{"schema_version":"onlylabs.public_signal.v1","title":"Amazon (Nova) Repo: amazon-science/learning_under_noisy_labels","description":"Amazon (Nova) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/f4595697-5d99-49d3-82de-6752a6f38455","json_url":"https://onlylabs.fyi/signals/f4595697-5d99-49d3-82de-6752a6f38455/signal.json","generated_at":"2026-06-11T02:52:58.151458+00:00","org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/amazon","dossier_json_url":"https://onlylabs.fyi/labs/amazon/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/f4595697-5d99-49d3-82de-6752a6f38455","signal_json":"https://onlylabs.fyi/signals/f4595697-5d99-49d3-82de-6752a6f38455/signal.json","source":"https://github.com/amazon-science/learning_under_noisy_labels","lab_dossier":"https://onlylabs.fyi/labs/amazon","lab_dossier_json":"https://onlylabs.fyi/labs/amazon/dossier.json","analysis":"https://onlylabs.fyi/analysis/amazon","analysis_json":"https://onlylabs.fyi/analysis/amazon/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/amazon/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"data","label":"Data demand","url":"https://onlylabs.fyi/data-radar/data","json_url":"https://onlylabs.fyi/data-radar/data/signals.json"}]}},"answer_pack":{"answer":"Amazon (Nova) published amazon-science/learning_under_noisy_labels (Python). 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Dependencies Install the Python3 dependecies by executing the following command: ``` pip3 install -r requirements.txt ``` Tests In the root folder you can run some sanity check tests, by executing the following command: ``` bash run_tests.sh ``` To run Text Classification experiments: ``` cd examples/text_experiments ``` ``` bash run_text_exp.sh ``` To run TrashNet experiments: ``` cd data && git clone https://github.com/garythung/trashnet.git ``` ``` mv trashnet/data/dataset-resized.zip . && rm -rf trashnet && unzip dataset-resized.zip ``` ``` cd ../examples/trashnet_experiments && python3 generate_synthetic_annotations.py ``` ``` bash run_trashnet_exp.sh ``` To run experiments on CIFAR-10N: ``` cd examples/cifar10n_experiments ``` ``` bash run_cifar_exp.sh ``` To run synthetic experiments: ``` cd examples/syntethic_experiments ``` ``` bash run_exp.sh..."},"evidence_pages":[{"url":"https://github.com/amazon-science/learning_under_noisy_labels","final_url":"https://github.com/amazon-science/learning_under_noisy_labels","title":"amazon-science/learning_under_noisy_labels repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:52:58.151458+00:00","bytes":17735,"raw_path":"c02a13e0c5281d1edebb6f2849eecf79fed90f810174d6541357998e15e46dd4.json","content_hash":"5adbdef949b182fe21866ba7c214c1bdd42b29bed82564212a9441ed0046b22e","excerpt_chars":1200,"truncated":true,"excerpt":"amazon-science/learning_under_noisy_labels Language: Python License: Apache-2.0 Stars: 2 Forks: 0 Open issues: 0 Created: 2026-02-17T06:46:23Z Pushed: 2026-02-17T14:45:24Z Default branch: main Fork: no Archived: no README: When Annotators Disagree: A Principled Approach to Learning with Noisy Labels The code is written in Python 3. 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