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