Knowledge catalogue
arXiv:2604.02546v2 Announce Type: replace Abstract: Pretraining 3D encoders by aligning with Contrastive Language Image Pretraining (CLIP) has emerged as a promising direction to learn generalizable r
arXiv:2606.27829v1 Announce Type: new Abstract: Speculative decoding (SD) has emerged as a key solution to accelerate the inference of autoregressive models. However, in the field of image generation,
arXiv:2410.18647v4 Announce Type: replace Abstract: Data scaling has revolutionized fields like natural language processing and computer vision, providing models with remarkable generalization capabil
arXiv:2601.16956v1 Announce Type: cross Abstract: The rapid growth of Large Transformer-based models, specifically Large Language Models (LLMs), now scaling to trillions of parameters, has necessitate
arXiv:2601.14302v2 Announce Type: replace-cross Abstract: Image transmission and processing systems in resource-critical applications face significant challenges from adversarial perturbations that co
arXiv:2603.12001v2 Announce Type: replace-cross Abstract: Distributed AI and IoT applications increasingly execute across heterogeneous resources spanning end devices, edge/fog infrastructure, and clo
arXiv:2510.09685v2 Announce Type: replace-cross Abstract: Deep learning has become a pivotal technology in fields such as computer vision, scientific computing, and dynamical systems, significantly ad
arXiv:2606.27576v1 Announce Type: new Abstract: Conventional RGB cameras suffer from lighting artifacts such as flare, glare, flicker, and overexposure, leading to irrecoverable information loss that
arXiv:2606.28048v1 Announce Type: cross Abstract: Insurance fraud remains costly and operationally difficult, particularly in call-centre workflows where many customer interactions begin at FNOL. Whil
arXiv:2606.27914v1 Announce Type: new Abstract: Autonomously controlling and handling a vehicle at and beyond its stability limit is a mathematically and computationally demanding task. Prior demonstr
arXiv:2606.27619v1 Announce Type: new Abstract: Dyslexic learners increasingly use artificial intelligence (AI) tools to support reading, writing, organisation, and study-related tasks. However, their
arXiv:2511.03217v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel in generating fluent utterances but can lack reliable grounding in verified information. At the same time,
arXiv:2511.07836v4 Announce Type: replace-cross Abstract: The curse of dimensionality remains a persistent challenge in modern optimization problems. Expanding the search space into higher dimensions
arXiv:2501.16947v2 Announce Type: replace Abstract: The advances in Vision-Language models (VLMs) offer exciting opportunities for robotic applications involving image geo-localization - the problem o
arXiv:2512.16893v2 Announce Type: replace Abstract: Portrait animation has witnessed tremendous quality improvements thanks to recent advances in video diffusion models. However, these 2D methods ofte
arXiv:2604.00757v2 Announce Type: replace-cross Abstract: Large Vision Language Models show impressive performance across image and video understanding tasks, yet their computational cost grows rapidl
arXiv:2606.27729v1 Announce Type: new Abstract: 6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-base
arXiv:2606.28196v1 Announce Type: new Abstract: Traditionally, dexterous manipulation controllers are designed using analytic models constrained by strong assumptions about the hand and the objects be
arXiv:2601.12066v4 Announce Type: replace Abstract: Existing video object removal methods predominantly rely on diffusion models following a noise-to-data paradigm, where generation starts from uninfo
arXiv:2606.27718v1 Announce Type: new Abstract: Video frame interpolation (VFI) remains a challenging task, particularly when dealing with large, non-linear motions and complex occlusions. While flow-
arXiv:2602.17901v3 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) and diffusion models have respectively advanced representation learning and generative modeling for high-dimens
arXiv:2606.27779v1 Announce Type: new Abstract: Generating lifelike facial animation for dyadic conversations requires reconciling high-level cognitive intent with precise low-level motor reflexes, ye
arXiv:2606.28144v1 Announce Type: new Abstract: Reconstructing high-fidelity, relightable 3D avatars from a single in-the-wild image is a challenging ill-posed problem, primarily hindered by the scarc
arXiv:2402.11736v3 Announce Type: replace Abstract: Kernel herding belongs to a family of deterministic quadratures that seek to minimize the maximum mean discrepancy (MMD), that is, the worst-case in
arXiv:2606.28057v1 Announce Type: cross Abstract: Language models (LMs) represent tokens using embedding matrices that scale linearly with the vocabulary size. To constrain the parameter footprint, pr
arXiv:2606.27593v1 Announce Type: new Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries:
arXiv:2606.27797v1 Announce Type: cross Abstract: Knowledge Distillation (KD) enables training smaller student models under the guidance of larger teacher models, and the widely adopted TRL library im
Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding This is an interesting new open weights (MIT licensed) model, the first model release from DeepReinforce. [...] with variants including 9B Dense, 3
arXiv:2606.28192v1 Announce Type: new Abstract: Bimanual manipulation is essential for advanced robotic systems because it offers higher efficiency and flexibility compared to single-arm configuration
arXiv:2606.28274v1 Announce Type: cross Abstract: Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction re
arXiv:2606.27821v1 Announce Type: cross Abstract: Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting re
arXiv:2503.13051v3 Announce Type: replace-cross Abstract: Sorting and permutation learning are key concepts in optimization and machine learning, especially when organizing high-dimensional data into
arXiv:2606.27760v1 Announce Type: new Abstract: End-to-end pixel-space diffusion models bypass the lossy compression of Latent Diffusion Models (LDMs) but struggle to jointly model low-frequency seman
arXiv:2603.28272v2 Announce Type: replace Abstract: Ensuring that robot navigation is safe and socially acceptable is crucial for comfortable human-robot interaction in shared environments. However, e
arXiv:2606.27558v1 Announce Type: new Abstract: Fairness measurements in the form of disaggregated evaluations often rely on demographic signals that are legally constrained or culturally sensitive. R
arXiv:2509.03704v2 Announce Type: replace Abstract: Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating
arXiv:2510.03243v3 Announce Type: replace-cross Abstract: Efficient scheduling of large language model (LLM) inference tasks is critical for achieving low latency and high throughput, a challenge that
arXiv:2510.18874v3 Announce Type: replace-cross Abstract: Adapting language models (LMs) to new tasks via post-training carries the risk of degrading existing capabilities -- a phenomenon classically
arXiv:2505.23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disas
arXiv:2606.27786v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) enhances LLMs by incorporating external knowledge to support response generation. However, conflicts between retr
arXiv:2606.28062v1 Announce Type: cross Abstract: Data fusion, also known as truth discovery, is a data integration problem that aims to determine the correct value or set of values for each attribute
arXiv:2606.27566v1 Announce Type: new Abstract: Robotic operations in space are challenging due to the harsh environment and the high cost of failure. Fiducial markers provide visual references that a
arXiv:2602.01588v3 Announce Type: replace-cross Abstract: Multimodal time series forecasting is crucial in real-world applications, where decisions depend on both numerical data and contextual signals
arXiv:2512.21970v2 Announce Type: replace Abstract: While Vision-Language-Action (VLA) models excel in generalist manipulation, they often lack fine-grained spatial awareness and show limited viewpoin
arXiv:2505.22783v2 Announce Type: replace-cross Abstract: Reliable altitude estimation with frequency-modulated continuous wave (FMCW) radar altimeters is increasingly a challenge due to in-band inter
arXiv:2502.06577v3 Announce Type: replace-cross Abstract: Causal knowledge can be used to support decision-making problems. This has been recognized in the causal bandits literature, where a causal (m
arXiv:2606.27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Opti
arXiv:2606.27406v1 Announce Type: cross Abstract: Software engineering, whether performed by humans or by AI agents, requires reasoning about how software behaves. We call the internal model that supp
arXiv:2606.27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns rega
arXiv:2606.27981v1 Announce Type: new Abstract: We introduce a new, contextual, multilingual dataset called ToxiREX: Toxic REasoning in ConteXt. The dataset consists of threads of Reddit comments and
arXiv:2506.10355v2 Announce Type: replace Abstract: Many real-world applications collect data in a streaming environment, where learning tasks are encountered sequentially. This necessitates continual
arXiv:2606.27505v1 Announce Type: new Abstract: AI generated images are proliferating across the Internet. While some are used for entertainment, others are weaponized for fraud and social engineering
arXiv:2603.11229v2 Announce Type: replace-cross Abstract: Machine learning forecast systems are moving beyond point predictions to full predictive distributions for future outcomes y conditional on co
arXiv:2606.27678v1 Announce Type: new Abstract: Cross-domain diagnosis remains a major challenge in cervical cell pathology due to pronounced domain shifts across institutions and the subtle visual di
arXiv:2509.21785v2 Announce Type: replace-cross Abstract: Discretizing raw features into bucketized attribute representations is a popular step before sharing a dataset. It is, however, evident that t
arXiv:2605.25042v2 Announce Type: replace Abstract: Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution a
arXiv:2606.27780v1 Announce Type: new Abstract: World models are often used for planning by rolling learned dynamics forward. Many planning environments, however, are not vectors or images; they are g
arXiv:2602.10179v2 Announce Type: replace-cross Abstract: Recent advances in large image editing models have shifted the paradigm from text-driven instructions to vision-prompt editing, where user int
Automated lint: 49 errors, 14 warnings, 3 info
Why do RL runs on LLMs blow up even when the recipe looks right? GEOALIGN, from the Alibaba team behind Qwen, points at the rollouts. A handful of bad batches push the policy in incoherent directions,