Papers by Dana Alon
DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback (2025.naacl-long)
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Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd Van Steenkiste, Ranjay Krishna, Cyrus Rashtchian
| Challenge: | Text-to-Image models (T2I) still struggle to produce images that are both aesthetically pleasing and faithful to the user’s input text. |
| Approach: | They propose a training algorithm that trains T2I models to be faithful to the input text. |
| Outcome: | The proposed model improves both the semantic alignment and aesthetic appeal of two diffusion-based T2I models, evidenced by multiple benchmarks (+1.7% on TIFA, +2.9% on DSG1K, +3.4% on VILA aesthetic). |
OpenMSD: Towards Multilingual Scientific Documents Similarity Measurement (2024.lrec-main)
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| Challenge: | Existing methods for finding related papers in different languages are not effective for multilingual SDSM. |
| Approach: | They propose to use Open-access Multilingual Scientific Documents to develop multilingual SDSM models that adjust and extend state-of-the-art methods for English SDSM tasks. |
| Outcome: | The proposed model outperforms baseline methods on multilingual SDSM tasks while preserving the performance of the existing methods. |
PaRaDe: Passage Ranking using Demonstrations with LLMs (2023.findings-emnlp)
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Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui
| Challenge: | Existing studies show that large language models can be instructed to perform zero-shot passage re-ranking . Existing work like UPR demonstrate promising results for zero- shot ranking using LLMs . |
| Approach: | They propose a demonstration selection strategy based on difficulty rather than semantic similarity . they propose to include only one demonstration in the prompt to improve re-ranking . |
| Outcome: | The proposed method improves LLM-based re-ranking by adding one demonstration to the prompt. |