User-Generated Content
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Community-Aware Assessment of Social Textual Engagement and Resonance: A Human-Centric Perspective on User-Generated Content Evaluation
arXiv:2606.01897v2 Announce Type: replace Abstract: Traditional Video Quality Assessment (VQA) focuses narrowly on aesthetic fidelity, overlooking the complex social dynamics that define quality in User-Generated Content (UGC). In this work, we propose a paradigm shift from signal-centric metrics to human-centric resonance assessment. We introduce CASTER (Community-Aware Assessment of Social Textual Engagement and Resonance), a new task that evaluates whether a UGC item achieves positive...
Community-Aware Assessment of Social Textual Engagement and Resonance: A Human-Centric Perspective on User-Generated Content Evaluation
arXiv:2606.01897v3 Announce Type: replace Abstract: Traditional Video Quality Assessment (VQA) focuses narrowly on aesthetic fidelity, overlooking the complex social dynamics that define quality in User-Generated Content (UGC). In this work, we propose a paradigm shift from signal-centric metrics to human-centric resonance assessment. We introduce CASTER (Community-Aware Assessment of Social Textual Engagement and Resonance), a new task that evaluates whether a UGC item achieves positive...
When the Gold Standard Isn't Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content
arXiv:2512.17738v3 Announce Type: replace Abstract: User-generated content (UGC) is characterised by frequent use of non-standard language, from spelling errors to expressive choices such as slang, character repetitions, and emojis. This makes evaluating UGC translation challenging: what counts as a "good" translation depends on the desired standardness level of the output. To explore this, we examine the human translation guidelines of four UGC datasets, and derive a taxonomy of twelve...
Community-Aware Assessment of Social Textual Engagement and Resonance: A Human-Centric Perspective on User-Generated Content Evaluation
arXiv:2606.01897v1 Announce Type: new Abstract: Traditional Video Quality Assessment (VQA) focuses narrowly on aesthetic fidelity, overlooking the complex social dynamics that define quality in User-Generated Content (UGC). In this work, we propose a paradigm shift from signal-centric metrics to human-centric resonance assessment. We introduce CASTER (Community-Aware Assessment of Social Textual Engagement and Resonance), a new task that evaluates whether a UGC item achieves positive...
TSM-Bench: Detecting LLM-Generated Text in Real-World Wikipedia Editing Practices
arXiv:2605.31113v1 Announce Type: new Abstract: Automatically detecting machine-generated text (MGT) is critical to maintaining the knowledge integrity of user-generated content (UGC) platforms such as Wikipedia. Existing detection benchmarks primarily focus on \textit{generic} text generation tasks (e.g., ``Write an article about machine learning.''). However, editors frequently employ LLMs for specific writing tasks (e.g., summarisation).
Zero-Shot Embedding Drift Detection: A Lightweight Defense Against Prompt Injections in LLMs
arXiv:2601.12359v1 Announce Type: cross Abstract: Prompt injection attacks have become an increasing vulnerability for LLM applications, where adversarial prompts exploit indirect input channels such as emails or user-generated content to circumvent alignment safeguards and induce harmful or unintended outputs. Despite advances in alignment, even state-of-the-art LLMs remain broadly vulnerable to adversarial prompts, underscoring the urgent need for robust, productive, and generalizable...
Dynamic Content Moderation in Livestreams: Combining Supervised Classification with MLLM-Boosted Similarity Matching
arXiv:2512.03553v3 Announce Type: replace Abstract: Content moderation remains a critical yet challenging task for large-scale user-generated video platforms, especially in livestreaming environments where moderation must be timely, multimodal, and robust to evolving forms of unwanted content. We present a hybrid moderation framework deployed at production scale that combines supervised classification for known violations with reference-based similarity matching for novel or subtle cases....
The Feeling of Control Slipping Away
Back in the web-traffic-obsessed days of 2018, at a time of dawning awareness of how easily audiences online could be manipulated and spoofed by bots, the writer Max Read argued that the internet had crossed a threshold known as “the Inversion.” Not only had bots proliferated across the internet; they had come to constitute it. In outnumbering humans, bots were also loosening everyone’s grasp on the very reality of online experience.
Scheduling in Queueing Systems with Uncertain and Evolving Holding Costs
arXiv:2505.21331v2 Announce Type: replace Abstract: In content moderation for social media platforms, the cost of delaying the review of a content is proportional to its view trajectory, which fluctuates and is apriori unknown. Motivated by such uncertain and evolving holding costs, we consider a queueing model where job states evolve based on a Markov chain with state-dependent instantaneous holding costs. We demonstrate that in the presence of such uncertain and evolving holding costs, the...
Google and Meta denied new trial in youth social media addiction case
Google and Meta denied new trial in youth social media addiction case June 10 : A California state court judge has denied motions by Meta Platforms and Google's YouTube seeking a new trial after a jury found the companies liable for designing social media platforms that are harmful to young people. Los Angeles Superior Court Judge Carolyn Kuhl ruled on the motions on Tuesday, according to court documents. The companies had sought a new trial in a lawsuit filed by a woman who said she became...