Knowledge catalogue
arXiv:2506.04970v2 Announce Type: replace Abstract: Information on trees at the individual level is crucial for monitoring forest ecosystems and planning forest management. Current monitoring methods
arXiv:2608.28389v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) augments LLMs with external documents, but public or user-editable sources expose RAG systems to data poisoning:
arXiv:2608.27492v1 Announce Type: cross Abstract: Publicly-acceesible face-manipulation tools have made deepfake creation accessible to non-expert users. Against these, existing defenses are mostly po
arXiv:2608.27690v1 Announce Type: cross Abstract: Cardiovascular risk prediction remains limited by incomplete clinical data and imaging biomarkers that reduce computed tomography (CT) to a small numb
arXiv:2606.22454v2 Announce Type: replace Abstract: As LLM-generated text is increasingly used, especially in fictional domains, we explore how much LLM-generated stories differ from human-written sto
arXiv:2608.27793v1 Announce Type: new Abstract: Autonomous navigation in underwater cave environments is essential for search-and-rescue operations, scientific exploration, and emergency egress. Tradi
arXiv:2608.27797v1 Announce Type: cross Abstract: Natural-language tasking of embodied agents is rarely just goal specification: users also impose constraints that must persist while the world changes
arXiv:2608.28070v1 Announce Type: new Abstract: Automated detection of surface micro-defects on industrial components, such as copper tubes, is critically important for quality assurance but remains c
arXiv:2608.28570v1 Announce Type: new Abstract: Identifying the underlying dynamics and 3D geometry of deformable linear objects (DLOs), such as cables, ropes, and hoses, is essential for accurate rob
arXiv:2608.28044v1 Announce Type: cross Abstract: Large language model (LLM) inference serving is priced by tokens, but GPU energy is consumed over inference windows. This accounting mismatch makes to
arXiv:2608.28137v1 Announce Type: cross Abstract: We present CheXtriev, a graph-based, anatomy-aware framework for chest radiograph retrieval. Unlike prior methods focussed on global features, our met
arXiv:2508.21240v2 Announce Type: replace Abstract: This work introduces a novel generative continual learning framework based on self-organizing maps (SOMs), a brain-inspired natural computing model,
arXiv:2608.26907v1 Announce Type: cross Abstract: Deep generative models such as flow matching and diffusion models have shown potential for learning complex dynamical systems, but typically act as bl
arXiv:2608.28053v1 Announce Type: new Abstract: Chinese neologisms exploit diverse and unique linguistic mechanisms, such as phonetic substitution (e.g., 886 for ``bye-bye'') and visual character deco
arXiv:2608.28266v1 Announce Type: new Abstract: Agent systems powered by multimodal large language models (MLLMs) have advanced rapidly in recent years, yet existing embodied-agent benchmarks still la
arXiv:2608.27549v1 Announce Type: new Abstract: Physical understanding and reasoning depend on forming compact and generalizable representations of the world. While modern vision-language models can r
arXiv:2608.27893v1 Announce Type: new Abstract: High-quality e-commerce creatives are essential for presenting products and conveying marketing messages. Recent diffusion models enable scalable creati
arXiv:2509.22737v3 Announce Type: replace Abstract: Visual comparison reasoning is a fundamental capability of vision-language models (VLMs), covering judgments of object quantity, geometric dimension
arXiv:2608.28084v1 Announce Type: new Abstract: The classification and regression of particle collision events constitute a persistent computational challenge in experimental high energy physics, wher
arXiv:2608.27785v1 Announce Type: new Abstract: We study audio-visual conflict as a compositional generalization test for AV-LLMs: the model must combine synchronized but semantically incompatible aud
arXiv:2505.15450v3 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the
arXiv:2608.28142v1 Announce Type: new Abstract: Electrification of commercial delivery fleets is shifting fleet routing from distance- and time-based optimization toward energy-aware decision-making.
arXiv:2608.28316v1 Announce Type: new Abstract: Static importance scores compress visual evidence into a single ranking, but the value of remaining evidence can change after one cue has been observed.
arXiv:2608.28179v1 Announce Type: cross Abstract: We study risk-averse decision making, in which an agent selects actions while being uncertain about the true system state. The risk is measured via op
arXiv:2608.28140v1 Announce Type: new Abstract: Non-prehensile manipulation offers versatile skills for moving and rearranging heavy or bulky objects, particularly when combined with a mobile manipula
arXiv:2608.28476v1 Announce Type: new Abstract: Long-horizon agentic tasks require large language models (LLMs) to iteratively retrieve, integrate, and maintain dispersed information across multi-turn
arXiv:2608.28409v1 Announce Type: new Abstract: Multi-robot systems are well-positioned for exploration in hazardous environments, but effective deployment requires deciding not only where robots shou
arXiv:2608.27726v1 Announce Type: new Abstract: Multi-agent motion planning for high-degree-of-freedom robotics manipulators in shared workspaces remains a fundamental yet challenging problem. Central
arXiv:2608.28341v1 Announce Type: new Abstract: Precise dense correspondence is a fundamental prerequisite for multimodal spectral imaging systems that fuse disparate wavelength ranges for subsequent
arXiv:2608.28405v1 Announce Type: new Abstract: Current cultural evaluations for large language models (LLMs) often reduce culture to single-turn factual recall via MCQs, failing to capture a common u
arXiv:2608.27808v1 Announce Type: cross Abstract: Self-report is the cheapest oversight channel a deployer has, and on capable computer-use agents (CUAs) it fails precisely where oversight matters. On
arXiv:2608.27634v1 Announce Type: cross Abstract: Nearest neighbor classification relies fundamentally on how locality is defined, yet conventional k-NN imposes the same neighborhood cardinality throu
arXiv:2608.28442v1 Announce Type: new Abstract: Pretraining accounts for a large fraction of the total computational cost in LLM training. However, noise-dominant gradients and the highly ill-conditio
arXiv:2608.28205v1 Announce Type: new Abstract: Pruning visual foundation models has attracted considerable attention. However, existing methods focus on rigid point-to-point token alignment on a sing
arXiv:2608.28080v1 Announce Type: new Abstract: Image-conditioned 3D generation has advanced rapidly, yet existing evaluation protocols largely judge rendered-view plausibility and semantic alignment,
arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c
arXiv:2608.27513v1 Announce Type: new Abstract: Softmax attention stores key and value vectors for every preceding token, causing inference memory to grow with sequence length. Recent language models
arXiv:2608.27521v1 Announce Type: new Abstract: Many dynamical processes unfold on the sphere but the default scientific machine learning architectures are Euclidean. Applying these architectures on a
arXiv:2608.27713v1 Announce Type: new Abstract: Edge intelligence systems increasingly require model training and online inference to coexist on resource-constrained devices, while inference demand ca
arXiv:2608.28547v1 Announce Type: new Abstract: Model merging combines multiple task-specific fine-tuned LLMs into a single multi-task model without additional training. However, merged models are kno
arXiv:2603.27936v3 Announce Type: replace-cross Abstract: Nonlinear Partial Differential Equations (PDEs) are ubiquitous in mathematical physics and engineering. Although Physics-Informed Neural Netwo
arXiv:2502.15438v5 Announce Type: replace Abstract: Vision-based occupancy networks (VONs) provide an end-to-end solution for reconstructing 3D environments in autonomous driving. However, existing me
arXiv:2608.28108v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) allow users to specify manipulation tasks in natural language, but distinguishing a target or placement goal amon
arXiv:2608.28343v1 Announce Type: new Abstract: High-throughput phenotyping depends on accurate 3D reconstruction of plants across growth stages, yet the development and evaluation of temporal complet
arXiv:2608.27922v1 Announce Type: new Abstract: Autoregressive video diffusion models enable streaming generation through sliding-window attention, but each generated block is conditioned on previousl
arXiv:2608.27633v1 Announce Type: new Abstract: Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly cont
arXiv:2608.28308v1 Announce Type: new Abstract: We study the scaling behavior of learning rate and batch size in pretraining dense large language models on English-prevalent corpora. Beyond scaling ex
arXiv:2608.27516v1 Announce Type: cross Abstract: Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor
arXiv:2509.16145v3 Announce Type: replace Abstract: Body flexibility plays a critical role in fish-like swimming, as the spatial distribution of stiffness governs body deformation, hydrodynamic loadin
arXiv:2608.27728v1 Announce Type: new Abstract: Diffusion models generate skillful weather ensembles but require costly iterative sampling. We introduce a supervised energy-distance distillation metho
arXiv:2206.09012v4 Announce Type: replace-cross Abstract: We consider the problem of inferring high-dimensional data mathbf{x} in a model that consists of a prior p(mathbf{x}) and an auxiliary differe
arXiv:2608.27967v1 Announce Type: cross Abstract: The timely dissemination of cyber threat intelligence (CTI) is critical for organizations to mount swift and effective incident response. When valid C
arXiv:2608.27685v1 Announce Type: new Abstract: Simultaneously optimizing the trajectories of multiple agents is a challenging problem plagued by nonlinearity, nonconvexity, and the curse of dimension
arXiv:2603.16574v2 Announce Type: replace Abstract: Transformers underlie almost all state-of-the-art language models in computational linguistics, yet their cognitive adequacy as models of human sent
arXiv:2608.28092v1 Announce Type: cross Abstract: Interpreting a CT scan means comparing structures on either side, judging how far apart organs sit, and knowing where each one belongs. Medical vision
arXiv:2606.21359v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet their tendency to hallucinate poses significa
arXiv:2608.28145v1 Announce Type: new Abstract: Source-Fully-Free Domain Adaptation (SFF-DA) has emerged as a strategic paradigm to adapt Vision-Language Models (VLMs) without any access to source dat
arXiv:2608.28058v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) remain prone to hallucinations, producing responses that are irrelevant or inconsistent with the multimodal input.
arXiv:2608.27480v1 Announce Type: cross Abstract: Tea plantations are vulnerable to Postelectrotermes militaris, commonly known as the Upcountry Live Wood Termite (ULWT), which can cause substantial d
arXiv:2608.28237v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) models are increasingly deployed in dynamic environments where concept drift causes the underlying process distribut