Academic
arXiv:2602.15514v1 Announce Type: new Abstract: As large language models (LLMs) become increasingly prevalent, reliable methods for detecting AI-generated text are critical for mitigating potential risks. …
arXiv:2602.15521v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) effectively scales model capacity while preserving computational efficiency through sparse expert activation. However, training high-quality MoEs from scratch …
arXiv:2602.15537v1 Announce Type: new Abstract: Pure speech language models aim to learn language directly from raw audio without textual resources. A key challenge is that …
arXiv:2602.15540v1 Announce Type: new Abstract: This paper introduces Perspectives, an interactive extension of the Discourse Analysis Tool Suite designed to empower Digital Humanities (DH) scholars …
arXiv:2602.15547v1 Announce Type: new Abstract: Text embedding models are widely used for semantic similarity tasks, including information retrieval, clustering, and classification. General-purpose models are typically …
arXiv:2602.15564v1 Announce Type: new Abstract: Text-to-SQL has recently achieved impressive progress, yet remains difficult to apply effectively in real-world scenarios. This gap stems from the …
arXiv:2602.15578v1 Announce Type: new Abstract: Depression manifests through a diverse set of symptoms such as sleep disturbance, loss of interest, and concentration difficulties. However, most …
arXiv:2602.15620v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly improved large language model reasoning, but existing RL fine-tuning methods rely heavily on heuristic techniques …
arXiv:2602.15675v1 Announce Type: new Abstract: Despite the advances in neural text to speech (TTS), many Arabic dialectal varieties remain marginally addressed, with most resources concentrated …
arXiv:2602.15678v1 Announce Type: new Abstract: Northrop Frye's theory of four fundamental narrative genres (comedy, romance, tragedy, satire) has profoundly influenced literary criticism, yet computational approaches …
arXiv:2602.15689v1 Announce Type: new Abstract: Large language models and LLM-based agents are increasingly used for cybersecurity tasks that are inherently dual-use. Existing approaches to refusal, …
arXiv:2602.15716v1 Announce Type: new Abstract: Lexical semantic change detection (LSCD) increasingly relies on contextualised language model embeddings, yet most approaches still quantify change using a …
