arXiv:2507.09245v2 Announce Type: replace
Abstract: The Swa-bhasha Resource Hub provides a comprehensive collection of data resources and algorithms developed for Romanized Sinhala to Sinhala transliteration between 2020 and 2025. These resources have…
arXiv:2604.24536v1 Announce Type: new
Abstract: Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we present methods for generating empathically neutral compr…
arXiv:2508.10180v3 Announce Type: replace
Abstract: Data valuation is essential for enhancing the transparency and accountability of large language models (LLMs) and vision-language models (VLMs). However, existing methods typically rely on gradient c…
arXiv:2510.10930v2 Announce Type: replace-cross
Abstract: Reasoning is not just about solving problems — it is also about evaluating which problems are worth solving at all. Evaluations of artificial intelligence (AI) systems primarily focused on pro…
arXiv:2510.17881v3 Announce Type: replace-cross
Abstract: Large language models (LLMs) are typically aligned with population-level preferences, despite substantial variation across individual users. We introduce POPI, a user-level personalization fram…
arXiv:2604.24690v1 Announce Type: new
Abstract: While Large Language Models (LLMs) have increasingly assisted in historical tasks such as text processing, their capacity for professional-level historical reasoning remains underexplored. Existing bench…
arXiv:2510.18774v4 Announce Type: replace
Abstract: AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online ed…
arXiv:2604.24700v1 Announce Type: cross
Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users phrase queries, a gap not well addressed by existing…
arXiv:2512.16378v4 Announce Type: replace-cross
Abstract: As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly process spoken language and enable speech-to-text transl…
arXiv:2604.24715v1 Announce Type: new
Abstract: Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transformers, but most are still pretrained from scratch and …