R2-MultiOmnia: Leading Multilingual Multimodal Reasoning via Self-Training (2025.acl-long)
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| Challenge: | Recent studies have introduced eclectic strategies to enhance MLLMs’ reasoning capabilities, but they remain related to a single language. |
| Approach: | They propose a modular approach that instructs models to abstract key elements of the reasoning process and refine reasoning trajectories via self-correction. |
| Outcome: | The proposed approach improves multimodal reasoning, gets aligned performances among the languages approaching strong models and improves the model's performance. |
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