Language Models as AI Research World Models
cs.CL
Submitted: 2026-10-08
Updated: 2026-10-08
Code: https://github.com/allenai/OLMo-core
Terminology
Sources
- Encoder-Decoder Diffusion Language Models for Efficient Training and Inference
- ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models
- Accelerating Neural Architecture Search using Performance Prediction
- MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
- Evaluating Large Language Models Trained on Code
- Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
- AI Research Preference Models
- What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
- AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive
- World Models
- Dream to Control: Learning Behaviors by Latent Imagination
- Learning Latent Dynamics for Planning from Pixels
- Mastering Diverse Domains through World Models
- AIRA_2: Overcoming Bottlenecks in AI Research Agents
- Training Compute-Optimal Large Language Models
- MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
- When to Trust Your Model: Model-Based Policy Optimization
- Scaling Laws for Neural Language Models
- In-context Reinforcement Learning with Algorithm Distillation
- AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model
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