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cs.LG2026
Training AI Scientists to Replicate Research
Damon Falck, Samer Sabri, Anja Surina +8
The replicability of papers is a cornerstone of scientific knowledge, ensuring the reliability of existing results and providing a base for further experiments. The act of replicat…
cs.LG2026
Epiplexity Guided Data Selection and Generation for Out-of-Distribution Generalization
Ellen Su, Andres Potapczynski, Shikai Qiu +2
Modern systems are increasingly expected to transfer across tasks not specified during training. What data facilitates generalization in these new, unanticipated settings? One hypo…
cs.LG2025
SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms
Alex Havrilla, Edward Hughes, Mikayel Samvelyan +1
Large language model (LLM) driven synthetic data generation has emerged as a powerful method for improving model reasoning capabilities. However, most methods either distill large…