. 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phonecited by 1,917
  10. 2024HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusalcited by 1,429
  11. 2023Jailbreaking Black Box Large Language Models in Twenty Queriescited by 1,420
  12. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,207
9 more
  1. 2023Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!cited by 1,154
  2. 2021Datasets: A Community Library for Natural Language Processingcited by 530
  3. 2023A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easilycited by 259
  4. 2024Aya 23: Open Weight Releases to Further Multilingual Progresscited by 123
  5. 2024Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmeticcited by 112
  6. 2024Does Refusal Training in LLMs Generalize to the Past Tense?cited by 79
  7. 2024The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harmcited by 70
  8. 2024Introducing v0.5 of the AI Safety Benchmark from MLCommonscited by 62
  9. 2024LionGuard: Building a Contextualized Moderation Classifier to Tackle Localized Unsafe Contentcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 10; 2026: 4.

17 papers.

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  1. 2024Survey of Cultural Awareness in Language Models: Text and Beyondcited by 103
  2. 2024Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarkingcited by 35
  3. 2025The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMscited by 26
  4. 2025o3-mini vs DeepSeek-R1: Which One is Safer?cited by 24
  5. 2025Early External Safety Testing of OpenAI's o3-mini: Insights from the Pre-Deployment Evaluationcited by 13
  6. 2026Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scalingcited by 13
  7. 2025On Jailbreaking Quantized Language Models Through Fault Injection Attackscited by 8
  8. 2025ASTRAL: Automated Safety Testing of Large Language Modelscited by 7
  9. 2024Boosting LLM Translation Skills without General Ability Loss via Rationale Distillationcited by 6
  10. 2025From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMscited by 6
  11. 2025EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructionscited by 6
  12. 2025Quantifying CBRN Risk in Frontier Modelscited by 6
5 more
  1. 2026How Sensitive Are Safety Benchmarks to Judge Configuration Choices?cited by 5
  2. 2025Psychometric Personality Shaping Modulates Capabilities and Safety in Language Modelscited by 4
  3. 2026RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Modelscited by 3
  4. 2025TRUSTVIS: A Multi-Dimensional Trustworthiness Evaluation Framework for Large Language Modelscited by 0
  5. 2026Localizing Safety Alignment: MLP Layers and Mid-Network Blocks Encode Refusal Behavior in Large Language Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025SDEval: Safety Dynamic Evaluation for Multimodal Large Language Models
  2. 2024ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming
  3. 2024S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models
  4. 2025SafeLawBench: Towards Safe Alignment of Large Language Models
  5. 2024SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety
  6. 2024SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models
  7. 2025CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models
  8. 2024Benchmarking LLM Guardrails in Handling Multilingual Toxicity