# Fairness, Accountability, Transparency

Published articles for Fairness, Accountability, Transparency.

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## EveryEvalEver aims to standardize AI benchmark reporting and sharing

DevFeed: [EveryEvalEver aims to standardize AI benchmark reporting and sharing](<https://devfeed.tech/articles/all-of-ai-benchmarking-at-your-fingertips-17333.md>)

Original publisher: [Read original article](<https://research.ibm.com/blog/every-evaluation-ever>)

Author: Kim Martineau

Published: 2026-07-23T14:00:00Z

Content type: article

Language: en

Sources: [IBM Research](<https://devfeed.tech/sources/ibm-research.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [LLM evaluation / benchmarking](<https://devfeed.tech/topics/llm-evaluation-benchmarking.md>), [ibm](<https://devfeed.tech/topics/ibm.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-evaluation](<https://devfeed.tech/tags/ai-evaluation.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [ai-transparency](<https://devfeed.tech/tags/ai-transparency.md>), [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [fairness-accountability-transparency](<https://devfeed.tech/tags/fairness-accountability-transparency.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [ibm](<https://devfeed.tech/tags/ibm.md>), [news](<https://devfeed.tech/tags/news.md>), [performance](<https://devfeed.tech/tags/performance.md>), [reporting](<https://devfeed.tech/tags/reporting.md>)

### AI overview

IBM, Hugging Face, and academic collaborators launched EveryEvalEver to make AI benchmark results easier to compare, replicate, and reuse. The project combines standardized reporting with a crowdsourced database of model evaluation results.

### Source excerpt

IBM is part of a global team trying to make AI benchmarking results easier to compare, replicate, and reuse.

## Stanford AI Lab Papers at ICCV 2021

DevFeed: [Stanford AI Lab Papers at ICCV 2021](<https://devfeed.tech/articles/stanford-ai-lab-papers-at-iccv-2021-7583.md>)

Original publisher: [Read original article](<https://ai.stanford.edu/blog/iccv-2021/>)

Author: Compiled by Drew A. Hudson

Published: 2021-10-08T07:00:00Z

Content type: article

Language: en

Sources: [The Stanford AI Lab Blog](<https://devfeed.tech/sources/the-stanford-ai-lab-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Self-supervised learning](<https://devfeed.tech/topics/self-supervised-learning.md>), [multimodal](<https://devfeed.tech/topics/multimodal.md>), [Representation learning](<https://devfeed.tech/topics/representation-learning.md>), [object-detection](<https://devfeed.tech/topics/object-detection.md>), [Transformer](<https://devfeed.tech/topics/transformer.md>)

Tags: [3d](<https://devfeed.tech/tags/3d.md>), [ai](<https://devfeed.tech/tags/ai.md>), [computer-vision](<https://devfeed.tech/tags/computer-vision.md>), [diffusion](<https://devfeed.tech/tags/diffusion.md>), [fairness-accountability-transparency](<https://devfeed.tech/tags/fairness-accountability-transparency.md>), [learning](<https://devfeed.tech/tags/learning.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [object-detection](<https://devfeed.tech/tags/object-detection.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [video](<https://devfeed.tech/tags/video.md>), [vision](<https://devfeed.tech/tags/vision.md>)

### AI overview

Stanford AI Lab presents its accepted work for ICCV 2021, including research on multimodal medical image recognition, self-supervised learning, diffusion-based shape generation, object pose tracking, human-object relationships in videos, 3D human motion, computational photography, and related vision topics.

### Source excerpt

The International Conference on Computer Vision (ICCV 2021) will be hosted virtually next week. We're excited to share all the work from SAIL that will be presented, and you'll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that's happening at Stanford! List of Accepted Papers GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition Authors: Mars Huang Contact: mschuang@stanford.edu Keywords: medical image, self-supervised learning, multimodal fusion 3D Shape Generation and Completion Through Point-Voxel Diffusion Authors: Linqi Zhou, Yilun Du, Jiajun Wu Contact: linqizhou@stanford.edu Links: Paper | Video | Website Keywords: diffusion, shape generation CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds Authors: Yijia Weng*, He Wang*, Qiang Zhou, Yuzhe Qin, Yueqi Duan, Qingnan Fan, Baoquan Chen, Hao Su, Leonidas J. Guibas Contact: yijiaw@stanford.edu Award nominations: Oral Presentation Links: Paper | Video | Website Keywords: category-level object pose tracking, articulated objects Detecting Human-Object Relationships in Videos Authors: Jingwei Ji, Rishi Desai, Juan Carlos Niebles Contact: jingweij@cs.stanford.edu Links: Paper Keywords: human-object relationships, video, detection, transformer, spatio-temporal reasoning Geography-Aware Self-Supervised Learning Authors: Kumar Ayush, Burak Uzkent, Chenlin Meng, Kumar Tanmay, Marshall Burke, David Lobell, Stefano Ermon Contact: kayush@cs.stanford.edu, chenlin@stanford.edu Links: Paper | Website Keywords: self-supervised learning, contrastive learning, remote sensing, spatio-temporal, classification, object detection, segmentation HuMoR: 3D Human Motion Model for Robust Pose Estimation Authors: Davis Rempe, Tolga Birdal, Aaron Hertzmann, Jimei Yang, Srinath Sridhar, Leonidas Guibas Contact: drempe@stanford.edu Award nominations: Oral Presentati