2 papers
cs.LG2026
Olmix: A Framework for Data Mixing Throughout LM Development
Mayee F. Chen, Tyler Murray, David Heineman +5
Data mixing -- determining the ratios of data from different domains -- is a first-order concern for training language models (LMs). While existing mixing methods show promise, the…
cs.LG2026
How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs
Yapei Chang, Kyle Lo, Mohit Iyyer +1
Generating step-by-step "how-to" procedures is a key LLM capability: how-to advice is commonly requested in chatbots, and step-by-step planning is critical for reasoning over compl…