3 citations · 3 across the 4 of their papers we have counts for
5 papers
Decoding the Hook: A Multimodal LLM Framework for Analyzing the Hooking Period of Video Ads
Kunpeng Zhang, Poppy Zhang, Shawndra Hill +1
Video-based ads are a vital medium for brands to engage consumers, with social media platforms leveraging user data to optimize ad delivery and boost engagement. A crucial but unde…
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Yuanchen Wu, Saurabh Verma, Justin Lee +6
Large language models (LLMs) are highly sensitive to prompts, but most automatic prompt optimization (APO) methods assume access to ground-truth references (e.g., labeled validatio…
Statistical Models of Top- Partial Orders
Amel Awadelkarim, Johan Ugander
In many contexts involving ranked preferences, agents submit partial orders over available alternatives. Statistical models often treat these as marginal in the space of total orde…
Rank-heterogeneous Preference Models for School Choice
Amel Awadelkarim, Arjun Seshadri, Itai Ashlagi +2
School choice mechanism designers use discrete choice models to understand and predict families' preferences. The most widely-used choice model, the multinomial logit (MNL), is lin…
Prioritized Restreaming Algorithms for Balanced Graph Partitioning
Amel Awadelkarim, Johan Ugander
Balanced graph partitioning is a critical step for many large-scale distributed computations with relational data. As graph datasets have grown in size and density, a range of high…