Papers with cascade paradigm

2 papers
SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities (2023.findings-emnlp)

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Challenge: Existing multi-modal large language models typically adopt the cascade paradigm, preventing inter-modal knowledge transfer.
Approach: They propose a large language model with intrinsic cross-modal conversational abilities . they construct a cross-text speech instruction dataset and employ a three-stage training strategy .
Outcome: The proposed model can follow cross-modal human instructions and handle multiple modalities with one model.
Enhanced Reasoning for Biomedical Document-Level Relation Extraction via a Novel Cascade Language Model Framework (2026.acl-long)

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Challenge: Pre-trained language models (PLMs) are the leading paradigm in document-level relation extraction.
Approach: They propose a cascade framework that leverages the complementary strengths of PLMs and LLMs through a detect-then-rethink paradigm.
Outcome: The proposed framework improves on BioRED and CDR datasets and improves existing models.

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