Modern search engines aggregate results from different verticals: webpages, news, images, video, shopping, knowledge cards, local maps, etc. Unlike "ten blue links", these are heterogeneous in nature and not even arranged a list on the page. This revolution directly challenges conventional "ranked list" formulation ad hoc search. Therefore, finding proper presentation for gallery of is critical modern engines.

The European Union's General Data Protection Regulation (GDPR), with its explicit consent requirement, may restrict the use of personal data and shake foundations online advertising. ad industry has predicted drastic loss revenue from GDPR compliance been seeking alternative ways targeting. Taking advantage an event created by publisher's request for users Union IP addresses, authors find that a publisher uses pay-per-click model, capacity to leverage both user behavior web page content...

The advertising industry has recently witnessed proliferation in native ads, which are inserted into a web stream (e.g., list of news articles or social media posts) and look like the surrounding nonsponsored contents. This study is among first to examine ads unveil how their effectiveness changes across serial positions by analyzing large-scale data set with 120 ads. For each ad, authors use separate “natural experiment” studies compare ad’s performance as its position varies. Subsequently,...

Advertising effectiveness measurement is a fundamental problem in online advertising. Various causal inference methods have been employed to measure the effects of ad treatments. However, existing mainly focus on linear logistic regression for univariate and binary treatments are not well suited complex multi-dimensions, where each dimension could be discrete or continuous. In this paper we propose novel two-stage framework assessing impact first stage, estimate propensity parameter via...

As firms collect greater amounts of data about their customers from an ever broader set “touchpoints,” a new methodological challenges arises. Companies often these various platforms at differing levels aggregation, and it is not clear how to merge sources draw meaningful inferences customer-level behavior patterns. In this article, the authors provide method that can use, based on readily available data, gauge monitor multiplatform media usage. The key innovation in Bayesian data-fusion...

As the online advertising industry has evolved into an age of diverse ad formats and delivery channels, users are exposed to complex treatments involving various characteristics. The diversity generality call for accurate causal measurement effectiveness, i.e., how treatment causes changes in outcomes without confounding effect by user Various inference approaches have been proposed measure treatments. However, most existing methods focus on univariate binary not well suited Moreover, be...

In online advertising market it is crucial to provide advertisers with a reliable measurement of effectiveness make better marketing campaign planning. The basic idea for ad compare the performance (e.g., success rate) among users who were and not exposed certain treatment ads. When randomized experiment available, naive comparison can be biased because unexposed populations typically have different features. One solid methodology fair apply inverse propensity weighting doubly robust...

The rise of large language models (LLMs) has revolutionized the way that we interact with artificial intelligence systems through natural language. However, LLMs often misinterpret user queries because their uncertain intention, leading to less helpful responses. In human interactions, clarification is sought targeted questioning uncover obscure information. Thus, in this paper, introduce LaMAI (Language Model Active Inquiry), designed endow same level interactive engagement. leverages...

The authors examine how positive incidental emotion influences online search and ad click-through rates. They predict find that while is irrelevant to the task, it has effect of priming emotionally congruent thoughts, which increases likelihood consumers will use words as keywords in their queries. This keywords, turn, clicking on paid ads. Results from six studies support this prediction role lower persuasion knowledge a mechanism. Specifically, queries reduces towards sponsored content...

Modern search engines aggregate results from different verticals : webpages, news, images, video, shopping, knowledge cards, local maps, and so on. Unlike “ten blue links,” these are heterogeneous in nature not even arranged a list on the page. This revolution directly challenges conventional “ranked list” formulation ad hoc search. Therefore, finding proper presentation for gallery of is critical modern engines. We propose novel framework that learns optimal page to render onto result...

Large Language Models (LLMs) have exhibited remarkable performance across various natural language processing (NLP) tasks. However, fine-tuning these models often necessitates substantial supervision, which can be expensive and time-consuming to obtain. This paper introduces a novel unsupervised method called LanguageModel Self-Improvement by Reinforcement Learning Contemplation (SIRLC) that improves LLMs without reliance on external labels. Our approach is grounded in the observation it...

Abstract The before-and-after study with multiple unaffected control groups is widely applied to treatment effects. current methods usually assume that the groups’ differences between before and after periods, i.e. group time effects, follow a normal distribution. However, there no strong priori evidence for normality assumption, are not enough check assumption. We propose use flexible skew- t distribution family model consider range of plausible distributions. Based on we robust- method...

Large language models (LLMs) have catalyzed a paradigm shift in natural processing, yet their limited controllability poses significant challenge for downstream applications. We aim to address this by drawing inspiration from the neural mechanisms of human brain, specifically Broca's and Wernicke's areas, which are crucial generation comprehension, respectively. In particular, area receives cognitive decision signals area, treating as an intricate decision-making process, differs fully...

World models play a crucial role in decision-making within embodied environments, enabling cost-free explorations that would otherwise be expensive the real world. To facilitate effective decision-making, world must equipped with strong generalizability to support faithful imagination out-of-distribution (OOD) regions and provide reliable uncertainty estimation assess credibility of simulated experiences, both which present significant challenges for prior scalable approaches. This paper...