Proposes a model to optimize feedback for content creators on social media.
problem Nurturing content creation on social media platforms.
method Modeling feedback distribution to incentivize creators and optimize newsfeed experience.
result Optimized newsfeed for content creators without compromising user experience.
Modeling incentives for content creators on algorithm-curated platforms.
problem Maximizing exposure for content creators on algorithmic platforms.
method Formalized exposure game model, proving effects of algorithmic choices on equilibria, proposing tools for finding equilibria.
result Algorithmic choices significantly affect content exposure and creator behavior.
Designing AI market for content creation
problem Balancing technological progress and individual incentives for content creation
method Dynamic Stackelberg game model
result Inducing greater reliance on AI-assisted creation
NFT royalties boost creator earnings by sharing risk, reducing info asymmetry, and enabling price discrimination.
problem NFTs' royalties are criticized for being neutralized by speculators.
method Analyzes NFTs' royalties in various market conditions and their effects on creators.
result Royalties enable creators to capitalize on speculators' presence through risk sharing, info reduction, and price discrimination.
New estimator reduces bias in interference studies on content marketplaces.
problem Interference bias in experiments on content marketplaces like Douyin.
method Developed a Monte-Carlo estimator based on DQ techniques.
result Achieved bias second-order in treatment effect with low variance.
Comment classification on cookery channels using BERT and traditional models.
problem Volume of multilingual comments, variable lengths, slang, symbols, and abbreviations make comment classification challenging.
method Evaluated traditional machine learning models (Naive Bayes, KNN, SVM, Random Forest, Decision Trees) and BERT-based models (BERT, DISTILBERT, XLM) for multilingual comment classification.
result XLM was the top-performing BERT model with an accuracy of 67.31, while Random Forest with Term Frequency Vectorizer was the best traditional model with 63.59 accuracy.
Topic discovery has witnessed a significant growth as a field of data mining at large. In particular, time-evolving topic discovery, where the evolution of a topic is taken into account has been instrumental in understanding the historical context of an emerging topic in a dynamic corpus. Traditionally, time-evolving t…
In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. With deceptive words, online social network users can get infected by these online fake news easily, which has brough…
Paper proposes HGAT for detecting fake news on HIN.
problem Viral spread of fake news causing social harm.
method Hierarchical Graph Attention Network (HGAT) for node representation learning in HIN.
result HGAT outperforms text-based and network-based models.
New credit attribution methods for machine learning models using relaxed stability guarantees.
problem Ensuring proper attribution in generative models trained on existing works.
method Proposed new definitions of stability that allow for non-stable processing of a subset of datapoints with permission.
result Extended well-studied stability notions and provided a comprehensive characterization of learnability.
Study finds consumers are more price-sensitive before livestreams than after.
problem Understanding consumer demand during livestreaming lifecycle.
method Examined consumer demand for live events and recorded versions using data from a livestreaming platform.
result Demand is more price-sensitive before livestreams than after.
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet w…
ReSkill reconciles RL skill creation with policy optimization.
problem RL policies lack reusable strategies across tasks.
method Integrates skill creation into RL loop with three mechanisms.
result Consistently outperforms existing methods, especially on unseen tasks.
Ethereum smart contracts have recently drawn a considerable amount of attention from the media, the financial industry and academia. With the increase in popularity, malicious users found new opportunities to profit by deceiving newcomers. Consequently, attackers started luring other attackers into contracts that seem …
Analyzes Indian chemical industry post-Covid.
problem Global uncertainty impacts chemical industry performance.
method Fundamental analysis of key players and trends.
result Various geopolitical and macroeconomic trends shape industry performance.
Study shows online learning algorithms incentivize low-quality content, proposing new algorithms to improve quality.
problem Online learning algorithms in content recommender systems incentivize producers to create low-quality content.
method Analyzed the game between producers and content quality, designed new learning algorithms to incentivize high effort and quality.
result New algorithms incentivize producers to invest high effort and achieve high user welfare, improving content quality.
Proposes a VAE variant for ordinal content factors.
problem Isolating ordinal-valued content factors in deep latent variable models.
method Introduces a partially ordered set (poset) structure and a conditional Gaussian spacing prior model.
result Significant improvements in content-style separation over previous non-ordinal approaches.
Sensory data are often comprised of independent content and transformation factors. For example, face images may have shapes as content and poses as transformation. To infer separately these factors from given data, various ``disentangling'' models have been proposed. However, many of these are supervised or semi-super…
In the industry of video content providers such as VOD and IPTV, predicting the popularity of video contents in advance is critical not only from a marketing perspective but also from a network optimization perspective. By predicting whether the content will be successful or not in advance, the content file, which is l…
Many businesses are using recommender systems for marketing outreach. Recommendation algorithms can be either based on content or driven by collaborative filtering. We study different ways to incorporate content information directly into the matrix factorization approach of collaborative filtering. These content-booste…
Spotify improves content mix using contextual bandits.
problem Skewed historical data and varying user preferences across contexts.
method Contextual bandits to dynamically learn optimal content type distribution.
result Improved precision and user engagement with under-represented content types.
A new model considers fatigue in online content recommendation systems.
problem Fatigue in users due to overexposure and boredom from similar recommendations.
method Proposed a fatigue-aware Dependent Click Model (DCM) and two learning algorithms.
result Developed algorithms with regret bounds for learning content relevance and fatigue effects.
New PCGML approach generates novel game content across multiple platformer domains.
problem Generating novel game content in new domains.
method Using a new affordance and path vocabulary, variational autoencoders trained on data from six platformer games produce new content with varying proportions of different domains.
result Captures latent level space spanning multiple domains and generates new content with varying proportions of different domains.
We consider visual domains in which a class label specifies the content of an image, and class-irrelevant properties that differentiate instances constitute the style. We present a domain-independent method that permits the open-ended recombination of style of one image with the content of another. Open ended simply me…
One of the best ways for developers to test and improve their skills in a fun and challenging way are programming challenges, offered by a plethora of websites. For the inexperienced ones, some of the problems might appear too challenging, requiring some suggestions to implement a solution. On the other hand, tagging p…
New study shows personalized content recommendations can lead to polarization of user preferences.
problem Personalized content recommendations can alter user preferences, leading to polarization.
method Used a model of preference dynamics to explore how personalized content affects user preferences.
result Standard reward maximization algorithms achieve only constant regret in personalized recommendation environments.
Text style transfer aims to modify the style of a sentence while keeping its content unchanged. Recent style transfer systems often fail to faithfully preserve the content after changing the style. This paper proposes a structured content preserving model that leverages linguistic information in the structured fine-gra…
Study on heat content for submanifolds in sub-Riemannian geometry.
problem Understanding heat content for submanifolds in sub-Riemannian geometry.
method Existence of smooth tubular neighborhood, definition of relative heat content, approximation via smooth neighborhoods, asymptotic expansion analysis.
result Approximation of relative heat content fails to recover the exact expansion.
With rapid development of the Internet, web contents become huge. Most of the websites are publicly available, and anyone can access the contents from anywhere such as workplace, home and even schools. Nevertheless, not all the web contents are appropriate for all users, especially children. An example of these content…
Generates music with video emotion using deep neural networks.
problem Generating music with video emotion.
method Hybrid deep neural network combining ANFIS and LSTM.
result Low mean absolute errors and similar global features in spectrograms.
Enhances content moderation with culturally-aware models.
problem Global content moderation policies miss local cultural nuances.
method Fine-tuning encoder-decoder models on media-diet data.
result Improved accuracy in local violation detection and cultural alignment.
This work improves disentanglement by preventing style variables from encoding content-related features.
problem Disentanglement of content and style in data representations using Variational Autoencoders.
method Adversarial training with mutual information minimization to prevent content information leakage in style representations.
result The method efficiently separates content and style related attributes and generalizes to unseen data.
Much of the data being created on the web contains interactions between users and items. Stochastic blockmodels, and other methods for community detection and clustering of bipartite graphs, can infer latent user communities and latent item clusters from this interaction data. These methods, however, typically ignore t…
Transforms web content for better visibility in AI-driven search engines.
problem Disruption of traditional SEO by generative AI search engines.
method Fine-tunes a BART-base transformer on synthetically generated training data.
result Significant improvements in ROUGE-L and BLEU scores, and substantial visibility gains in generative search responses.
Improves content allocation in educational platforms with sparse data.
problem Imbalanced content allocation and delayed convergence in adaptive strategies.
method Introduces WAPTS, an algorithm that refines Thompson Sampling for data-sparse environments.
result Demonstrates earlier and more reliable identification of promising treatments.
Simple method disentangles content and style from pre-trained vision models.
problem Learning interpretable features in visual representations.
method Probabilistic linear entanglement model and simple disentanglement algorithm.
result Method provably disentangles content and style features.
Study on heat content for domains with fractal boundaries.
problem Analyzing short-time asymptotics of heat content for domains with fractal boundaries.
method Developing mathematical analysis on de Gennes' hypothesis and exploring fractal curvatures.
result Fractal curvatures and their scaling exponents may emerge in the short-time heat content asymptotics of domains with fractal boundaries.
IGSD separates task-specific content channels in transformer components by comparing activation replacement with zero ablation.
problem Mechanistic interpretability of transformer components
method IGSD: paired-intervention framework for comparing activation replacement with zero ablation
result IGSD identifies an early-layer content channel in transformer components that standard importance methods underestimate.
Proposes a new model to measure trade impact and information content in fluctuating markets.
problem Measuring price impact and information content of trades in a time-varying market setting.
method Non-linear observation-driven model for dynamically estimating market impact and information content.
result Market impact shows intraday patterns with large fluctuations, some of which are exogenous.
Opportunistic communications are expected to playa crucial role in enabling context-aware vehicular services. A widely investigated opportunistic communication paradigm for storing a piece of content probabilistically in a geographica larea is Floating Content (FC). A key issue in the practical deployment of FC is how …
Measures policy-violating content prevalence with ML-assisted sampling and LLM labeling.
problem Accurate measurement of content violations that are often rare and costly to label.
method Design-based measurement system using ML-assisted probability sampling and LLM labeling.
result Produces unbiased prevalence estimates with confidence intervals and dashboard drilldowns.
Recommender systems leverage product and community information to target products to consumers. Researchers have developed collaborative recommenders, content-based recommenders, and (largely ad-hoc) hybrid systems. We propose a unified probabilistic framework for merging collaborative and content-based recommendations…
Minimal surfaces can be transformed into others with unchanged bending content.
problem Understanding the deformation properties of minimal surfaces.
method Refined polar decomposition theorem to identify bending-neutral deformations.
result Every minimal surface can be transformed into another by a bending-neutral deformation.
Study heat content on RCD(K,N) spaces with specific boundary conditions.
problem Analyzing heat content in RCD(K,N) spaces with irregular boundaries.
method Proved first-order asymptotics using measured interior geodesic condition.
result Established first-order heat content asymptotics on RCD(K,N) spaces.
Classifies domains critical for heat content and exit-time moments.
problem Understanding critical domains for heat content and exit-time moments.
method First variation of heat content, constant flow property, isoparametric foliation.
result Domains critical for heat content at all times have constant flow property and isoparametric foliation.
Study heat content in sub-Riemannian manifolds, obtaining asymptotic expansion.
problem Heat content in sub-Riemannian manifolds with non-characteristic domains.
method Fourth-order asymptotic expansion, combining rough boundary temperature and stochastic completeness.
result Obtained a fourth-order asymptotic expansion for relative heat content.
Content based image retrieval, a technique which uses visual contents of image to search images from large scale image databases according to users' interests. This paper provides a comprehensive survey on recent technology used in the area of content based face image retrieval. Nowadays digital devices and photo shari…
RB-Modulation trains free diffusion models without external adapters.
problem Training-free personalization of diffusion models with style and content control.
method Stochastic optimal control with a style descriptor and cross-attention aggregation.
result Precise content and style extraction and control without external adapters.