Papers by Najmeh Sadoughi
Detect, Disambiguate, and Translate: On-Demand Visual Reasoning for Multimodal Machine Translation with Large Vision-Language Models (2025.naacl-long)
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Danyang Liu, Fanjie Kong, Xiaohang Sun, Dhruva Patil, Avijit Vajpayee, Zhu Liu, Vimal Bhat, Najmeh Sadoughi
| Challenge: | Multimodal machine translation (MMT) aims to leverage additional modalities beyond text . current MMT systems rely heavily on monolingual English captioning data . |
| Approach: | They propose a reasoning-based framework to leverage large-scale vision-language models for MMT . they propose Detect, Disambiguate, and Translate framework to detect ambiguity in input sentence . |
| Outcome: | The proposed framework outperforms state-of-the-art models in disambiguation accuracy and translation quality. |
An automated medical scribe for documenting clinical encounters (N18-5)
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Gregory Finley, Erik Edwards, Amanda Robinson, Michael Brenndoerfer, Najmeh Sadoughi, James Fone, Nico Axtmann, Mark Miller, David Suendermann-Oeft
| Challenge: | a medical scribe is a clinical professional who charts patient–physician encounters in real time. |
| Approach: | They propose to use multiple speech and language technologies to create an automated medical scribe. |
| Outcome: | a medical scribe can be used as an alternative to human scribes or as an assistive tool for physicians . the system relies on multiple speech and language technologies, including speaker diarization, medical speech recognition, knowledge extraction, and natural language generation. |
Attribute-Controlled Translation with Preference Optimization (2026.findings-eacl)
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| Challenge: | Attribute-controlled translation (ACT) is a natural language processing task that produces translations that satisfy specific constraints on linguistic and stylistic attributes. |
| Approach: | They propose to leverage the contrastive nature of ACT tasks with preference optimization . they also propose to exploit knowledge distillation with synthetically-generated training samples . |
| Outcome: | The proposed approach improves attribute matching and translation quality in small-medium size models. |
From dictations to clinical reports using machine translation (N18-3)
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Gregory Finley, Wael Salloum, Najmeh Sadoughi, Erik Edwards, Amanda Robinson, Nico Axtmann, Michael Brenndoerfer, Mark Miller, David Suendermann-Oeft
| Challenge: | Medical dictation is one of the most common ways to document clinical encounters. |
| Approach: | They propose a machine callytranslation technique that automates post-processing tasks . they show that it outperforms conventional systems in correcting errors . |
| Outcome: | The proposed method outperforms conventional systems in many tasks while being much simpler to maintain. |