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20032026
most citedFactuality Challenges in the Era of Large Language Models

163 citations · 464 across the 29 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.IR2022★ 107 cited

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Jonathan Stray, Alon Halevy, Parisa Assar +18

Recommender systems are the algorithms which select, filter, and personalize content across many of the worlds largest platforms and apps. As such, their positive and negative effe…

cs.SI2022★ 13 cited

Affective Signals in a Social Media Recommender System

Jane Dwivedi-Yu, Yi-Chia Wang, Lijing Qin +2

People come to social media to satisfy a variety of needs, such as being informed, entertained and inspired, or connected to their friends and community. Hence, to design a ranking…

cs.CL2022★ 3 cited

Detecting and Understanding Harmful Memes: A Survey

Shivam Sharma, Firoj Alam, Md. Shad Akhtar +7

The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audi…

cs.CL2022

The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems

Caleb Ziems, Jane A. Yu, Yi-Chia Wang +2

Conversational agents have come increasingly closer to human competence in open-domain dialogue settings; however, such models can reflect insensitive, hurtful, or entirely incoher…

cs.LG2022

"That's so cute!": The CARE Dataset for Affective Response Detection

Jane Dwivedi-Yu, Alon Y. Halevy

Social media plays an increasing role in our communication with friends and family, and our consumption of information and entertainment. Hence, to design effective ranking functio…