Knowledge catalogue
arXiv:2607.04179v1 Announce Type: cross Abstract: End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers fr
arXiv:2607.04761v1 Announce Type: new Abstract: Real-time, text-promptable 4D reconstruction is indispensable for autonomous surgical interaction. Severe misalignment between semantic meaning and phys
arXiv:2607.04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does
arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text des
arXiv:2607.03156v1 Announce Type: new Abstract: Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning ha
arXiv:2607.04605v1 Announce Type: cross Abstract: Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens
arXiv:2607.04469v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) commit multiple tokens per denoising step by decoding each selected position independently from the shared conte
arXiv:2607.04428v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising a masked sequence, offering a parallel alternative to autoregressive mo
arXiv:2607.04927v1 Announce Type: cross Abstract: World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense super
arXiv:2607.03397v1 Announce Type: new Abstract: Text-to-Image diffusion models often propagate harmful bias inherited from the training data. Existing bias mitigation techniques typically intervene on
arXiv:2603.00205v2 Announce Type: replace-cross Abstract: Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expr
arXiv:2607.04472v1 Announce Type: new Abstract: The rapid proliferation of artificial intelligence-generated content necessitates reliable multimodal forensics. Beyond video-level binary classificatio
arXiv:2607.03822v1 Announce Type: new Abstract: Vision-based 3D occupancy prediction fundamentally relies on the 2D-to-3D view transformation. Current paradigms predominantly utilize explicit physical
arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen
arXiv:2607.02630v1 Announce Type: cross Abstract: Hardware accelerators now sit on the critical path of online serving. GPUs, FPGAs, and increasingly remote services such as hardware security modules,
arXiv:2607.02947v1 Announce Type: cross Abstract: Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet
arXiv:2607.04096v1 Announce Type: new Abstract: Current agentic workflows usually involve decomposing user requests into sequences of tool calls with correctly resolved parameters, the results of whic
arXiv:2404.06294v2 Announce Type: replace-cross Abstract: Super-Resolution (SR) is a time-hallowed image processing problem that aims to improve the quality of a Low-Resolution (LR) sample up to the s
arXiv:2607.04125v1 Announce Type: new Abstract: Small object detection in Unmanned Aerial Vehicle (UAV) imagery remains challenging under adverse conditions, including complex weather, low illuminatio
arXiv:2607.03661v1 Announce Type: new Abstract: Point cloud-based understanding has become an important enabler for facility operation and maintenance involving indoor building components. However, ex
arXiv:2607.02770v1 Announce Type: cross Abstract: We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute effi
arXiv:2504.13853v2 Announce Type: replace-cross Abstract: Rational design of lipid nanoparticles (LNPs) for tissue-specific delivery critically depends on predicting the composition of the protein cor
arXiv:2607.04977v1 Announce Type: new Abstract: Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift. This task, widely known as quantific
arXiv:2607.05005v1 Announce Type: new Abstract: Low-light degradation reduces image visibility and weakens structural cues that are important for visual representation and scene understanding. Existin
arXiv:2312.15320v3 Announce Type: replace-cross Abstract: Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic
arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input
arXiv:2512.16357v3 Announce Type: replace Abstract: Pre-trained Latent Diffusion Models (LDMs) have recently shown strong perceptual priors for low-level vision tasks, making them a promising directio
Moving Beyond the Prototype The AI landscape has shifted. While 'vibe coding' with tools like Antigravity and AI Studio lets you build and deploy complex agents in minutes, the real work begins on 'Da
arXiv:2604.16870v2 Announce Type: replace-cross Abstract: AI agents increasingly call external tools (file system, network, APIs) through the Model Context Protocol (MCP). These tool calls are the age
arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to
arXiv:2607.05243v1 Announce Type: new Abstract: Reconstructing dynamic human-scene environments from monocular videos is a challenging problem that requires jointly modeling scene geometry, camera mot
arXiv:2607.02919v1 Announce Type: cross Abstract: Magnetic particle imaging (MPI) enables real-time, radiation-free tracking of magnetic nanoparticle-coated instruments, making it highly suitable for
arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro
arXiv:2405.19521v3 Announce Type: replace Abstract: In applied statistics and machine learning, the gold standards used for training are often biased and almost always noisy. Dawid and Skene's justifi
arXiv:2607.03865v1 Announce Type: cross Abstract: Generative models such as diffusion and flow matching have advanced robotic visuomotor policies by modeling multimodal action distributions, but their
arXiv:2607.03614v1 Announce Type: new Abstract: Spatial question answering is the dominant paradigm for evaluating spatial intelligence in Vision-Language Models (VLMs), but it leaves a complementary
arXiv:2607.02542v1 Announce Type: new Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actio
arXiv:2607.04988v1 Announce Type: new Abstract: Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through
arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina
arXiv:2605.06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than expl
arXiv:2607.04982v1 Announce Type: cross Abstract: High-resolution velocity models are crucial for reservoir characterization and subsurface delineation. However, the band limited nature of our surface
arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic
arXiv:2607.02607v1 Announce Type: cross Abstract: Video reasoning requires Large Multimodal Models (LMMs) to remain grounded in dense evidence, yet existing systems largely adopt 'read-once, generate-
arXiv:2607.03204v1 Announce Type: new Abstract: In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed me
arXiv:2607.04270v1 Announce Type: cross Abstract: Large language models (LLMs) have recently emerged as powerful backbones for recommender systems by reformulating recommendation as a token-level gene
arXiv:2602.09530v2 Announce Type: replace-cross Abstract: We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and n
arXiv:2607.04553v1 Announce Type: cross Abstract: We present a bidirectional framework for estimating the energy consumption of text-to-video (T2V) and text-to-video-audio (T2VA) models from architect
arXiv:2607.04801v1 Announce Type: new Abstract: Personalizing text-to-image diffusion models to render several specific subjects in a coherent image remains challenging: the model must preserve each s
arXiv:2607.03350v1 Announce Type: cross Abstract: Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories su
arXiv:2607.04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that
arXiv:2607.03751v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models acquire broad embodied capabilities through large-scale pretraining, yet their generalization remains far more fragi
arXiv:2607.04531v1 Announce Type: cross Abstract: Low-precision neural networks are attractive for resource-constrained hardware, but fixed-point arithmetic introduces failure modes that are often hid
arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio
arXiv:2607.04534v1 Announce Type: new Abstract: We present an empirical study of structural routing failure in large language models (LLMs) over a formally verified algebraic corpus. The task requires
arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over
arXiv:2607.04747v1 Announce Type: new Abstract: Survival analysis on Whole Slide Images (WSIs) is important in computational pathology for prognosis estimation and treatment planning. However, existin
arXiv:2607.03643v1 Announce Type: cross Abstract: Purpose: Early screening for eye diseases is critical in low- and middle-income countries where access to care is limited. We investigate whether a co
arXiv:2607.02929v1 Announce Type: cross Abstract: Visual brand language is the set of visual properties that convey brand identity for a product. What is the impact of visual brand language on a perso
arXiv:2607.04972v1 Announce Type: cross Abstract: Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existin
arXiv:2607.05352v1 Announce Type: cross Abstract: We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world