Papers with multimodal LLM

3 papers
Listen Again and Choose the Right Answer: A New Paradigm for Automatic Speech Recognition with Large Language Models (2024.findings-acl)

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Challenge: Recent advances in large language models (LLMs) have promoted generative error correction (GER) for automatic speech recognition (ASR).
Approach: They propose a multimodal LLM to receive source speech as extra input and reformat it as a cloze test with logits calibration to remove input information redundancy and simplify GER with clear instructions.
Outcome: The proposed model improves on 9 popular ASR datasets and is faster than vanilla GER.
STELLA: A Multimodal LLM for Protein Functional Annotation via Unified Sequence-Structure Encoding (2026.findings-acl)

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Challenge: a multimodal protein language model (LLM) integrates sequence, structure, and function into functional annotation.
Approach: They propose a multimodal protein language model that synergistically aligns bimodal representations with the textual modality to advance protein functional annotation.
Outcome: The proposed model synergizes bimodal representations with the textual modality to advance protein functional annotation.
MAviS: A Multimodal Conversational Assistant For Avian Species (2025.emnlp-main)

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Challenge: Existing multimodal large language models face challenges when it comes to specialized topics like avian species.
Approach: They propose a large-scale multimodal avian species dataset that integrates image, audio, and text modalities for over 1,000 bird species.
Outcome: The proposed model outperforms the baseline MiniCPM-o-2.6 by a large margin.

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