Dario Amodei

Discovering Language Model Behaviors with Model-Written Evaluations

2022 · arXiv (Cornell University)

As language models (LMs) scale, they develop many novel behaviors, good and bad, exacerbating the need to evaluate how they behave. Prior work creates evaluations with crowdwork (which is time-consuming and expensive) or existing data …

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

2015 · arXiv (Cornell University)

We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages. Because it replaces entire pipelines of hand-engineered components with neural networks, end-to-end learning …

Fine-Tuning Language Models from Human Preferences

2019 · arXiv (Cornell University)

Reward learning enables the application of reinforcement learning (RL) to tasks where reward is defined by human judgment, building a model of reward by asking humans questions. Most work on reward learning has used simulated …

Scaling Laws for Neural Language Models

2020 · arXiv (Cornell University)

This paper develops a transport-validity theory for agentic AI interventions that are first screened on small systems and later considered for frontier-scale deployment. Rather than predicting absolute frontier performance, it asks when a comparative gain …

Language Models are Few-Shot Learners

2020 · arXiv (Cornell University)

Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still …