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Found 4 papers, 2 papers with code
An LLM-based Recommender System Environment
To address these challenges, we propose a comprehensive framework for synthetic environments that simulate human behavior by harnessing the capabilities of large language models (LLMs).
CAESAR: Enhancing Federated RL in Heterogeneous MDPs through Convergence-Aware Sampling with Screening
CAESAR is an aggregation strategy used by the server that combines convergence-aware sampling with a screening mechanism.
Siamese SIREN: Audio Compression with Implicit Neural Representations
Implicit Neural Representations (INRs) have emerged as a promising method for representing diverse data modalities, including 3D shapes, images, and audio.
Examining the Emergence of Deductive Reasoning in Generative Language Models
We conduct a preliminary inquiry into the ability of generative transformer models to deductively reason from premises provided.
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