Language-Grounded Multi-Domain Image Translation via Semantic Difference Guidance (2026.eacl-long)
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| Challenge: | Existing methods for image-to-image translation lack structural integrity and attribute-specific control . Existing approaches lack semantics and provide fine-grained, attribute-based control compared to GAN-based methods . |
| Approach: | They propose a language-grounded attribute-controllable translation framework that grounds semantic differences into corresponding visual transformations while preserving unrelated structural and semantic content. |
| Outcome: | Experiments on CelebA(Dialog) and BDD100K show that LACE achieves high visual fidelity, structural preservation, and interpretable domain-specific control, surpassing baselines. |
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| Challenge: | Pretrained multilingual translation models with massive coverage are becoming of the backbone of many translation systems. |
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LaMI: Augmenting Large Language Models via Late Multi-Image Fusion (2026.acl-short)
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| Challenge: | Large Language Models lack visual grounding on visual reasoning, despite training on text alone. |
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| Challenge: | a new protocol allows for a multilingual hierarchy of concepts and images based on native speakers . the results suggest that the current models are not robust enough to handle multilingual data . |
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Bootstrapping Multilingual Semantic Parsers using Large Language Models (2023.eacl-main)
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Learning Translations via Images with a Massively Multilingual Image Dataset (P18-1)
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| Challenge: | Existing datasets for learning translations of words are limited to a few high-resource languages and unrealistically easy settings. |
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Ozan Caglayan, Menekse Kuyu, Mustafa Sercan Amac, Pranava Madhyastha, Erkut Erdem, Aykut Erdem, Lucia Specia
| Challenge: | Pre-trained language models have been shown to improve performance in many natural language tasks. |
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| Challenge: | Multilingual alignment of sentence representations has mostly required bitexts to bridge the gap between languages. |
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Translation-Enhanced Multilingual Text-to-Image Generation (2023.acl-long)
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Multilingual Pixel Representations for Translation and Effective Cross-lingual Transfer (2023.emnlp-main)
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| Challenge: | Recent work shows that pixel representations can be finetuned across scripts without vocabulary extensions, adapters, or transliteration. |
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ControlText: Unlocking Controllable Fonts in Multilingual Text Rendering without Font Annotations (2025.findings-emnlp)
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Bowen Jiang, Yuan Yuan, Xinyi Bai, Zhuoqun Hao, Alyson Yin, Yaojie Hu, Wenyu Liao, Lyle Ungar, Camillo Jose Taylor
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