Category
Research
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Evaluating fairness in ChatGPT
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MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
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Learning to reason with LLMs
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OpenAI o1-mini
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OpenAI o1 System Card External Testers Acknowledgements
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Introducing SWE-bench Verified
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GPT-4o System Card External Testers Acknowledgements
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Improving Model Safety Behavior with Rule-Based Rewards
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GPT-4o mini: advancing cost-efficient intelligence
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Prover-Verifier Games improve legibility of language model outputs
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OpenAI and Los Alamos National Laboratory announce research partnership
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A Holistic Approach to Undesired Content Detection in the Real World
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A Holistic Approach to Undesired Content Detection in the Real World
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Consistency Models
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Improved Techniques for Training Consistency Models
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Extracting Concepts from GPT-4
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Hello GPT-4o
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Understanding the source of what we see and hear online
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The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions
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Video generation models as world simulators
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Building an early warning system for LLM-aided biological threat creation
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Improving mathematical reasoning with process supervision
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Democratic inputs to AI
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GPTs are GPTs: An early look at the labor market impact potential of large language models
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GPT-4
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Point-E: A system for generating 3D point clouds from complex prompts
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Scaling laws for reward model overoptimization
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Introducing Whisper
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Efficient training of language models to fill in the middle
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DALL·E 2 pre-training mitigations
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Learning to play Minecraft with Video PreTraining
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Evolution through large models
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Techniques for training large neural networks
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Teaching models to express their uncertainty in words
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Hierarchical text-conditional image generation with CLIP latents
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A research agenda for assessing the economic impacts of code generation models
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Solving (some) formal math olympiad problems
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Text and code embeddings by contrastive pre-training
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WebGPT: Improving the factual accuracy of language models through web browsing
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Solving math word problems
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TruthfulQA: Measuring how models mimic human falsehoods
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Introducing Triton: Open-source GPU programming for neural networks
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Evaluating large language models trained on code
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Multimodal neurons in artificial neural networks
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Understanding the capabilities, limitations, and societal impact of large language models
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Understanding the capabilities, limitations, and societal impact of large language models
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Scaling Kubernetes to 7,500 nodes
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CLIP: Connecting text and images
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DALL·E: Creating images from text
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DALL·E: Creating images from text
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Generative language modeling for automated theorem proving
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Image GPT
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Language models are few-shot learners
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AI and efficiency
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Jukebox
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Improving verifiability in AI development
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Improving verifiability in AI development
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OpenAI Microscope
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Scaling laws for neural language models
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Scaling laws for neural language models
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Dota 2 with large scale deep reinforcement learning
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Deep double descent
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Procgen Benchmark
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GPT-2: 1.5B release
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Solving Rubik’s Cube with a robot hand
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Emergent tool use from multi-agent interaction
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GPT-2: 6-month follow-up
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MuseNet
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Generative modeling with sparse transformers
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OpenAI Five defeats Dota 2 world champions
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Implicit generation and generalization methods for energy-based models
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Neural MMO: A massively multiagent game environment
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Better language models and their implications
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Better language models and their implications
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Computational limitations in robust classification and win-win results
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How AI training scales
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Quantifying generalization in reinforcement learning
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Spinning Up in Deep RL
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Learning concepts with energy functions
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Plan online, learn offline: Efficient learning and exploration via model-based control
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Reinforcement learning with prediction-based rewards
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FFJORD: Free-form continuous dynamics for scalable reversible generative models
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FFJORD: Free-form continuous dynamics for scalable reversible generative models
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The International 2018: Results
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Large-scale study of curiosity-driven learning
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OpenAI Five Benchmark: Results
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Learning dexterity
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Variational option discovery algorithms
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Glow: Better reversible generative models
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Learning Montezuma’s Revenge from a single demonstration
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OpenAI Five
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Retro Contest: Results
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Learning policy representations in multiagent systems
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GamePad: A learning environment for theorem proving
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Gym Retro
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AI and compute
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Evolved Policy Gradients
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Gotta Learn Fast: A new benchmark for generalization in RL
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Retro Contest
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Variance reduction for policy gradient with action-dependent factorized baselines