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arXiv:2604.04106v1 Announce Type: new Abstract: The generation of realistic and controllable GPS trajectories is a fundamental task for applications in urban planning, mobility simulation, and …
arXiv:2604.03417v1 Announce Type: new Abstract: Network visualization has traditionally relied on heuristic metrics, such as stress, under the assumption that optimizing them leads to aesthetic …
arXiv:2604.03656v1 Announce Type: new Abstract: Generative Engine Optimization (GEO) is rapidly reshaping digital marketing paradigms in the era of Large Language Models (LLMs). However, current …
arXiv:2604.03891v1 Announce Type: new Abstract: Multi-task representation learning (MTRL) is an approach that learns shared latent representations across related tasks, facilitating collaborative learning that improves …
arXiv:2604.03631v1 Announce Type: new Abstract: On-screen learning behavior provides valuable insights into how students seek, use, and create information during learning. Analyzing on-screen behavioral engagement …
arXiv:2604.04144v1 Announce Type: new Abstract: The holy grail of LLM personalization is a single LLM for each user, perfectly aligned with that user's preferences. However, …
arXiv:2604.04120v1 Announce Type: new Abstract: Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, …
arXiv:2604.03506v1 Announce Type: new Abstract: Despite the large corpus of biology training text, the impact of reasoning models on biological research generally lags behind math …
arXiv:2604.03858v1 Announce Type: new Abstract: Training Data Attribution (TDA) seeks to trace model predictions back to influential training examples, enhancing interpretability and safety. We formulate …
arXiv:2604.03562v1 Announce Type: new Abstract: Adaptive reward design for deep reinforcement learning (DRL) in multi-beam LEO satellite scheduling is motivated by the intuition that regime-aware …
arXiv:2604.03493v1 Announce Type: new Abstract: Cultural representation in Large Language Model (LLM) outputs has primarily been evaluated through the proxies of cultural diversity and factual …
arXiv:2604.04017v1 Announce Type: new Abstract: Deep research agents integrate fragmented evidence through multi-step tool use. BrowseComp offers a text-only testbed for such agents, but existing …