Redirected, Not Removed: Task-Dependent Stereotyping Reveals the Limits of LLM Alignments
arXiv:2604.02669v1 Announce Type: new Abstract: How biased is a language model? The answer depends on how you ask. A model that refuses to choose between …
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arXiv:2604.02669v1 Announce Type: new Abstract: How biased is a language model? The answer depends on how you ask. A model that refuses to choose between …
arXiv:2604.02472v1 Announce Type: new Abstract: B2B sales organizations must identify "persuadable" accounts within zero-inflated revenue distributions to optimize expensive human resource allocation. Standard uplift frameworks …
arXiv:2604.03136v1 Announce Type: new Abstract: As AI-generated fiction becomes increasingly prevalent, questions of authorship and originality are becoming central to how written work is evaluated. …
The article examines the legal aspects of regulating artificial intelligence in the context of digital diplomacy. The author examines the process of transformation of traditional …
arXiv:2604.02478v1 Announce Type: new Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for …
arXiv:2604.02972v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have recently achieved remarkable success in complex reasoning tasks. However, closer scrutiny reveals persistent failure modes …
arXiv:2604.02500v1 Announce Type: new Abstract: As ongoing research explores the ability of AI agents to be insider threats and act against company interests, we showcase …
arXiv:2604.02926v1 Announce Type: new Abstract: The article proposes a new architecture based on Multi-head attention to solve the problem of morphological tagging for the Russian …
arXiv:2604.02474v1 Announce Type: new Abstract: Dynamical systems describe how a physical system evolves over time. Physical processes can evolve faster or slower in different environmental …
arXiv:2604.02923v1 Announce Type: new Abstract: Large Language Models (LLMs), particularly those employing Mixture-of-Experts (MoE) architectures, have achieved remarkable capabilities across diverse natural language processing tasks. …
arXiv:2604.02645v1 Announce Type: new Abstract: This work aims to shine a spotlight on the topic of metalanguage. We first define metalanguage, link it to NLP …
arXiv:2604.02528v1 Announce Type: new Abstract: The new Specifications for the National Bridge Inventory (SNBI), in effect from 2022, emphasize the use of element-level condition states …