Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Yada Pruksachatkun"'
Autor:
Yang Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan
Multiple metrics have been introduced to measure fairness in various natural language processing tasks. These metrics can be roughly categorized into two categories: 1) \emph{extrinsic metrics} for evaluating fairness in downstream applications and 2
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3467ba85c4dbc7d917e39f1bac180dc7
http://arxiv.org/abs/2203.13928
http://arxiv.org/abs/2203.13928
Publikováno v:
ACL/IJCNLP (Findings)
Existing bias mitigation methods to reduce disparities in model outcomes across cohorts have focused on data augmentation, debiasing model embeddings, or adding fairness-based optimization objectives during training. Separately, certified word substi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5436f52f1420365d6d542e5bd8f25d3
http://arxiv.org/abs/2106.10826
http://arxiv.org/abs/2106.10826
Autor:
Satyapriya Krishna, Jwala Dhamala, Tony Sun, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Yada Pruksachatkun
Publikováno v:
FAccT
Recent advances in deep learning techniques have enabled machines to generate cohesive open-ended text when prompted with a sequence of words as context. While these models now empower many downstream applications from conversation bots to automatic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c9c887a4cd9f5a38fe4317540b6c3ad
https://doi.org/10.1145/3442188.3445924
https://doi.org/10.1145/3442188.3445924
Autor:
Hui Dai, Yada Pruksachatkun, Sean Adler, James Mullenbach, Yi Yang, David Sontag, Jennifer Seale, Jordan Swartz, T. Greg McKelvey
Publikováno v:
ACL/IJCNLP (1)
Continuity of care is crucial to ensuring positive health outcomes for patients discharged from an inpatient hospital setting, and improved information sharing can help. To share information, caregivers write discharge notes containing action items t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::896b6f39e01df66d297b4baac6e99406
https://doi.org/10.18653/v1/2021.acl-long.109
https://doi.org/10.18653/v1/2021.acl-long.109
With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide prov
Autor:
Yada Pruksachatkun, Ian Tenney, Haokun Liu, Philip Yeres, Samuel R. Bowman, Jason Phang, Alex Wang, Phu Mon Htut
Publikováno v:
ACL (demo)
We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration-driven experimentation with state-of-the-art models and implements a broad set of task
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a142207d49aa77bc9befc3b26a7ca2ef
Autor:
Richard Yuanzhe Pang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Yada Pruksachatkun, Clara Vania, Katharina Kann, Samuel R. Bowman, Jason Phang
Publikováno v:
ACL
While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-rich intermediate task, before fine-tuning it on a target task. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3949565a300700fb5096df98e752bddc
https://doi.org/10.18653/v1/2020.acl-main.467
https://doi.org/10.18653/v1/2020.acl-main.467
Publikováno v:
CHI
Clinical psychology literature indicates that reframing ir- rational thoughts can help bring positive cognitive change to those suffering from mental distress. Through data from an online mental health forum, we study how these cognitive processes pl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcf1f7aa96a252f29b01cdbb707a1d7b
https://doi.org/10.1145/3290605.3300294
https://doi.org/10.1145/3290605.3300294