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arXiv:2602.13452v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication. However, their suitability for …
arXiv:2602.13455v1 Announce Type: new Abstract: The rise of digital technology has dramatically increased the potential for cyberbullying and online abuse, necessitating enhanced measures for detection …
arXiv:2602.13466v1 Announce Type: new Abstract: The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of …
arXiv:2602.13504v1 Announce Type: new Abstract: The rapid integration of large language models into newsroom workflows has raised urgent questions about the prevalence of AI-generated content …
arXiv:2602.13517v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated impressive reasoning capabilities by scaling test-time compute via long Chain-of-Thought (CoT). However, recent findings …
arXiv:2602.13540v1 Announce Type: new Abstract: Large language models (LLMs) are widely deployed as general-purpose problem solvers, making accurate confidence estimation critical for reliable use. Prior …
arXiv:2602.13551v1 Announce Type: new Abstract: Reward models (RMs) play a central role throughout the language model (LM) pipeline, particularly in non-verifiable domains. However, the dominant …
arXiv:2602.13567v1 Announce Type: new Abstract: Standard Knowledge Distillation (KD) compresses Large Language Models (LLMs) by optimizing final outputs, yet it typically treats the teacher's intermediate …
arXiv:2602.13571v1 Announce Type: new Abstract: Large language models (LLMs) have revolutionized natural language processing, yet hallucinations in knowledge-intensive tasks remain a critical challenge. Retrieval-augmented generation …
arXiv:2602.13575v1 Announce Type: new Abstract: Current alignment methods for Large Language Models (LLMs) rely on compressing vast amounts of human preference data into static, absolute …
arXiv:2602.13701v1 Announce Type: new Abstract: Metaphors are a distinctive feature of literary language, yet they remain less studied experimentally than everyday metaphors. Moreover, previous psycholinguistic …
arXiv:2602.13713v1 Announce Type: new Abstract: Identifying the strategic uses of reformulation in discourse remains a key challenge for computational argumentation. While LLMs can detect surface-level …