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Blog | Machine Learning | Carnegie Mellon University
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Latest posts
Last updated about 1 month ago
Yes, AI, There is a Santa Claus
about 1 month ago
People use LLMs to ask for insight on a variety of important...
Validating LLM-as-a-Judge Systems under Rating Indeterminacy
about 2 months ago
Figure 1: Our framework for validating LLM-as-a-judge systems under rating indeterminacy, where...
Carnegie Mellon at NeurIPS 2025
about 2 months ago
CMU researchers are presenting 156 papers at the Thirty-Ninth Annual Conference on...
How to Explore to Scale RL Training of LLMs on Hard Problems?
2 months ago
Figure 1. Three regimes of exploration: Current RL model can explore via:...
Carnegie Mellon University at EMNLP 2025
3 months ago
CMU researchers are presenting 50 papers at the Thirtieth Conference on Empirical...
Learning from Failure to Tackle Extremely Hard Problems
3 months ago
This blog post is based on the work BaNEL: Exploration Posteriors for...
Diffusion Beats Autoregressive in Data-Constrained Settings
4 months ago
TLDR If you are compute-constrained, use autoregressive models; if you are data-constrained,...
Verlog: A Multi-turn RL framework for LLM agents
5 months ago
Verlog is a multi-turn reinforcement learning framework built for long-horizon LLM-agentic tasks...
Carnegie Mellon University at ICML 2025
7 months ago
CMU researchers are presenting 127 papers at the Forty-Second International Conference on...
RLHF 101: A Technical Tutorial on Reinforcement Learning from Human Feedback
8 months ago
Reinforcement Learning from Human Feedback (RLHF) is a popular technique used to...
Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning
8 months ago
Machine unlearning is a promising approach to mitigate undesirable memorization of training...
Carnegie Mellon University at ICLR 2025
9 months ago
CMU researchers are presenting 143 papers at the Thirteenth International Conference on...