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arXiv:2602.05639v1 Announce Type: new Abstract: We introduce Variational Joint Embedding (VJE), a framework that synthesizes joint embedding and variational inference to enable self-supervised learning of...
arXiv:2602.05641v1 Announce Type: new Abstract: Lightweight cryptography is becoming essential as emerging technologies in digital identity systems and Internet of Things verification continue to demand...
arXiv:2602.05644v1 Announce Type: new Abstract: This paper proposes an Improved Noisy Deep Q-Network (Noisy DQN) to enhance the exploration and stability of Unmanned Aerial Vehicle...
arXiv:2602.05646v1 Announce Type: new Abstract: While existing time series foundation models primarily rely on large-scale unimodal pretraining, they lack complementary modalities to enhance time series...
arXiv:2602.05648v1 Announce Type: new Abstract: We investigate how transformer models represent complex verb paradigms in Turkish and Modern Hebrew, concentrating on how tokenization strategies shape...
arXiv:2602.05649v1 Announce Type: new Abstract: The long-standing dominance of gradient-boosted decision trees for tabular data has recently been challenged by in-context learning tabular foundation models....
arXiv:2602.05650v1 Announce Type: new Abstract: Personality is a complex, hierarchical construct typically assessed through item-level questionnaires aggregated into broad trait scores. Personality recognition models aim...
arXiv:2602.05651v1 Announce Type: new Abstract: Datalog is an increasingly popular recursive query language that is declarative by design, meaning its programs must be translated by...
arXiv:2602.05654v1 Announce Type: new Abstract: We study invertibility of $\lambda$-terms modulo $\lambda$-theories. Here a fundamental role is played by a class of $\lambda$-terms called finite...
arXiv:2602.05656v1 Announce Type: new Abstract: Behavioral evaluation is the dominant paradigm for assessing alignment in large language models (LLMs). In practice, alignment is inferred from...
arXiv:2602.05657v1 Announce Type: new Abstract: The study of tail behaviour of SGD-induced processes has been attracting a lot of interest, due to offering strong guarantees...
arXiv:2602.05660v1 Announce Type: new Abstract: The increasing penetration of photovoltaic (PV) generation introduces significant uncertainty into power system operation, necessitating forecasting approaches that extend beyond...
arXiv:2602.05662v1 Announce Type: new Abstract: AI agents are increasingly used as low-cost proxies for early visualization evaluation. In an initial study of deliberately flawed charts,...
arXiv:2602.05663v1 Announce Type: new Abstract: Leveraging long-term user behavioral patterns is a key trajectory for enhancing the accuracy of modern recommender systems. While generative recommender...
arXiv:2602.05665v1 Announce Type: new Abstract: Memory emerges as the core module in the Large Language Model (LLM)-based agents for long-horizon complex tasks (e.g., multi-turn dialogue,...
arXiv:2602.05666v1 Announce Type: new Abstract: In this paper, we study efficient beam coverage design for multi-antenna systems in both far-field and near-field cases. To reduce...
arXiv:2602.05667v1 Announce Type: new Abstract: Benchmarking the hundreds of functional connectivity (FC) modeling methods on large-scale fMRI datasets is critical for reproducible neuroscience. However, the...
arXiv:2602.05668v1 Announce Type: new Abstract: Modern science increasingly relies on ever-growing observational datasets and automated inference pipelines, under the implicit belief that accumulating more data...
arXiv:2602.05670v1 Announce Type: new Abstract: Advances in AIGC technologies have enabled the synthesis of highly realistic audio deepfakes capable of deceiving human auditory perception. Although...
arXiv:2602.05671v1 Announce Type: new Abstract: Does human-AI assistance unfold in the same way as human-human assistance? This research explores what can be learned from the...
arXiv:2602.05674v1 Announce Type: new Abstract: Privately releasing marginals of a tabular dataset is a foundational problem in differential privacy. However, state-of-the-art mechanisms suffer from a...
arXiv:2602.05675v1 Announce Type: new Abstract: Over the past two decades, research in evolutionary multi-objective optimization has predominantly focused on continuous domains, with comparatively limited attention...
arXiv:2602.05676v1 Announce Type: new Abstract: Recent advancements in 3D foundation models have enabled the generation of high-fidelity assets, yet precise 3D manipulation remains a significant...
arXiv:2602.05679v1 Announce Type: new Abstract: Partially observable Markov decision processes (POMDPs) are a principled planning model for sequential decision-making under uncertainty. Yet, real-world problems with...