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arXiv:2602.14970v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in contact-center Quality Assurance (QA) to automate agent performance evaluation and coaching feedback....
arXiv:2602.14972v1 Announce Type: new Abstract: Estimating causal quantities traditionally relies on bespoke estimators tailored to specific assumptions. Recently proposed Causal Foundation Models (CFMs) promise a...
arXiv:2602.14977v1 Announce Type: new Abstract: Macrocycles are ring-shaped molecules that offer a promising alternative to small-molecule drugs due to their enhanced selectivity and binding affinity...
arXiv:2602.14983v1 Announce Type: new Abstract: Multimodal learning seeks to integrate information from heterogeneous sources, where signals may be shared across modalities, specific to individual modalities,...
arXiv:2602.14987v1 Announce Type: new Abstract: We present a model-based approach to learning robust runtime monitors for autonomous systems. Runtime monitors play a crucial role in...
arXiv:2602.14989v1 Announce Type: new Abstract: Vision language models (VLMs) achieve strong performance on RGB imagery, but they do not generalize to thermal images. Thermal sensing...
arXiv:2602.14994v1 Announce Type: new Abstract: Reasoning about actual causes of observed effects is fundamental to the study of rationality. This important problem has been studied...
arXiv:2602.14997v1 Announce Type: new Abstract: Geometric deep learning (GDL) deals with supervised learning on data domains that go beyond Euclidean structure, such as data with...
arXiv:2602.15001v1 Announce Type: new Abstract: Frontier LLMs are safeguarded against attempts to extract harmful information via adversarial prompts known as "jailbreaks". Recently, defenders have developed...
arXiv:2602.15004v1 Announce Type: new Abstract: We show that AI foundation models that are pretrained on numerical solutions to a diverse corpus of partial differential equations...
arXiv:2602.15005v1 Announce Type: new Abstract: News recommendation plays a critical role in online news platforms by helping users discover relevant content. Cross-domain news recommendation further...
arXiv:2602.15006v1 Announce Type: new Abstract: Gaussian Processes (GPs) are a powerful tool for probabilistic modeling, but their performance is often constrained in complex, largescale real-world...
arXiv:2602.15008v1 Announce Type: new Abstract: Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this paper,...
arXiv:2602.15010v1 Announce Type: new Abstract: Many robot tasks require attending to the history of past observations. For example, finding an item in a room requires...
arXiv:2602.15011v1 Announce Type: new Abstract: TouchFusion is a wristband that enables touch interactions on nearby surfaces without any additional instrumentation or computer vision. TouchFusion combines...
arXiv:2602.15012v1 Announce Type: new Abstract: Cold-start personalization requires inferring user preferences through interaction when no user-specific historical data is available. The core challenge is a...
arXiv:2602.15013v1 Announce Type: new Abstract: This paper proposes a novel method for Text Style Transfer (TST) based on parameter-efficient fine-tuning of Large Language Models (LLMs)....
arXiv:2602.15014v1 Announce Type: new Abstract: Diffusion language models are a promising alternative to autoregressive models due to their potential for faster generation. Among discrete diffusion...
arXiv:2602.15015v1 Announce Type: new Abstract: We present the first polynomial-time algorithm for computing a near-optimal \emph{flow}-expander decomposition. Given a graph $G$ and a parameter $\phi$,...
arXiv:2602.15018v1 Announce Type: new Abstract: Neurosim is a fast, real-time, high-performance library for simulating sensors such as dynamic vision sensors, RGB cameras, depth sensors, and...
arXiv:2602.15019v1 Announce Type: new Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional,...
arXiv:2602.15022v1 Announce Type: new Abstract: Many generative tasks in chemistry and science involve distributions invariant to group symmetries (e.g., permutation and rotation). A common strategy...
arXiv:2602.15028v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in privacy-critical and personalization-oriented scenarios, yet the role of context length in shaping...
arXiv:2602.15029v1 Announce Type: new Abstract: Although learned representations underlie neural networks' success, their fundamental properties remain poorly understood. A striking example is the emergence of...