Knowledge catalogue
arXiv:2511.20162v2 Announce Type: replace Abstract: Large multi-modal models (LMMs) show increasing performance in realistic visual tasks for images and, more recently, for videos. For example, given
arXiv:2604.08045v1 Announce Type: new Abstract: Adnexal mass evaluation via ultrasound is a challenging clinical task, often hindered by subjective interpretation and significant inter-observer variab
arXiv:2604.06518v1 Announce Type: cross Abstract: Large volumes of medical data remain underutilized because centralizing distributed data is often infeasible due to strict privacy regulations and ins
arXiv:2511.11159v2 Announce Type: replace Abstract: Many tasks in machine learning can be described as or reduced to learning a probability distribution given a finite set of samples. A common approac
arXiv:2604.08525v1 Announce Type: cross Abstract: Today's large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginni
The specific tweet (status ID 2042726390617764234) could not be retrieved directly, as it does not appear in available search results and X/Twitter requires authentication to access individual post...
arXiv:2503.03088v4 Announce Type: replace-cross Abstract: The Segment Anything Model (SAM) has revolutionized image and video segmentation with its powerful zero-shot capabilities. However, its massiv
arXiv:2604.06566v1 Announce Type: cross Abstract: As the complexity of modern workloads and hardware increasingly outpaces human research and engineering capacity, existing methods for database perfor
arXiv:2604.03634v2 Announce Type: replace Abstract: We establish that temporal averaging over multiple observations is the degenerate case of algebraic group action with the trivial group G={e}. A
arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s
arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder
arXiv:2604.07053v2 Announce Type: replace Abstract: Recent feed-forward Gaussian reconstruction models adopt a pixel-aligned formulation that maps each 2D pixel to a 3D Gaussian, entangling Gaussian r
arXiv:2604.07277v1 Announce Type: cross Abstract: Online reinforcement learning (RL) serves as an effective method for enhancing the capabilities of Android agents. However, guiding agents to learn th
arXiv:2601.20524v2 Announce Type: replace Abstract: Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent
arXiv:2604.07120v1 Announce Type: cross Abstract: Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Informatio
The ASUS UGen300 is a plug-and-play USB AI accelerator featuring a Hailo-10H processor that delivers up to 40 TOPS (INT4) of inference performance and 8GB of dedicated LPDDR4 memory, consuming just...
arXiv:2604.07967v1 Announce Type: new Abstract: Adversarial claim rewriting is widely used to test fact-checking systems, but standard metrics fail to capture truth-conditional consistency and often l
arXiv:2509.23435v2 Announce Type: replace-cross Abstract: The creation of high-quality multimodal datasets remains fundamental for advancing role-playing capabilities in large language models (LLMs).
arXiv:2506.06975v5 Announce Type: replace-cross Abstract: As API access becomes a primary interface to large language models (LLMs), users often interact with black-box systems that offer little trans
arXiv:2604.08540v1 Announce Type: cross Abstract: Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchma
arXiv:2601.15474v2 Announce Type: replace-cross Abstract: Graph neural network (GNN) have demonstrated exceptional performance in solving critical problems across diverse domains yet remain susceptibl
arXiv:2509.23310v3 Announce Type: replace Abstract: Deep learning-based techniques for the analysis of multimodal remote sensing data have become popular due to their ability to effectively integrate
arXiv:2604.06173v1 Announce Type: cross Abstract: Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory do
arXiv:2604.07306v1 Announce Type: cross Abstract: Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This
arXiv:2604.06738v1 Announce Type: cross Abstract: We study offline learning in KL-regularized two-player zero-sum games, where policies are optimized under a KL constraint to a fixed reference policy.
arXiv:2604.07198v1 Announce Type: new Abstract: Emotion annotation is inherently subjective and cognitively demanding, producing signals that reflect diverse perceptions across annotators rather than
arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch
arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN
arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio
arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet
arXiv:2604.07154v1 Announce Type: cross Abstract: Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modalit
arXiv:2604.08014v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding requires jointly localizing target objects across both temporal and spatial dimensions based on natural language queries
arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.
Replit and Databricks have partnered to enable enterprise teams to build and deploy secure, production-grade data and AI applications by combining Replit's AI-powered development environment with D...
arXiv:2604.07583v1 Announce Type: new Abstract: Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performanc
arXiv:2604.06685v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have demonstrated significant potential in chemical visual understanding, current models are predominantly optimiz
arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason
arXiv:2604.08523v1 Announce Type: new Abstract: AI agents may be able to automate your inbox, but can they automate other routine aspects of your life? Everyday online tasks offer a realistic yet unso
arXiv:2604.06284v1 Announce Type: cross Abstract: Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve informat
arXiv:2603.20698v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastr
arXiv:2604.08015v1 Announce Type: new Abstract: We propose a unified objective function, termed CATMIL, that augments the base segmentation loss with two auxiliary supervision terms operating at diffe
arXiv:2604.06198v1 Announce Type: cross Abstract: The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure
arXiv:2604.07019v1 Announce Type: cross Abstract: Neural networks deliver impressive predictive performance across a variety of tasks, but they are often opaque in their decision-making processes. Des
arXiv:2401.00870v5 Announce Type: replace-cross Abstract: State-of-the-art large language models (LLMs) are typically deployed as online services, requiring users to transmit detailed prompts to cloud
arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea
arXiv:2604.06926v1 Announce Type: cross Abstract: We study the continuous-time structure of the difference-of-convex algorithm (DCA) for smooth DC decompositions with a strongly convex component. In d
arXiv:2604.07069v1 Announce Type: cross Abstract: This paper presents an indirect data-driven output feedback controller synthesis for nonlinear systems, leveraging Structured State-space Models (SSMs
Prince Canuma (GitHub: Blaizzy) demonstrated image segmentation capabilities using mlx-vlm at the AI Engineer event, showcasing the library's versatility beyond standard vision-language tasks. mlx-...
arXiv:2604.08088v1 Announce Type: new Abstract: Text-to-motion generation has attracted increasing attention in the research community recently, with potential applications in animation, virtual reali
arXiv:2604.03836v2 Announce Type: replace-cross Abstract: Semantics are one of the primary sources of top-down preattentive information. Modern deep object detectors excel at extracting such valuable
arXiv:2604.08457v1 Announce Type: new Abstract: Cooperative autonomous driving requires traffic scene understanding from both vehicle and infrastructure perspectives. While vision-language models (VLM
arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe
arXiv:2604.06616v1 Announce Type: cross Abstract: Hybrid queries combining high-dimensional vector similarity search with spatio-temporal filters are increasingly critical for modern retrieval-augment
The specific Reddit thread (r/MachineLearning post ID 1shg2ob) was not returned in the search results, and I was unable to directly fetch the URL's content. I cannot accurately summarize a page I h...
arXiv:2604.07758v1 Announce Type: new Abstract: Articulated objects are essential for embodied AI and world models, yet inferring their kinematics from a single closed-state image remains challenging
arXiv:2511.19365v2 Announce Type: replace-cross Abstract: Pixel diffusion aims to generate images directly in pixel space in an end-to-end fashion. This approach avoids the limitations of VAE in the t
arXiv:2604.07518v1 Announce Type: new Abstract: Vision-Language Models often struggle with complex visual reasoning due to the visual information loss in textual CoT. Existing methods either add the c
arXiv:2604.08495v1 Announce Type: cross Abstract: This paper addresses the decentralized non-uniform area coverage problem for multi-agent systems, a critical task in missions with high spatial priori
arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac
arXiv:2604.07622v1 Announce Type: new Abstract: Speculative decoding is an effective technique for accelerating large language model inference by drafting multiple tokens in parallel. In practice, its