Knowledge catalogue
arXiv:2412.20704v2 Announce Type: replace Abstract: Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-genera
arXiv:2604.11662v1 Announce Type: new Abstract: Recent work has shown that the hidden states of large language models contain signals useful for uncertainty estimation and hallucination detection, mot
arXiv:2512.06849v2 Announce Type: replace Abstract: Accurate segmentation of vertebral metastasis in CT is clinically important yet difficult to scale, as voxel-level annotations are scarce and both l
arXiv:2604.10271v1 Announce Type: cross Abstract: In what way could a data breach involving government-issued IDs such as passports, driver's licenses, etc., rival a random voluntary disclosure on a n
arXiv:2604.11749v1 Announce Type: new Abstract: Language change both reflects and shapes social processes, and the semantic evolution of foundational concepts provides a measurable trace of historical
arXiv:2604.10772v1 Announce Type: new Abstract: 3D layout generation and editing play a crucial role in Embodied AI and immersive VR interaction. However, manual creation requires tedious labor, while
arXiv:2604.09674v1 Announce Type: new Abstract: Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently developed an argument from rationality for the claim that LL
arXiv:2604.09670v1 Announce Type: cross Abstract: Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity,
arXiv:2604.09960v1 Announce Type: new Abstract: The rapid adoption of large language models has introduced a new class of AI-generated fake news that coexists with traditional human-written misinforma
I just updated our license. For personal use, you’re free to run the software on your own servers for coding, building applications, agents, tools, or integrations, as well as for research, experiment
arXiv:2604.09942v1 Announce Type: cross Abstract: Object binding is a foundational process in visual cognition, during which low-level perceptual features are joined into object representations. Bindi
arXiv:2604.10837v1 Announce Type: new Abstract: Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthorized animation of static images to create realistic d
arXiv:2604.10130v1 Announce Type: new Abstract: Background: Manual delineation of target volumes in head and neck cancer (HNC) remains a significant bottleneck in radiotherapy planning, characterized
arXiv:2604.09849v1 Announce Type: cross Abstract: We study whether in-domain pretraining of Bidirectional Encoder Representations from Transformer (BERT) model improves subdomain-level detection of ex
arXiv:2604.09905v1 Announce Type: new Abstract: Emergency department triage relies heavily on both quantitative vital signs and qualitative clinical notes, yet multimodal machine learning models predi
arXiv:2604.09573v1 Announce Type: cross Abstract: Experimental user studies evaluating the effectiveness of different subtypes of post-hoc explanations for black-box models are largely nonexistent. Th
In order to make sure ARC-AGI-3 games were solvable by humans we tested over 450 people If a game was too hard we either revised it or tossed it completely For maximum transparency we just open source
arXiv:2604.10164v1 Announce Type: new Abstract: Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at ca
Inflation in the United States had been on a downward trajectory following its post-pandemic peak, but the implementation of tariffs under President Trump introduced new upward pressure on consumer pr
arXiv:2604.10448v1 Announce Type: new Abstract: Instruction tuning relies on large instruction-response corpora whose quality and composition strongly affect downstream performance. We propose Answer
arXiv:2604.11639v1 Announce Type: new Abstract: Modern automatic differentiation frameworks (JAX, PyTorch) return the Hessian of the loss function as a monolithic tensor, without exposing the internal
arXiv:2604.10040v1 Announce Type: new Abstract: The primary goal of this work is to systematically evaluate the intra-finger variability of synthetic fingerprints (particularly latent prints) generate
arXiv:2511.08659v3 Announce Type: replace-cross Abstract: This book is an introductory textbook targeted towards computer science students who are completely new to the topic of automated negotiation.
arXiv:2604.11035v1 Announce Type: new Abstract: Diffusion language models promise parallel generation, yet still lag behind autoregressive (AR) models in quality. We stem this gap to a failure of intr
arXiv:2512.23532v2 Announce Type: replace Abstract: Diffusion models have become a leading paradigm for image super-resolution (SR), but existing methods struggle to guarantee both the high-frequency
arXiv:2604.09922v1 Announce Type: cross Abstract: Subsurface stratigraphy contains important spatio-temporal information about accumulation, deformation, and layer formation in polar ice sheets. In pa
arXiv:2604.09800v1 Announce Type: new Abstract: This paper presents an analytical framework to study the geometry arising when a soft continuum arm grasps a planar object. Both the arm centerline and
arXiv:2506.23471v2 Announce Type: replace-cross Abstract: The global fashion e-commerce industry has become integral to people's daily lives, leveraging technological advancements to offer personalize
arXiv:2509.20128v2 Announce Type: replace-cross Abstract: Audio-driven facial animation has made significant progress in multimedia applications, with diffusion models showing strong potential for tal
arXiv:2506.06248v2 Announce Type: replace Abstract: Equilibrium Propagation (EP) is a learning algorithm for training Energy-based Models (EBMs) on static inputs which leverages the variational descri
arXiv:2604.11748v1 Announce Type: new Abstract: Continuous diffusion models have achieved strong performance across domains such as images. However, in language modeling, prior continuous diffusion la
arXiv:2603.10079v2 Announce Type: replace Abstract: Large loss spikes in stochastic gradient descent are studied through a rigorous large-deviations analysis for a shallow, fully connected network in
arXiv:2604.09909v1 Announce Type: new Abstract: We study last-iterate convergence of SGD with greedy step size over smooth quadratics in the interpolation regime, a setting which captures the classica
arXiv:2603.02028v2 Announce Type: replace Abstract: Vision transformers have shown outstanding performance in image generation, yet their adoption in fluid dynamics remains limited. We introduce the L
arXiv:2604.11091v1 Announce Type: new Abstract: Prompt-based class-incremental learning methods typically construct a prompt pool consisting of multiple trainable key-prompts and perform instance-leve
arXiv:2604.10573v1 Announce Type: new Abstract: Robust 3D representation learning forms the perceptual foundation of spatial intelligence, enabling downstream tasks in scene understanding and embodied
arXiv:2604.11311v1 Announce Type: new Abstract: Diffusion-based models on continuous spaces have seen substantial recent progress through the mathematical framework of gradient flows, leveraging the W
arXiv:2604.11473v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures offer a scalable path for Graph Neural Networks (GNNs) in node classification tasks but typically rely on static
arXiv:2604.09664v1 Announce Type: cross Abstract: The non-equilibrium dynamics of mesoscale phase transitions are fundamentally shaped by thermal fluctuations, which not only seed instabilities but ac
arXiv:2511.18322v3 Announce Type: replace-cross Abstract: Learning soft continuum robot (SCR) dynamics from video offers flexibility but existing methods lack interpretability or rely on prior assumpt
arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d
arXiv:2604.11071v1 Announce Type: cross Abstract: We present a lightweight two-stage framework for low-light image enhancement (LLIE) that achieves competitive perceptual quality with significantly fe
arXiv:2407.05087v2 Announce Type: replace-cross Abstract: Multiplicative noise widely exists in radar images, medical images and other important fields' images. Compared to normal noises, multiplicati
arXiv:2604.09555v1 Announce Type: new Abstract: Multi-criteria Analysis (MCA) is used to rank alternatives based on various criteria. Key MCA methods, such as Multiple Criteria Decision Making (MCDM)
arXiv:2506.14493v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown great promise but require substantial computational resources during inference. Attackers can ex
arXiv:2604.10927v1 Announce Type: new Abstract: We propose LiveGesture, the first fully streamable, speech-driven full-body gesture generation framework that operates with zero look-ahead and supports
arXiv:2601.10775v2 Announce Type: replace Abstract: We propose a novel LLM-based framework for reasoning in discrete, game-theoretic tasks, illustrated with Tic-Tac-Toe. The method integrates in-conte
arXiv:2604.10834v1 Announce Type: cross Abstract: [Background:] Thematic analysis of free-text justifications in human experiments provides significant qualitative insights. Yet, it is costly because
arXiv:2604.11789v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks req
arXiv:2510.12117v3 Announce Type: replace-cross Abstract: Chatbot service providers (e.g., OpenAI) rely on tiered subscription plans to generate revenue, offering black-box access to basic models for
arXiv:2604.10643v1 Announce Type: new Abstract: Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is
arXiv:2504.14386v2 Announce Type: replace-cross Abstract: Positional embeddings (PE) play a crucial role in Vision Transformers (ViTs) by providing spatial information otherwise lost due to the permut
arXiv:2604.10556v1 Announce Type: new Abstract: While Diffusion Large Language Models (dLLMs) have emerged as a promising non-autoregressive paradigm comparable to autoregressive (AR) models, their fa
arXiv:2604.10765v1 Announce Type: cross Abstract: Lung cancer, the second leading cause of cancer-related deaths, is primarily linked to long-term tobacco smoking (85% of cases). Surprisingly, 10-15%
arXiv:2303.10894v3 Announce Type: replace Abstract: Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wi
arXiv:2604.10021v1 Announce Type: cross Abstract: Self-supervised music foundation models underperform on key detection, which requires pitch-sensitive representations. In this work, we present the fi
arXiv:2408.11871v4 Announce Type: replace-cross Abstract: Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language mo
arXiv:2604.10424v1 Announce Type: new Abstract: Foundation-style ECG encoders pretrained with self-supervised learning are increasingly reused across tasks, institutions, and deployment contexts, ofte
arXiv:2601.04448v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have greatly advanced Natural Language Processing (NLP), particularly through instruction tuning, which enables b
arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho