{"payload":{"pageCount":1,"repositories":[{"type":"Public","name":"prompts-for-structures","owner":"utahnlp","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":1,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-26T23:57:13.586Z"}},{"type":"Public","name":"cot_disguised_accuracy","owner":"utahnlp","isFork":false,"description":"Code for our 2023 MLRC paper \"Chain-of-Thought Unfaithfulness as Disguised Accuracy\"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":0,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-06-18T17:48:21.458Z"}},{"type":"Public","name":"x-fact","owner":"utahnlp","isFork":false,"description":"Official Code and Data repository of our ACL 2021 paper X-FACT: A New Benchmark Dataset for Multilingual Fact Checking.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":22,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-21T07:52:22.058Z"}},{"type":"Public","name":"marginal_srl_with_semlink","owner":"utahnlp","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":0,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-02T23:39:01.025Z"}},{"type":"Public","name":"structured_tuning_srl","owner":"utahnlp","isFork":false,"description":"Implementation of our ACL 2020 paper: Structured Tuning for Semantic Role Labeling","allTopics":["logic","pytorch","regularization","structured","loss-functions","srl","semantic-role-labeling","finetuning","roberta"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":4,"issueCount":1,"starsCount":16,"forksCount":2,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-02T23:37:19.021Z"}},{"type":"Public","name":"weak-verifiers","owner":"utahnlp","isFork":false,"description":"This repository contains the data and implementation for the ACL'23 Findings paper: \"Verifying Annotation Agreement without Multiple Experts: A Case Study with Gujarati SNACS\" ","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":0,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-08-17T19:20:22.491Z"}},{"type":"Public","name":"BERT-fine-tuning-analysis","owner":"utahnlp","isFork":false,"description":"The codebase for the paper: A Closer Look at How Fine-tuning Changes BERT","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":20,"forksCount":3,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-04-03T22:42:55.622Z"}},{"type":"Public","name":"lapa-mrp","owner":"utahnlp","isFork":false,"description":"The system submission \"LAPA\" of our team *Amazon* for MRP Shared Task","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":3,"issueCount":0,"starsCount":4,"forksCount":0,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2023-02-15T21:25:30.786Z"}},{"type":"Public","name":"DirectProbe","owner":"utahnlp","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":17,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-10-15T01:56:33.200Z"}},{"type":"Public","name":"therapist-observer","owner":"utahnlp","isFork":false,"description":"Code for the ACL 2019 paper \"Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes\"","allTopics":["dialog","attention","hierarchical-attention-networks","focal-loss","psychotherapy","elmo","transformer-encoder","acl2019","behavior-coding"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":12,"forksCount":5,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2022-06-11T21:50:58.271Z"}},{"type":"Public","name":"infotabs-code","owner":"utahnlp","isFork":false,"description":"Implementation of the semi-structured inference model in our ACL 2020 paper, INFOTABS: Inference on Tables as Semi-structured Data.","allTopics":["nlp","wikipedia","svm","transformer","nlp-machine-learning","tables","semi-structured-data","nli","nlp-datasets","acl2020","infotabs","inference","roberta"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":18,"forksCount":8,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-12-07T17:08:13.840Z"}},{"type":"Public","name":"neural-logic","owner":"utahnlp","isFork":false,"description":"Code for the paper: Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study (IJCAI 2021)","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":4,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-08-23T17:17:02.367Z"}},{"type":"Public","name":"madlibs","owner":"utahnlp","isFork":false,"description":"","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":2,"starsCount":0,"forksCount":0,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-07-20T15:02:37.617Z"}},{"type":"Public","name":"knowledge_infotabs","owner":"utahnlp","isFork":false,"description":"Repository containing code for the NAACL 2021 paper (Incorporating External Knowledge to Enhance Tabular Reasoning)","allTopics":["nlp","naacl","knowledge","wikipedia","inference","transformer","nlp-machine-learning","tables","semi-structured-data","nli","naacl2021","infotabs"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":17,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-20T18:42:54.865Z"}},{"type":"Public","name":"consistency","owner":"utahnlp","isFork":false,"description":"Implementation of models in our EMNLP 2019 paper: A Logic-Driven Framework for Consistency of Neural Models","allTopics":["logic","first-order-logic","pytorch","regularization","loss-functions","mnli","nli","emnlp2019","consistency","bert","snli","mscoco"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":30,"forksCount":3,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-13T09:25:15.984Z"}},{"type":"Public","name":"bert-therapy","owner":"utahnlp","isFork":false,"description":"Transformer-based observers in Psychotherapy","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":4,"forksCount":0,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-03-17T01:19:47.496Z"}},{"type":"Public","name":"layer_augmentation","owner":"utahnlp","isFork":false,"description":"Implementation of the NLI model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic.","allTopics":["logic","first-order-logic","pytorch","attention","attention-mechanism","snli","nli","decomposable-attention","acl2019"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":4,"starsCount":42,"forksCount":6,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-03T20:00:42.084Z"}},{"type":"Public","name":"layer_augmentation_qa","owner":"utahnlp","isFork":false,"description":"Implementation of the machine comprehension model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic.","allTopics":["qa","first-order-logic","pytorch","attention","attention-mechanism","squad","machine-comprehension","bidaf-pytorch","acl2019","bidaf","elmo"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":5,"forksCount":1,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-03T20:00:20.550Z"}},{"type":"Public","name":"learning-constraints","owner":"utahnlp","isFork":false,"description":"Experiments in our ACL 2020 paper. Learning Constraints for Structured Prediction Using Rectifier Networks","allTopics":["nlp","machine-learning","constraints","acl2020"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":6,"forksCount":1,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-05-02T08:28:17.524Z"}}],"repositoryCount":19,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"utahnlp repositories"}