Papers by Ricard Marxer
Scaling Properties of Speech Language Models (2024.emnlp-main)
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| Challenge: | Speech Language Models (SLMs) aim to learn language from raw audio without textual resources. |
| Approach: | They propose to use scaling properties of neural language models to estimate scale at which SLMs will be trained . they establish a strong correlation between pre-training loss and downstream syntactic and semantic performance . |
| Outcome: | The proposed model will have the English proficiency of text-based Large Language Models. |
SDialog: A Python Toolkit for End-to-End Agent Building, User Simulation, Dialog Generation, and Evaluation (2026.eacl-demo)
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Sergio Burdisso, Séverin Baroudi, Yanis Labrak, David Grünert, Pawel Cyrta, Yiyang Chen, Srikanth Madikeri, Esaú Villatoro-tello, Ricard Marxer, Petr Motlicek
| Challenge: | SDialog is an open-source Python toolkit for end-to-end development, simulation, evaluation and analysis of LLM-based conversational agents. |
| Approach: | They present an open-source Python toolkit for end-to-end development, simulation, evaluation and analysis of LLM-based conversational agents. |
| Outcome: | SDialog enables more controlled, transparent, and systematic research on conversational systems. |