Reinforcement learning from human feedback (RLHF)
Align AI behavior with human preferences through efficient RLHF and DPO workflows using high-quality data
The importance of RLHF and DPO in AI development and alignment
Increase model alignment
Harness a network of highly skilled experts (PHD graduates, engineers, domain experts) to create accurate, custom datasets.
Prioritize human-centric evaluation
Ship LLMs responsibly with human oversight and advanced tooling to efficiently validate model outcomes.
Optimize relevance
Prioritize the right user feedback to automatically improve your model’s accuracy and performance.
Mitigate biases
Reduce or eliminate biases present in the pre-trained model to align with your organization’s preferences.
Enhance model performance and alignment with RLHF
Through reinforcement learning with human feedback (RLHF), LLMs are trained to better align with human preferences and adapt to dynamic environments. Differentiated training data from expert human evaluations help refining foundational models, allowing them to handle more complex and nuanced tasks.
Overcoming human data challenges
Human feedback is essential for RLHF but can be costly, time-consuming, and prone to bias and inaccuracies. Ensuring the quality and consistency of human evaluators is not easy. Teams need tools and systems that provide strong collaboration, clear evaluation guidelines, and key real-time metrics.
Build next-generation LLMs with Labelbox
Labelbox's combination of highly skilled annotators and advanced software delivers high-quality human preference data across a wide range of specialized domains and languages.The underlying platform powers human-in-the loop workflows, real-time quality control, and transparent collaboration to build state-of-the-art LLM models.
Labelbox has enabled us to dramatically improve our model performance for our most critical AI initiatives by tapping into their network of expert labelers and platform for human evaluation. In the past two months, our document intelligence teams are seeing a 2X increase in data quality compared to other vendors. We continue to work with Labelbox to further enhance our genAI capabilities and to hit our development timelines.
Why Labelbox for RLHF
Generate high-quality preference data
Tap into Labelbox's dedicated workforce of expert AI trainers to generate large volumes of high-quality, nuanced preference data across various domains and languages to efficiently fine-tune your model on diverse preferences.
Accelerate model alignment
Utilize custom, differentiated data in RLHF and DPO workflows to seamlessly integrate human feedback into your training process. Quickly align your model's outputs with user expectations and improve overall satisfaction.
Boost frontier performance
Go beyond basic metrics. Labelbox provides granular performance dashboards that give you deep insights into your model's strengths and weaknesses. Identify outliers quickly with visual queues and iterate faster with data-driven decisions.
Reduce costs and maximize ROI
Streamline and customize your RLHF workflows, reducing the time and resources required for data collection and model training. Maximize your return on investment with efficient processes backed by industry-leading software.