Papers with DDA
Domain Differential Adaptation for Neural Machine Translation (D19-56)
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| Challenge: | Neural networks are data hungry and domain sensitive, so it is difficult to obtain labeled data for every domain. |
| Approach: | They propose a framework for domain adaptation where we model the difference between domains instead of smoothing over them. |
| Outcome: | The proposed framework improves on domain adaptation in multiple experimental settings. |
ODDA: An OODA-Driven Diverse Data Augmentation Framework for Low-Resource Relation Extraction (2025.findings-acl)
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| Challenge: | Existing methods for low-resource relation extraction (LRE) lack diversity, leading to suboptimal performance. |
| Approach: | They propose to use large language models to augment relation extraction models by observing the RE model's behavior and replacing schema constraints with attribute constraints. |
| Outcome: | Experiments on three widely-used benchmarks show that the proposed method outperforms state-of-the-art methods while maintaining enhanced model stability. |
Enhancing Training Data Attribution for Large Language Models with Fitting Error Consideration (2024.emnlp-main)
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| Challenge: | Large language models (LLMs) are difficult to interpret due to their black-box nature and randomness. |
| Approach: | They propose a new method which enhances influence functions by addressing fitting errors by eliminating knowledge bias present in the base model before fine-tuning. |
| Outcome: | The proposed method outperforms existing methods and achieves an average AUC of 91.64%. |
Explaining Matters: Leveraging Definitions and Semantic Expansion for Sexism Detection (2025.acl-long)
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| Challenge: | Existing tools for sexism detection fail to capture subtle distinctions within sexist content, limiting their practical applicability. |
| Approach: | They propose two techniques to address class imbalance and nuanced nature of sexist language . definition-based data augmentation leverages category-specific definitions to generate semantically-aligned examples . |
| Outcome: | The proposed techniques improve accuracy across all tasks and improve reliability. |
In Search of the Lost Arch in Dialogue: A Dependency Dialogue Acts Corpus for Multi-Party Dialogues (2025.findings-acl)
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Jon Cai, Brendan King, Peyton Cameron, Susan Windisch Brown, Miriam Eckert, Dananjay Srinivas, George Arthur Baker, V Kate Everson, Martha Palmer, James Martin, Jeffrey Flanigan
| Challenge: | Understanding speaker intentions remains a challenge in NLP . a number of corpora annotated using theoretical frameworks of dialogue focus on utterance-level labeling of speaker intent, missing wider context, or the rhetorical structure of a dialogue. |
| Approach: | They propose to annotate a corpus of 33 dialogues and over 9,000 utterance units using the Dependency Dialogue Acts framework. |
| Outcome: | The proposed corpus spans four genres of multi-party conversations from different modalities. |