Diverse and Effective Red Teaming Auto-gen Rewards & Multi-step RL | #aisafety #openai #genai #2024
AI Today27 Nov 2024

Diverse and Effective Red Teaming Auto-gen Rewards & Multi-step RL | #aisafety #openai #genai #2024

Paper: https://cdn.openai.com/papers/diverse... Blog: https://openai.com/index/advancing-re... This OpenAI research paper presents novel methods for automated red teaming of large language models (LLMs). The approach factorizes the red-teaming task into generating diverse attack goals and then training a reinforcement learning (RL) attacker to achieve those goals effectively and diversely. Key contributions include using automatically generated rule-based rewards and a multi-step RL process that encourages stylistic diversity in attacks. The methods are applied to two tasks: indirect prompt injection and safety "jailbreaking," demonstrating improved diversity and effectiveness compared to prior approaches. The paper also addresses limitations and suggests future research directions. ai , model , ai safety , openai, genai, generativeai, artificialintelligence , arxiv , research , paper , publication, reinforcement learning, rl

Episoder(30)

Mixtures of In-Context Learners | #ai #genai #llm #2024 #ml

Mixtures of In-Context Learners | #ai #genai #llm #2024 #ml

Paper: https://arxiv.org/pdf/2411.02830 This research introduces Mixtures of In-Context Learners (MOICL), a novel approach to improve in-context learning (ICL) in large language models (LLMs). MOICL ...

27 Nov 202414min

LLM2CLIP: POWERFUL LM UNLOCKS RICHER VISUAL REPRESENTATION | #ai #genai #lvm #llm #mmm #cv #ms #2024

LLM2CLIP: POWERFUL LM UNLOCKS RICHER VISUAL REPRESENTATION | #ai #genai #lvm #llm #mmm #cv #ms #2024

Paper: https://arxiv.org/pdf/2411.04997 Github: https://github.com/microsoft/LLM2CLIP The paper introduces LLM2CLIP, a method to improve the visual representation learning capabilities of CLIP by int...

27 Nov 202414min

OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024

OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024

Paper: https://arxiv.org/pdf/2411.14199 Github: https://github.com/AkariAsai/OpenScholar The research introduces OpenScholar, a retrieval-augmented large language model (LLM) designed for synthesizin...

27 Nov 202414min

Bilateral Reference for High-Resolution Dichotomous Image Segmentation | #ai #genai #llm #cv #2024

Bilateral Reference for High-Resolution Dichotomous Image Segmentation | #ai #genai #llm #cv #2024

Paper: https://arxiv.org/pdf/2401.03407 Github: https://github.com/ZhengPeng7/BiRefNet This research introduces BiRefNet, a novel deep learning framework for high-resolution dichotomous image segment...

27 Nov 202414min

LLaVA-o1: Let Vision Language Models Reason Step-by-Step | #ai #genai #lvm #llm #mmm #cv #2024

LLaVA-o1: Let Vision Language Models Reason Step-by-Step | #ai #genai #lvm #llm #mmm #cv #2024

Paper: https://arxiv.org/pdf/2411.10440 Github: https://github.com/PKU-YuanGroup/LLaV... The paper introduces LLaVA-o1, a vision-language model designed for improved multi-stage reasoning. Unlike pre...

27 Nov 202414min

Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024

Model-Based Transfer Learning for Contextual Reinforcement Learning | #ai #mit #rl #genai #ml #2024

Paper: https://arxiv.org/pdf/2408.04498 This research introduces Model-Based Transfer Learning (MBTL), a novel framework for improving the efficiency and robustness of deep reinforcement learning (RL...

27 Nov 202414min

OpenAI’s Approach to External Red Teaming for AI Models and System | #aisafety #openai #genai #2024

OpenAI’s Approach to External Red Teaming for AI Models and System | #aisafety #openai #genai #2024

Paper: https://cdn.openai.com/papers/openais... Blog: https://openai.com/index/advancing-re... This white paper details OpenAI's approach to external red teaming for AI models and systems. External r...

27 Nov 202414min

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