Zobrazeno 1 - 10
of 30 886
pro vyhledávání: '"Lerman A"'
Quantifying the effect of textual interventions in social systems, such as reducing anger in social media posts to see its impact on engagement, poses significant challenges. Direct interventions on real-world systems are often infeasible, necessitat
Externí odkaz:
http://arxiv.org/abs/2410.21474
In-context Learning (ICL) has become the primary method for performing natural language tasks with Large Language Models (LLMs). The knowledge acquired during pre-training is crucial for this few-shot capability, providing the model with task priors.
Externí odkaz:
http://arxiv.org/abs/2410.13776
This paper presents and analyzes the first matrix optimization model which allows general coordinate and spectral constraints. The breadth of problems our model covers is exemplified by a lengthy list of examples from the literature, including semide
Externí odkaz:
http://arxiv.org/abs/2410.09682
Online social networks use recommender systems to suggest relevant information to their users in the form of personalized timelines. Studying how these systems expose people to information at scale is difficult to do as one cannot assume each user is
Externí odkaz:
http://arxiv.org/abs/2409.16558
Autor:
Bartley, Nathan, Lerman, Kristina
Recommender systems underpin many of the personalized services in the online information & social media ecosystem. However, the assumptions in the research on content recommendations in domains like search, video, and music are often applied wholesal
Externí odkaz:
http://arxiv.org/abs/2409.13237
Fear and Loathing on the Frontline: Decoding the Language of Othering by Russia-Ukraine War Bloggers
Othering, the act of portraying outgroups as fundamentally different from the ingroup, often escalates into framing them as existential threats--fueling intergroup conflict and justifying exclusion and violence. These dynamics are alarmingly pervasiv
Externí odkaz:
http://arxiv.org/abs/2409.13064
The block tensor of trifocal tensors provides crucial geometric information on the three-view geometry of a scene. The underlying synchronization problem seeks to recover camera poses (locations and orientations up to a global transformation) from th
Externí odkaz:
http://arxiv.org/abs/2409.09313
The COVID-19 pandemic profoundly impacted people globally, yet its effect on scientists and research institutions has yet to be fully examined. To address this knowledge gap, we use a newly available bibliographic dataset covering tens of millions of
Externí odkaz:
http://arxiv.org/abs/2409.07710
Following the Russian Federation's full-scale invasion of Ukraine in February 2022, a multitude of information narratives emerged within both pro-Russian and pro-Ukrainian communities online. As the conflict progresses, so too do the information narr
Externí odkaz:
http://arxiv.org/abs/2409.07684
In-Context Learning (ICL) in Large Language Models (LLM) has emerged as the dominant technique for performing natural language tasks, as it does not require updating the model parameters with gradient-based methods. ICL promises to "adapt" the LLM to
Externí odkaz:
http://arxiv.org/abs/2409.06173