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Found 5 papers, 0 papers with code
SteP: Stacked LLM Policies for Web Actions
Performing tasks on the web presents fundamental challenges to large language models (LLMs), including combinatorially large open-world tasks and variations across web interfaces.
Learning to Win by Reading Manuals in a Monte-Carlo Framework
In this paper, we present an approach to language grounding which automatically interprets text in the context of a complex control application, such as a game, and uses domain knowledge extracted from the text to improve control performance.
Learning Document-Level Semantic Properties from Free-Text Annotations
The paraphrase structure is linked with a latent topic model of the review texts, enabling the system to predict the properties of unannotated documents and to effectively aggregate the semantic properties of multiple reviews.
Content Modeling Using Latent Permutations
We present a novel Bayesian topic model for learning discourse-level document structure.
