Papers by Ben Hutchinson
Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processing (2024.findings-naacl)
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| Challenge: | This paper concerns the use of religious texts in natural language processing (NLP) religious texts are expressions of culturally important values, and machine learning models reproduce cultural values encoded in training data. |
| Approach: | They argue that NLP's use of religious texts raises considerations beyond model biases . authors argue that religious texts are culturally important and are often used by researchers . |
| Outcome: | The proposed method repurposes translations from their original uses and motivations, and raises considerations beyond model biases. |
Social Biases in NLP Models as Barriers for Persons with Disabilities (2020.acl-main)
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| Challenge: | toxicity prediction and sentiment analysis models perpetuate undesirable social biases from the data on which they are trained. |
| Approach: | They propose to use toxicity prediction and sentiment analysis to examine whether NLP models perpetuate undesirable biases towards mentions of disability. |
| Outcome: | The proposed models contain undesirable biases towards mentions of disability in two English language models. |
Perturbation Sensitivity Analysis to Detect Unintended Model Biases (D19-1)
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| Challenge: | Recent research shows that data-driven NLP models may inadvertently capture, reflect and sometimes amplify various social biases present in the language data they are trained on. |
| Approach: | They propose a generic evaluation framework that detects unintended model biases related to named entities and requires no new annotations or corpora. |
| Outcome: | The proposed framework detects unintended model biases related to named entities and requires no new annotations or corpora. |
”It’s how you do things that matters”: Attending to Process to Better Serve Indigenous Communities with Language Technologies (2024.eacl-short)
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| Challenge: | Indigenous languages are historically under-served by natural language processing (NLP) but this is changing with the recent scaling of large multilingual models and an increased focus by the NLP community on endangered languages. |
| Approach: | They propose to build NLP technologies for Indigenous languages that should primarily serve Indigenous communities. |
| Outcome: | The proposed approach is based on interviews with 17 researchers working in or with Aboriginal and/or Torres Strait Islander communities on language technology projects in Australia. |
Underspecification in Scene Description-to-Depiction Tasks (2022.aacl-main)
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| Challenge: | Recent text-to-image generation systems have demonstrated impressive capabilities . recent work focuses on generating images depicting scenes from scene descriptions . |
| Approach: | They propose a conceptual framework to address implicitness, ambiguity and underspecification issues in multimodal image+text systems. |
| Outcome: | The proposed framework addresses key challenges concerning textual and visual ambiguity and risks that may be amplified by ambiguous and underspecified elements. |