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arXiv:2601.17858v1 Announce Type: new Abstract: Optimizing data mixtures is essential for unlocking the full potential of large language models (LLMs), yet identifying the optimal composition...
arXiv:2601.17859v1 Announce Type: new Abstract: Perfect Doppler compensation and synchronization is nontrivial due to multi-path Doppler effects and Einstein's theory of relativity in the space-air-ground-integrated...
arXiv:2601.17862v1 Announce Type: new Abstract: Medical image artificial intelligence models often achieve strong performance in single-center or single-device settings, yet their effectiveness frequently deteriorates in...
arXiv:2601.17865v1 Announce Type: new Abstract: The predictive probability of the next token (P_token) in large language models (LLMs) is inextricably linked to the probability of...
arXiv:2601.17866v1 Announce Type: new Abstract: Promptable segmentation has emerged as a powerful paradigm in computer vision, enabling users to guide models in parsing complex scenes...
arXiv:2601.17868v1 Announce Type: new Abstract: Standard Autoregressive Video LLMs inevitably suffer from causal masking biases that hinder global spatiotemporal modeling, leading to suboptimal understanding efficiency....
arXiv:2601.17869v1 Announce Type: new Abstract: Learning structural information from observational data is central to producing new knowledge outside the training corpus. This holds for mechanistic...
arXiv:2601.17875v2 Announce Type: new Abstract: For the past three decades, the architecture of the internet has rested on two primary pillars - communication on the...
arXiv:2601.17877v1 Announce Type: new Abstract: The study investigates the juridico-technological architecture of international public health instruments, focusing on their implementation across India, the European Union,...
arXiv:2601.17879v1 Announce Type: new Abstract: Long-form deep research requires multi-faceted investigations over extended horizons to get a comprehensive report. When handling such complex tasks, existing...
arXiv:2601.17880v1 Announce Type: new Abstract: We present Quran MD, a comprehensive multimodal dataset of the Quran that integrates textual, linguistic, and audio dimensions at the...
arXiv:2601.17883v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have recently emerged as a promising paradigm for brain-computer interfaces (BCIs), aiming to learn transferable neural...
arXiv:2601.17885v1 Announce Type: new Abstract: Bimanual manipulation in cluttered scenes requires policies that remain stable under occlusions, viewpoint and scene variations. Existing vision-language-action models often...
arXiv:2601.17887v1 Announce Type: new Abstract: Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized agents...
arXiv:2601.17888v1 Announce Type: new Abstract: Indirect call resolution remains a key challenge in reverse engineering and control-flow graph recovery, especially for stripped or optimized binaries....
arXiv:2601.17890v1 Announce Type: new Abstract: Time pressure and question difficulty can trigger stress and cognitive overload in web-based surveys, compromising data quality and user experience....
arXiv:2601.17892v1 Announce Type: new Abstract: Artificial intelligence's rapid integration with intellectual property rights necessitates assessment of its impact on trade secrets, copyrights and patents. This...
arXiv:2601.17893v1 Announce Type: new Abstract: Data videos have become a prominent vessel for communicating data to broad audiences, and a common object of study in...
arXiv:2601.17895v1 Announce Type: new Abstract: Spatial visual perception is a fundamental requirement in physical-world applications like autonomous driving and robotic manipulation, driven by the need...
arXiv:2601.17897v1 Announce Type: new Abstract: A growing body of research suggests that the cognitive processes of large language models (LLMs) differ fundamentally from those of...
arXiv:2601.17898v1 Announce Type: new Abstract: Named entity recognition (NER) is evolving from a sequence labeling task into a generative paradigm with the rise of large...
arXiv:2601.17899v1 Announce Type: new Abstract: Neighborhood search operators are critical to the performance of Multi-Objective Evolutionary Algorithms (MOEAs) and rely heavily on expert design. Although...
arXiv:2601.17900v1 Announce Type: new Abstract: 3D reconstruction is to recover 3D signals from the sampled discrete 2D pixels, with the goal to converge continuous 3D...
arXiv:2601.17902v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems based on large language models (LLMs) achieve superior performance by leveraging pretrained LLMs as decoders,...