| name (string) | url (string) | tags (sequence) |
|---|---|---|
"Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild" | "https://arxiv.org/abs/1906.02569" | [
"inclusive"
] |
"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter" | "https://arxiv.org/abs/1910.01108" | [
"sustainable"
] |
"RAFT: A Real-World Few-Shot Text Classification Benchmark" | "https://arxiv.org/abs/2109.14076" | [
"rigorous"
] |
"Interactive Model Cards: A Human-Centered Approach to Model Documentation" | "https://arxiv.org/abs/2205.02894" | [
"rigorous"
] |
"Data Governance in the Age of Large-Scale Data-Driven Language Technology" | "https://arxiv.org/abs/2206.03216" | [
"consentful"
] |
"Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets" | "https://arxiv.org/abs/2103.12028" | [
"rigorous"
] |
"A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication" | "https://arxiv.org/abs/2111.04424" | [
"rigorous"
] |
"Bugs in the Data: How ImageNet Misrepresents Biodiversity" | "https://arxiv.org/abs/2208.11695" | [
"rigorous",
"socially conscious"
] |
"Measuring Data" | "https://arxiv.org/abs/2212.05129" | [
"rigorous"
] |
"Perturbation Augmentation for Fairer NLP" | "https://arxiv.org/abs/2205.12586" | [
"rigorous"
] |
"SEAL : Interactive Tool for Systematic Error Analysis and Labeling" | "https://arxiv.org/abs/2210.05839" | [
"rigorous"
] |
"Multitask Prompted Training Enables Zero-Shot Task Generalization" | "https://arxiv.org/abs/2110.08207" | [
"rigorous"
] |
"BLOOM: A 176B-Parameter Open-Access Multilingual Language Model" | "https://arxiv.org/abs/2211.05100" | [
"inclusive"
] |
"The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset" | "https://arxiv.org/abs/2303.03915" | [
"inclusive"
] |
"Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements" | "https://arxiv.org/abs/2210.01970" | [
"rigorous"
] |
"Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face" | "https://arxiv.org/abs/2302.14534" | [
"inclusive"
] |
"The ROOTS Search Tool: Data Transparency for LLMs" | "https://arxiv.org/abs/2302.14035" | [
"rigorous"
] |
"Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness" | "https://arxiv.org/abs/2302.10893" | [
"rigorous"
] |
"Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning" | "https://arxiv.org/abs/2302.08476" | [
"sustainable"
] |
"The Gradient of Generative AI Release: Methods and Considerations" | "https://arxiv.org/abs/2302.04844" | [
"inquisitive"
] |
"BigScience: A Case Study in the Social Construction of a Multilingual Large Language Model" | "https://arxiv.org/abs/2212.04960" | [
"inquisitive"
] |
"Towards Openness Beyond Open Access: User Journeys through 3 Open AI Collaboratives" | "https://arxiv.org/abs/2301.08488" | [
"inquisitive"
] |
"Stable Bias: Analyzing Societal Representations in Diffusion Models" | "https://arxiv.org/abs/2303.11408" | [
"rigorous"
] |
"Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML" | "https://arxiv.org/abs/2305.18615" | [
"rigorous",
"inquisitive"
] |
Hugging Face Ethics & Society Papers
This is an incomplete list of ethics-related papers published by researchers at Hugging Face.
- Gradio: https://arxiv.org/abs/1906.02569
- DistilBERT: https://arxiv.org/abs/1910.01108
- RAFT: https://arxiv.org/abs/2109.14076
- Interactive Model Cards: https://arxiv.org/abs/2205.02894
- Data Governance in the Age of Large-Scale Data-Driven Language Technology: https://arxiv.org/abs/2206.03216
- Quality at a Glance: https://arxiv.org/abs/2103.12028
- A Framework for Deprecating Datasets: https://arxiv.org/abs/2111.04424
- Bugs in the Data: https://arxiv.org/abs/2208.11695
- Measuring Data: https://arxiv.org/abs/2212.05129
- Perturbation Augmentation for Fairer NLP: https://arxiv.org/abs/2205.12586
- SEAL: https://arxiv.org/abs/2210.05839
- Multitask Prompted Training Enables Zero-Shot Task Generalization: https://arxiv.org/abs/2110.08207
- BLOOM: https://arxiv.org/abs/2211.05100
- ROOTS: https://arxiv.org/abs/2303.03915
- Evaluate & Evaluation on the Hub: https://arxiv.org/abs/2210.01970
- Spacerini: https://arxiv.org/abs/2302.14534
- ROOTS Search Tool: https://arxiv.org/abs/2302.14035
- Fair Diffusion: https://arxiv.org/abs/2302.10893
- Counting Carbon: https://arxiv.org/abs/2302.08476
- The Gradient of Generative AI Release: https://arxiv.org/abs/2302.04844
- BigScience: A Case Study in the Social Construction of a Multilingual Large Language Model: https://arxiv.org/abs/2212.04960
- Towards Openness Beyond Open Access: User Journeys through 3 Open AI Collaboratives: https://arxiv.org/abs/2301.08488
- Stable Bias: Analyzing Societal Representations in Diffusion Models: https://arxiv.org/abs/2303.11408
- Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML: https://arxiv.org/abs/2305.18615
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