87 citations · 141 across the 5 of their papers we have counts for
7 papers
The Community Archive: An Ethically Sourced X (Twitter) Dataset
Brandon Duderstadt, Omar Shehata, Ivan Vendrov +1
We present The Community Archive, a novel dataset of over 5 million posts from the social media site X (previously known as Twitter). In contrast with other large scale social medi…
Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value
Joe Edelman, Tan Zhi-Xuan, Ryan Lowe +30
Beneficial societal outcomes cannot be guaranteed by aligning individual AI systems with the intentions of their operators or users. Even an AI system that is perfectly aligned to…
Opportunities and Risks of LLMs for Scalable Deliberation with Polis
Christopher T. Small, Ivan Vendrov, Esin Durmus +6
Polis is a platform that leverages machine intelligence to scale up deliberative processes. In this paper, we explore the opportunities and risks associated with applying Large Lan…
What are you optimizing for? Aligning Recommender Systems with Human Values
Jonathan Stray, Ivan Vendrov, Jeremy Nixon +2
We describe cases where real recommender systems were modified in the service of various human values such as diversity, fairness, well-being, time well spent, and factual accuracy…
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
Martin Mladenov, Chih-Wei Hsu, Vihan Jain +7
The development of recommender systems that optimize multi-turn interaction with users, and model the interactions of different agents (e.g., users, content providers, vendors) in…
Gradient-based Optimization for Bayesian Preference Elicitation
Ivan Vendrov, Tyler Lu, Qingqing Huang +1
Effective techniques for eliciting user preferences have taken on added importance as recommender systems (RSs) become increasingly interactive and conversational. A common and con…
Order-Embeddings of Images and Language
Ivan Vendrov, Ryan Kiros, Sanja Fidler +1
Hypernymy, textual entailment, and image captioning can be seen as special cases of a single visual-semantic hierarchy over words, sentences, and images. In this paper we advocate…