🔬 Research Summary by Griffin Adams, a final year NLP PhD student at Columbia University under Noémie Elhadad and Kathleen McKeown, who will be starting as the Head of Clinical NLP for Stability AI in … [Read more...] about From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
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Does diversity really go well with Large Language Models?
✍️ Column by Sun Gyoo Kang, Lawyer. Disclaimer: The views expressed in this article are solely my own and do not reflect my employer's opinions, beliefs, or positions. Any opinions or information in this article … [Read more...] about Does diversity really go well with Large Language Models?
Measuring Value Understanding in Language Models through Discriminator-Critique Gap
🔬 Research Summary by Zhaowei Zhang, a Ph.D. student at Peking University, researching Intent Alignment and Multi-Agent Systems for building a trustworthy and social AI system. [Original paper by Zhaowei Zhang, … [Read more...] about Measuring Value Understanding in Language Models through Discriminator-Critique Gap
Open and Linked Data Model for Carbon Footprint Scenarios
🔬 Research Summary by Boris Ruf, an AI researcher at AXA, focusing on algorithmic fairness and digital sustainability. [Original paper by Boris Ruf and Marcin Detyniecki] Overview: Measuring the carbon … [Read more...] about Open and Linked Data Model for Carbon Footprint Scenarios
A Sequentially Fair Mechanism for Multiple Sensitive Attributes
🔬 Research Summary by Francois Hu & Philipp Ratz. François Hu is a postdoctoral researcher in statistical learning at UdeM in Montreal. Philipp Ratz is a PhD student at UQAM in Montreal. [Original … [Read more...] about A Sequentially Fair Mechanism for Multiple Sensitive Attributes