4 papers
Entropy-Preserving Reinforcement Learning
Aleksei Petrenko, Ben Lipkin, Kevin Chen +4
Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn from exploration on their own trajector…
Fast Controlled Generation from Language Models with Adaptive Weighted Rejection Sampling
Benjamin Lipkin, Benjamin LeBrun, Jacob Hoover Vigly +9
The dominant approach to generating from language models subject to some constraint is locally constrained decoding (LCD), incrementally sampling tokens at each time step such that…
Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo
João Loula, Benjamin LeBrun, Li Du +12
A wide range of LM applications require generating text that conforms to syntactic or semantic constraints. Imposing such constraints can be naturally framed as probabilistic condi…
Models Can and Should Embrace the Communicative Nature of Human-Generated Math
Sasha Boguraev, Ben Lipkin, Leonie Weissweiler +1
Math is constructed by people for people: just as natural language corpora reflect not just propositions but the communicative goals of language users, the math data that models ar…