2 citations · 3 across the 7 of their papers we have counts for
3 papers · 1 filter
Asymmetric Prompt Weighting for Reinforcement Learning with Verifiable Rewards
Reinhard Heckel, Mahdi Soltanolkotabi, Christos Thramboulidis
Reinforcement learning with verifiable rewards has driven recent advances in LLM post-training, in particular for reasoning. Policy optimization algorithms generate a number of res…
Trace Reconstruction with Language Models
Franziska Weindel, Michael Girsch, Reinhard Heckel
The general trace reconstruction problem seeks to recover an original sequence from its noisy copies independently corrupted by insertions, deletions, and substitutions. This probl…
OpenThoughts: Data Recipes for Reasoning Models
Etash Guha, Ryan Marten, Sedrick Keh +47
Reasoning models have made rapid progress on many benchmarks involving math, code, and science. Yet, there are still many open questions about the best training recipes for reasoni…