Alternatives and similar repositories for CoTaEval

Users that are interested in CoTaEval are comparing it to the libraries listed below

• princeton-nlp / benign-data-breaks-safety
  ☆41Updated 9 months ago
• jaechan-repo / muse_bench
  ☆26Updated 11 months ago
• licong-lin / negative-preference-optimization
  ☆60Updated last year
• paul-rottger / xstest
  Röttger et al. (NAACL 2024): "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"
  ☆101Updated 4 months ago
• ethz-spylab / unlearning-vs-safety
  ☆23Updated 9 months ago
• OPTML-Group / Unlearn-Simple
  "Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning" by Chongyu Fan*, Jiancheng Liu*, Licong Lin*, Jingh…
  ☆28Updated 3 weeks ago
• SafeAILab / RAIN
  [ICLR'24] RAIN: Your Language Models Can Align Themselves without Finetuning
  ☆94Updated last year
• OPTML-Group / SOUL
  Official repo for EMNLP'24 paper "SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning"
  ☆26Updated 9 months ago
• OPTML-Group / WAGLE
  Official repo for NeurIPS'24 paper "WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models"
  ☆15Updated 7 months ago
• sail-sg / closer-look-LLM-unlearning
  [ICLR 2025] A Closer Look at Machine Unlearning for Large Language Models
  ☆32Updated 7 months ago
• jinzhuoran / RWKU
  RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models. NeurIPS 2024
  ☆77Updated 9 months ago
• vinid / safety-tuned-llamas
  ICLR2024 Paper. Showing properties of safety tuning and exaggerated safety.
  ☆85Updated last year
• boyiwei / alignment-attribution-code
  [ICML 2024] Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
  ☆80Updated 3 months ago
• yaojin17 / Unlearning_LLM
  [ACL 2024] Code and data for "Machine Unlearning of Pre-trained Large Language Models"
  ☆59Updated 9 months ago
• swj0419 / muse_bench
  ☆22Updated 4 months ago
• git-disl / Vaccine
  This is the official code for the paper "Vaccine: Perturbation-aware Alignment for Large Language Models" (NeurIPS2024)
  ☆44Updated 7 months ago
• XuandongZhao / weak-to-strong
  [ICML 2025] Weak-to-Strong Jailbreaking on Large Language Models
  ☆76Updated 2 months ago
• kevinyaobytedance / llm_unlearn
  LLM Unlearning
  ☆171Updated last year
• declare-lab / resta
  Restore safety in fine-tuned language models through task arithmetic
  ☆28Updated last year
• chujiezheng / LLM-Safeguard
  Official repository for ICML 2024 paper "On Prompt-Driven Safeguarding for Large Language Models"
  ☆92Updated last month
• Lslland / T-Vaccine
  ☆16Updated 3 weeks ago
• zhxieml / remiss-jailbreak
  ☆30Updated last year
• SORRY-Bench / sorry-bench
  Benchmark evaluation code for "SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal" (ICLR 2025)
  ☆56Updated 4 months ago
• ajyl / dpo_toxic
  A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity.
  ☆74Updated 4 months ago
• VITA-Group / SEAL
  Official code for SEAL: Steerable Reasoning Calibration of Large Language Models for Free
  ☆30Updated 3 months ago
• sail-sg / I-FSJ
  Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses (NeurIPS 2024)
  ☆62Updated 6 months ago
• yihuaihong / ConceptVectors
  ConceptVectors Benchmark and Code for the paper "Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces"
  ☆36Updated 5 months ago
• franciscoliu / SKU
  Official code implementation of SKU, Accepted by ACL 2024 Findings
  ☆15Updated 6 months ago
• Vaidehi99 / InfoDeletionAttacks
  ☆44Updated 5 months ago
• deeplearning-wisc / picle
  Official code for ICML 2024 paper on Persona In-Context Learning (PICLe)
  ☆25Updated last year