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Machine Learning Blog | ML@CMU | Carnegie Mellon University

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CMU researchers are presenting 156 papers at the Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), held from December 2nd-December 7th at the San Diego Convention. Here is a quick overview of the areas our researchers are working on:

Here are our most frequent collaborator institutions:

Table of Conten...

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People use LLMs to ask for insight on a variety of important questions: future planning, emotional problems, scientific research. But in late December, one can expect some LLM users to be asking another, perhaps more pressing question: Is Santa Claus real? Indeed, children have been consulting external sources for this important question for


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Figure 1: Our framework for validating LLM-as-a-judge systems under rating indeterminacy, where items in a subjective rating task can have multiple “correct” ratings. Our framework provides guidance on (i) how to structure rating tasks to capture rater disagreement, (ii) how to aggregate disagreement into labels, and (iii) ...


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CMU researchers are presenting 156 papers at the Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), held from December 2nd-December 7th at the San Diego Convention. Here is a quick overview of the areas our researchers are working on:

Here are our most frequent collaborator institutions:

Table of Conten...

Read full story

Figure 1. Three regimes of exploration: Current RL model can explore via: (1) sharpening: simply increases likelihood on traces it can sample with high probability; (2) chaining: chain asymmetric skills in the base model (e.g.,


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