Improving Visual Sensitivity of LLMs on Multimodal Machine Translation with Metric-based Loss Weighting

arXiv:2609.31169 · cs.CL, cs.AI · Submitted 2026-09-25 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/hplt-project/sacremoses

Terminology

• Fine-Tuning — 98× in this paper · explained in 5 episodes
• Accuracy — 29× in this paper · explained in 1 episode
• Grounding — 7× in this paper · explained in 3 episodes
• Visual Grounding — 7× in this paper · explained in 2 episodes
• In Multimodal Machine Translation — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Empirical Methods in Natural Language Processing — 3× in this paper
• Multimodal Dataset — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Sentence-level Machine Translation — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes
• Visually Conditioned Masked Language Modeling — 1× in this paper

Sources

• OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
• Qwen2.5-VL Technical Report
• Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
• No Language Left Behind: Scaling Human-Centered Machine Translation
• Achieving Human Parity on Automatic Chinese to English News Translation
• Gumbel-Attention for Multi-modal Machine Translation
• Qwen3 Technical Report

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