Parallel Speaker–Listener Large Language Models (PaSLLMs): Non-Sequential Text Generation via Token-Set Prediction and Differentiable Reordering
Year: 2025
Type: article
Abstract: This work presents a theoretical framework for reformulating large language model generation using a parallel Speaker–Listener architecture. The approach decouples semantic content prediction from linguistic ordering through an unordered token-set representation and differentiable reordering mechanisms. The framework aims to explore alternatives to sequential autoregressive decoding and expand the design space for modular, distributed inference in large-scale language models. No empirical results are claimed; the contribution is conceptual and architectural.
Author: Tirumala, Bharadwaj
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7106449137
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