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arXiv:2603.06595v1 Announce Type: new Abstract: With large language models (LLMs) now performing strongly across diverse tasks, there is growing demand for them to personalize outputs …
arXiv:2603.06592v1 Announce Type: new Abstract: Contemporary studies have uncovered many puzzling phenomena in the neural information processing of Transformer-based language models. Building a robust, unified …
arXiv:2603.06594v1 Announce Type: new Abstract: Automated \enquote{LLM-as-a-Judge} frameworks have become the de facto standard for scalable evaluation across natural language processing. For instance, in safety …
arXiv:2603.06816v1 Announce Type: new Abstract: The alignment problem refers to concerns regarding powerful intelligences, ensuring compatibility with human preferences and values as capabilities increase. Current …
arXiv:2603.06865v1 Announce Type: new Abstract: Human annotation remains the foundation of reliable and interpretable data in Natural Language Processing (NLP). As annotation and evaluation tasks …
arXiv:2603.06942v1 Announce Type: new Abstract: Recent advances have made long-form report-generating systems widely available. This has prompted evaluation frameworks that use LLM-as-judge protocols and claim …
arXiv:2603.06974v1 Announce Type: new Abstract: We present Elenchus, a dialogue system for knowledge base construction grounded in inferentialist semantics, where knowledge engineering is re-conceived as …
arXiv:2603.06976v1 Announce Type: new Abstract: We present the first large-scale, cross-domain evaluation of document chunking strategies for dense retrieval, addressing a critical but underexplored aspect …
arXiv:2603.07017v1 Announce Type: new Abstract: Safety alignment is critical for deploying large language models (LLMs) in real-world applications, yet most existing approaches rely on large …
arXiv:2603.07019v1 Announce Type: new Abstract: Checklists have emerged as a popular approach for interpretable and fine-grained evaluation, particularly with LLM-as-a-Judge. Beyond evaluation, these structured criteria …
arXiv:2603.07023v1 Announce Type: new Abstract: Despite the promise of Retrieval-Augmented Generation in grounding Multimodal Large Language Models with external knowledge, the transition to extensive contexts …
arXiv:2603.07025v1 Announce Type: new Abstract: Speech Large Language Models (LLMs) that understand and follow instructions in many languages are useful for real-world interaction, but are …