Search Results for author:
Found 8 papers, 4 papers with code
Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas
Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a chal- lenging and time-consuming task.
VideolandGPT: A User Study on a Conversational Recommender System
This paper investigates how large language models (LLMs) can enhance recommender systems, with a specific focus on Conversational Recommender Systems that leverage user preferences and personalised candidate selections from existing ranking models.
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation.
RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
In traditional recommender system literature, diversity is often seen as the opposite of similarity, and typically defined as the distance between identified topics, categories or word models.
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
We propose a loss function, sigmoidF1, which is an approximation of the F1 score that (1) is smooth and tractable for stochastic gradient descent, (2) naturally approximates a multilabel metric, and (3) estimates label propensities and label counts.
Recommenders with a mission: assessing diversity in newsrecommendations
News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens towards the information that is most important to them.
Faithfully Explaining Rankings in a News Recommender System
There is an increasing demand for algorithms to explain their outcomes.
The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams
We do so by tracking entities that emerge in public discourse, that is, in online text streams such as social media and news streams, before they are incorporated into Wikipedia, which, we argue, can be viewed as an online place for collective memory.
