Knowledge catalogue
arXiv:2609.06046v1 Announce Type: cross Abstract: We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots
arXiv:2609.06106v1 Announce Type: new Abstract: Heterogeneous Federated Learning (HFL) aims to train models across devices with diverse resource budgets while preserving data privacy. Existing HFL met
arXiv:2609.06196v1 Announce Type: cross Abstract: We study the computational effort required for global optimization of a smooth, possibly nonconvex objective Gamma:R^doR. An algorithm satisfies the (
arXiv:2609.06862v1 Announce Type: new Abstract: Superposition refers to neural networks representing more features than they have dimensions. It offers a possible explanation for polysemantic neurons
arXiv:2609.07403v1 Announce Type: new Abstract: Privacy-sensitive surveillance systems could benefit from large vision-language models (VLMs), but such models typically require centralized access to r
arXiv:2609.08593v1 Announce Type: cross Abstract: Integrating generative adversarial networks (GANs) into federated semantic communication (SemCom) is a natural progression, as generative priors can r
arXiv:2609.07192v1 Announce Type: new Abstract: Asynchronous federated learning improves scalability by updating the global model from a server-side buffer of client updates as they arrive, rather tha
arXiv:2609.06073v1 Announce Type: new Abstract: Federated fine-tuning adapts large language models (LLMs) to decentralized client data, but its scalability in cross-device training is often limited by
arXiv:2602.05036v2 Announce Type: replace Abstract: Can multi-task self-supervised learning on graphs be coordinated without the usual tug-of-war between objectives? Graph self-supervised learning (SS
arXiv:2503.06867v2 Announce Type: replace-cross Abstract: Time series forecasting (TSF) is important in real-world applications. Recently, Transformer-based methods have achieved strong performance by
arXiv:2601.08026v5 Announce Type: replace Abstract: Scientific compound figures combine multiple labeled panels into a single image, and downstream pretraining and retrieval require panel-aligned visu
arXiv:2603.18493v2 Announce Type: replace Abstract: Streaming 3D reconstruction maintains a persistent latent state that is updated online from incoming frames, enabling constant-memory inference. A k
arXiv:2609.07147v1 Announce Type: new Abstract: Federated learning, as a privacy-preserving distributed machine learning paradigm, faces significant threats from backdoor attacks. Compared to centrali
arXiv:2503.11006v3 Announce Type: replace Abstract: Vision and Language Navigation (VLN) requires an embodied agent to traverse complex environments by following natural language instructions, demandi
arXiv:2609.07010v1 Announce Type: new Abstract: Multimodal sentiment analysis often remains text-dominant due to raw-video noise and insufficient temporal modeling. Using CH-SIMS v2.0S, this study pro
arXiv:2609.05959v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection aims to localize humans and objects in images and classify their interactions. Zero-shot HOI focuses on recogni
arXiv:2609.08848v1 Announce Type: new Abstract: We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for gam
arXiv:2609.08961v1 Announce Type: cross Abstract: For a finite set O of Boolean functions, we consider the class of propositional formulas built using the functions in O as connectives. We determine,
arXiv:2609.08333v1 Announce Type: cross Abstract: In molecular discovery, molecule size is coupled to composition, structure, and other target properties. Yet most 3D generators require molecule size
arXiv:2609.08032v1 Announce Type: new Abstract: We introduce FlexMoGen, a novel framework for flexible human motion synthesis conditioned on both natural language descriptions and motion style referen
arXiv:2609.08620v1 Announce Type: cross Abstract: We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learnin
arXiv:2510.01912v2 Announce Type: replace Abstract: Reconstructing a three-dimensional hyperspectral cube from a two-dimensional compressed measurement is a severely ill-posed inverse problem. Existin
arXiv:2609.07137v1 Announce Type: new Abstract: Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fidelity meshes, yet their post-training strat
arXiv:2609.06173v1 Announce Type: new Abstract: Post-deployment drift poses a critical risk to algorithmic accountability, particularly when ground truth labels are delayed and performance degradation
arXiv:2609.08743v1 Announce Type: new Abstract: Object-centric manipulation policies improve generalization by modeling object motion instead of directly predicting robot actions. However, existing me
arXiv:2609.07617v1 Announce Type: new Abstract: With the rise of live sports betting in recent years, tennis forecasting has expanded from pre-match prediction to models that update win probabilities
arXiv:2507.23768v2 Announce Type: replace-cross Abstract: Existing methods for transfer learning struggle to deal with situations where the source datasets are limited and not guaranteed to be well-al
arXiv:2609.06826v1 Announce Type: cross Abstract: This paper examines the theory of Invariant Structural Learning (ISL), which proposes a non-optimization approach to concept formation. Learning is in
arXiv:2609.07853v1 Announce Type: new Abstract: Semantic and goal-oriented communication is increasingly studied for 6G, but generalization beyond seen data remains a key weakness under tight rate bud
arXiv:2609.08305v1 Announce Type: new Abstract: Automating filament tracing in Cryo-Electron Microscopy (Cryo-EM) is essential for 3D helical reconstruction but challenged by intersecting topologies a
arXiv:2609.08886v1 Announce Type: new Abstract: Language-guided robots need persistent scene memories to follow instructions, revisit objects, and resolve references to objects encountered over time.
arXiv:2609.05912v1 Announce Type: new Abstract: Single image super-resolution aims to reconstruct high-resolution images from low-resolution inputs. This paper proposes FreeTransformSR, a novel lightw
arXiv:2609.07048v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently shown excellent progress in open-ended image-to-text generation. However, their multimodal nature makes them
arXiv:2609.08391v1 Announce Type: new Abstract: Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual question answering over satellite imagery, yet l
arXiv:2609.07346v1 Announce Type: new Abstract: Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis but can introduce complex, view-dependent a
arXiv:2609.06208v1 Announce Type: new Abstract: Understanding human attention is fundamental for scene interpretation, yet existing approaches often rely on heavily trained models that lack interpreta
arXiv:2609.08316v1 Announce Type: new Abstract: Multi-modal large language models (MLLMs) have demonstrated significant potential in image quality assessment (IQA) by bridging visual perception with d
arXiv:2601.18524v2 Announce Type: replace Abstract: Accurate prediction of nuclear magnetic resonance (NMR) chemical shifts is fundamental to spectral analysis and molecular structure elucidation, yet
arXiv:2609.07111v1 Announce Type: new Abstract: Quadruped robot locomotion policies are often trained using reinforcement learning, which in turn relies heavily on hand-crafted reward functions. Desig
arXiv:2609.05905v1 Announce Type: cross Abstract: LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events.
arXiv:2506.12045v2 Announce Type: replace Abstract: Accurate reconstruction of latent environmental fields from sparse, indirect observations is a fundamental challenge across scientific domains, from
arXiv:2609.06912v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are commonly pretrained on large collections of procedurally generated synthetic tasks, yet it remains unclear how well
arXiv:2609.08636v1 Announce Type: new Abstract: Egocentric 4D interaction forecasting aims to anticipate both where future interactions will occur in 3D and how the human body will move to realize the
arXiv:2609.06660v1 Announce Type: new Abstract: Accurate aerodynamic prediction is critical for designing fuel-efficient and safe transportation systems such as aircraft and automobiles, yet tradition
arXiv:2609.06017v1 Announce Type: new Abstract: The appearance of a smoky scene is shaped by two processes that a camera records together: the participating medium alters scene radiance in a view-depe
arXiv:2609.05662v1 Announce Type: new Abstract: Full-page end-to-end Optical Music Recognition seeks to transcribe entire music pages directly into symbolic notation, avoiding the limitations of tradi
arXiv:2609.05846v1 Announce Type: cross Abstract: In function-on-function regression, the coefficient surface eta(s,t) may exhibit complex support structure---from localized patches to global patterns
arXiv:2609.07497v1 Announce Type: new Abstract: Existing SLAM systems lack modeling of the functional relations required for fine-grained robotic interaction. Functional 3D scene graphs can represent
arXiv:2603.05567v2 Announce Type: replace Abstract: Dual-target structure-based drug design aims to generate a single ligand together with two pocket-specific binding poses, each compatible with a cor
arXiv:2509.23552v2 Announce Type: replace Abstract: Antimicrobial Resistance (AMR) is a rapidly escalating global health crisis. While genomic sequencing enables rapid prediction of resistance phenoty
arXiv:2609.08385v1 Announce Type: new Abstract: Floorplans are compact, appearance-invariant maps ideal for indoor localization, yet existing methods rely on depth networks that are brittle in clutter
arXiv:2609.06619v1 Announce Type: new Abstract: Western blot (WB) images are widely used as key evidence in biomedical research. Recent scientific misconduct cases reveal that WB imagery is increasing
arXiv:2609.05744v1 Announce Type: new Abstract: Reconstructing continuous terrain manifolds from massive, unstructured airborne LiDAR point clouds remains challenging in complex Wildland-Urban Interfa
arXiv:2609.05588v1 Announce Type: cross Abstract: World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction.
General Robotics Technology Inc. said today that its GRID robot intelligence platform now automates its own engineering work, cutting the time needed to get a new robot into production from about a mo
arXiv:2609.06823v1 Announce Type: new Abstract: The next generation of artificial intelligence systems will likely be natively temporal and multimodal in both inputs and outputs: able to converse, per
arXiv:2609.07231v1 Announce Type: new Abstract: Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the lack of appearance features. While recent
arXiv:2511.09801v3 Announce Type: replace-cross Abstract: This work extends the recently introduced Alpha-Procrustes family of Riemannian metrics for symmetric positive definite (SPD) matrices by inco
arXiv:2609.05822v1 Announce Type: new Abstract: Deploying advanced HVAC (Heating, Ventilation and Air Conditioning) controllers at scale remains difficult because performance often depends on accurate
arXiv:2603.20589v2 Announce Type: replace Abstract: Generating data from discrete distributions is important for a number of application domains including text, tabular data, and genomic data. Several