1 citations · 1 across the 5 of their papers we have counts for
5 papers
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance +4
Large language models (LLMs) are increasingly applied to complex reasoning tasks that require executing several complex steps before receiving any reward. Properly assigning credit…
Learning Action and Reasoning-Centric Image Editing from Videos and Simulations
Benno Krojer, Dheeraj Vattikonda, Luis Lara +4
An image editing model should be able to perform diverse edits, ranging from object replacement, changing attributes or style, to performing actions or movement, which require many…
Reframing linguistic bootstrapping as joint inference using visually-grounded grammar induction models
Eva Portelance, Siva Reddy, Timothy J. O'Donnell
Semantic and syntactic bootstrapping posit that children use their prior knowledge of one linguistic domain, say syntactic relations, to help later acquire another, such as the mea…
Grammar Induction for Minimalist Grammars using Variational Bayesian Inference : A Technical Report
Eva Portelance, Amelia Bruno, Daniel Harasim +2
The following technical report presents a formal approach to probabilistic minimalist grammar parameter estimation. We describe a formalization of a minimalist grammar. We then pre…
A generalized parsing framework for Abstract Grammars
Daniel Harasim, Chris Bruno, Eva Portelance +2
This technical report presents a general framework for parsing a variety of grammar formalisms. We develop a grammar formalism, called an Abstract Grammar, which is general enough…