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전체 전문분석자료
arXiv:2603.03326v1 Announce Type: cross Abstract: Aligning Large Language Models (LLMs) with specific personas typically relies on expensive and monolithic Supervised Fine-Tuning (SFT) or RLHF. While …
arXiv:2603.03327v1 Announce Type: cross Abstract: User satisfaction is closely related to enterprises, as it not only directly reflects users' subjective evaluation of service quality or …
arXiv:2603.03293v1 Announce Type: new Abstract: Retrieval augmented generation (RAG) reduces hallucinations and factual errors in large language models (LLMs) by conditioning generation on retrieved external …
arXiv:2603.03299v1 Announce Type: new Abstract: Large language models (LLMs) have been noted to fabricate scholarly citations, yet the scope of this behavior across providers, domains, …
arXiv:2603.03300v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) offers significant potential for legal AI, yet systematic benchmarks are sparse. Prior work introduced LaborBench to benchmark …
arXiv:2603.03309v1 Announce Type: new Abstract: Cold start scenarios present fundamental obstacles to effective recommendation generation, particularly when dealing with users lacking interaction history or items …
arXiv:2603.03310v1 Announce Type: new Abstract: Modern large language model (LLM) inference engines optimize throughput and latency under fixed decoding rules, treating generation as a linear …
arXiv:2603.03311v1 Announce Type: new Abstract: This paper documents the architecture, development practices, and preserved artifacts of the Logovista English--Japanese machine translation system, a large, explicitly …
arXiv:2603.03317v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) allow agents to execute complex natural language tasks. Many LLM applications, such as …
arXiv:2603.03328v1 Announce Type: new Abstract: Language exhibits inherent structures, a property that explains both language acquisition and language change. Given this characteristic, we expect language …
arXiv:2603.03329v1 Announce Type: new Abstract: Despite significant strides in language models in the last few years, when used as agents, such models often try to …
arXiv:2603.03330v1 Announce Type: new Abstract: Large language models (LLMs) often present answers with high apparent confidence despite lacking an explicit mechanism for reasoning about certainty …