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

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SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with MotionAware Mem | #2024

SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with MotionAware Mem | #2024

Paper: https://arxiv.org/pdf/2411.11922 Github: https://github.com/yangchris11/samurai Blog: https://yangchris11.github.io/samurai/ The paper introduces SAMURAI, a novel visual object tracking method...

27 Marras 202414min

Adding Error Bars to Evals: A Statistical Approach to LM Evaluations | #llm #genai #anthropic #2024

Adding Error Bars to Evals: A Statistical Approach to LM Evaluations | #llm #genai #anthropic #2024

Github: https://arxiv.org/pdf/2411.00640 This research paper advocates for incorporating rigorous statistical methods into the evaluation of large language models (LLMs). It introduces formulas for c...

27 Marras 202414min

Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions | #ai #llm #alibaba #genai #2024

Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions | #ai #llm #alibaba #genai #2024

Paper: https://arxiv.org/pdf/2411.14405 Github: https://github.com/AIDC-AI/Marco-o1 The Alibaba MarcoPolo team introduces Marco-o1, a large reasoning model designed to excel in open-ended problem-sol...

27 Marras 202414min

FLUX.I TOOLS | #ai #computervision #cv #BlackForestLabs #2024

FLUX.I TOOLS | #ai #computervision #cv #BlackForestLabs #2024

Github: https://github.com/black-forest-labs/... Black Forest Labs announced FLUX.1 Tools, a suite of four open-access and API-based models enhancing their FLUX.1 text-to-image model. FLUX.1 Fill exc...

27 Marras 202414min

Tülu 3 opens language model post-training up to more tasks and more people | #ai #llm #allenai #2024

Tülu 3 opens language model post-training up to more tasks and more people | #ai #llm #allenai #2024

Blog: https://allenai.org/blog/tulu-3 Summary The Allen Institute for Artificial Intelligence (Ai2) has released Tülu 3, an open-source family of post-trained language models. Unlike closed models fr...

27 Marras 202414min

Multimodal Autoregressive Pre-training of Large Vision Encoders | #ai #computervision #apple #2024

Multimodal Autoregressive Pre-training of Large Vision Encoders | #ai #computervision #apple #2024

Paper: https://arxiv.org/pdf/2411.14402 Github Link: https://github.com/apple/ml-aim This research introduces AIMV2, a family of large-scale vision encoders pre-trained using a novel multimodal auto...

27 Marras 202414min