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arXiv:2603.16112v1 Announce Type: new Abstract: Adapting large language models (LLMs) to specialized financial reasoning typically requires expensive fine-tuning that produces model-locked expertise. Training-free alternatives have …
arXiv:2603.16120v1 Announce Type: new Abstract: Deep Research (DR) tools (e.g. OpenAI DR) help researchers cope with ballooning publishing counts. Such tools can synthesize scientific papers …
arXiv:2603.16127v1 Announce Type: new Abstract: We investigate the role of learning rate scheduling in the large-scale pre-training of large language models, focusing on its influence …
arXiv:2603.16128v1 Announce Type: new Abstract: As autonomous LLM-based agents increasingly populate social platforms, understanding the dynamics of AI-agent communities becomes essential for both communication research …
arXiv:2603.16131v1 Announce Type: new Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple levels …
arXiv:2603.16137v1 Announce Type: new Abstract: Large language models offer transformative potential for e-commerce search by enabling intent-aware recommendations. However, their industrial deployment is hindered by …
arXiv:2603.16142v1 Announce Type: new Abstract: Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, offering a promising alternative to …
arXiv:2603.16184v1 Announce Type: new Abstract: We present Polyglot-Lion, a family of compact multilingual automatic speech recognition (ASR) models tailored for the linguistic landscape of Singapore, …
arXiv:2603.16192v1 Announce Type: new Abstract: Modern LLMs employ safety mechanisms that extend beyond surface-level input filtering to latent semantic representations and generation-time reasoning, enabling them …
arXiv:2603.16219v1 Announce Type: new Abstract: Realizing personalized intelligence faces a core dilemma: sending user history to centralized large language models raises privacy concerns, while on-device …
arXiv:2603.16244v1 Announce Type: new Abstract: Cross-Context Review (CCR) improves LLM verification by separating production and review into independent sessions. A natural extension is multi-turn review: …
arXiv:2603.16258v1 Announce Type: new Abstract: This paper analyses the implementation of Automatic Speech Recognition (ASR) into the transcription workflow of the KIParla corpus, a resource …