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arXiv:2602.21212v1 Announce Type: new Abstract: Natural disasters such as earthquakes, torrential rainfall, floods, and volcanic eruptions occur with extremely low frequency and affect limited geographic …
arXiv:2602.21230v1 Announce Type: new Abstract: The evaluation of Deep Research Agents is a critical challenge, as conventional outcome-based metrics fail to capture the nuances of …
arXiv:2602.21257v1 Announce Type: new Abstract: We present SPL (Structured Prompt Language), a declarative SQL-inspired language that treats large language models as generative knowledge bases and …
arXiv:2602.21262v1 Announce Type: new Abstract: With increasing integration of Large Language Models (LLMs) into areas of high-stakes human decision-making, it is important to understand the …
arXiv:2602.21265v1 Announce Type: new Abstract: We introduce \ToolMATH, a math-grounded benchmark that evaluates tool-augmented language models in realistic multi-tool environments where the output depends on …
arXiv:2602.21377v1 Announce Type: new Abstract: Tokenization and sub-tokenization based models like word2vec, BERT and the GPTs are the state-of-the-art in natural language processing. Typically, these …
arXiv:2602.21461v1 Announce Type: new Abstract: Vector glyphs are the atomic units of digital typography, yet most learning-based pipelines still depend on carefully curated exemplar sheets …
arXiv:2602.21485v1 Announce Type: new Abstract: In AI, most evaluations of natural language understanding tasks are conducted in standardized dialects such as Standard American English (SAE). …
arXiv:2602.21543v1 Announce Type: new Abstract: Multilingual pretraining typically lacks explicit alignment signals, leading to suboptimal cross-lingual alignment in the representation space. In this work, we …
arXiv:2602.21608v1 Announce Type: new Abstract: Bangla-English code-mixing is widespread across South Asian social media, yet resources for implicit meaning identification in this setting remain scarce. …
arXiv:2602.21619v1 Announce Type: new Abstract: Visual spatial reasoning (VSR) remains challenging for modern vision-language models (VLMs), despite advances in multimodal architectures. A common strategy is …
arXiv:2602.21628v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a prevailing paradigm for enhancing reasoning in Multimodal Large Language Models …