Alternatives and similar repositories for R-Judge:

Users that are interested in R-Judge are comparing it to the libraries listed below

• SafeAILab / RAIN
  [ICLR'24] RAIN: Your Language Models Can Align Themselves without Finetuning
  ☆89Updated 9 months ago
• pillowsofwind / Course-Correction
  [EMNLP 2024] The official GitHub repo for the paper "Course-Correction: Safety Alignment Using Synthetic Preferences"
  ☆19Updated 5 months ago
• RobustNLP / DeRTa
  A novel approach to improve the safety of large language models, enabling them to transition effectively from unsafe to safe state.
  ☆58Updated last month
• xbmxb / EnvDistraction
  ☆17Updated 5 months ago
• XuandongZhao / weak-to-strong
  Weak-to-Strong Jailbreaking on Large Language Models
  ☆72Updated last year
• pillowsofwind / Knowledge-Conflicts-Survey
  [EMNLP 2024] The official GitHub repo for the survey paper "Knowledge Conflicts for LLMs: A Survey"
  ☆107Updated 5 months ago
• OpenSafetyLab / SALAD-BENCH
  【ACL 2024】 SALAD benchmark & MD-Judge
  ☆134Updated last week
• tatsu-lab / test_set_contamination
  ☆37Updated last year
• Jometeorie / KnowledgeSpread
  ☆29Updated 5 months ago
• IS2Lab / S-Eval
  S-Eval: Automatic and Adaptive Test Generation for Benchmarking Safety Evaluation of Large Language Models
  ☆54Updated last month
• Princeton-SysML / Jailbreak_LLM
  ☆165Updated last year
• PKU-Alignment / beavertails
  BeaverTails is a collection of datasets designed to facilitate research on safety alignment in large language models (LLMs).
  ☆126Updated last year
• GodXuxilie / PromptAttack
  An LLM can Fool Itself: A Prompt-Based Adversarial Attack (ICLR 2024)
  ☆79Updated last month
• hongbinye / Cognitive-Mirage-Hallucinations-in-LLMs
  Repository for the paper "Cognitive Mirage: A Review of Hallucinations in Large Language Models"
  ☆47Updated last year
• thu-coai / AutoDetect
  Official github repo for AutoDetect, an automated weakness detection framework for LLMs.
  ☆41Updated 8 months ago
• princeton-nlp / LLMBar
  [ICLR 2024] Evaluating Large Language Models at Evaluating Instruction Following
  ☆121Updated 8 months ago
• liyucheng09 / Contamination_Detector
  Lightweight tool to identify Data Contamination in LLMs evaluation
  ☆47Updated last year
• boyiwei / CoTaEval
  [NeurIPS 2024 D&B] Evaluating Copyright Takedown Methods for Language Models
  ☆17Updated 8 months ago
• kevinyaobytedance / llm_unlearn
  LLM Unlearning
  ☆145Updated last year
• niconi19 / LLM-Conversation-Safety
  [NAACL2024] Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey
  ☆90Updated 7 months ago
• shizhediao / R-Tuning
  [NAACL 2024 Outstanding Paper] Source code for the NAACL 2024 paper entitled "R-Tuning: Instructing Large Language Models to Say 'I Don't…
  ☆108Updated 8 months ago
• chujiezheng / LLM-Safeguard
  Official repository for ICML 2024 paper "On Prompt-Driven Safeguarding for Large Language Models"
  ☆86Updated 6 months ago
• Improbable-AI / curiosity_redteam
  Official implementation of ICLR'24 paper, "Curiosity-driven Red Teaming for Large Language Models" (https://openreview.net/pdf?id=4KqkizX…
  ☆72Updated last year
• YihanWang617 / LLM-Jailbreaking-Defense-Backtranslation
  Code for paper "Defending aginast LLM Jailbreaking via Backtranslation"
  ☆27Updated 7 months ago
• lancopku / agent-backdoor-attacks
  Code&Data for the paper "Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents" [NeurIPS 2024]
  ☆63Updated 5 months ago
• vinid / safety-tuned-llamas
  ICLR2024 Paper. Showing properties of safety tuning and exaggerated safety.
  ☆78Updated 10 months ago
• ryoungj / ToolEmu
  [ICLR'24 Spotlight] A language model (LM)-based emulation framework for identifying the risks of LM agents with tool use
  ☆130Updated 11 months ago
• DAMO-NLP-SG / multilingual-safety-for-LLMs
  [ICLR 2024]Data for "Multilingual Jailbreak Challenges in Large Language Models"
  ☆67Updated last year
• kevinyaobytedance / llm_eval
  LLM evaluation.
  ☆14Updated last year
• HillZhang1999 / ICD
  Code & Data for our Paper "Alleviating Hallucinations of Large Language Models through Induced Hallucinations"
  ☆63Updated last year