Knowledge catalogue
arXiv:2604.13883v1 Announce Type: new Abstract: Modern machine learning models typically represent inputs as fixed points in a high-dimensional embedding space. While this approach has been proven pow
arXiv:2303.17674v5 Announce Type: replace-cross Abstract: We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets pl
arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench
arXiv:2604.14121v1 Announce Type: new Abstract: LLM reasoning traces suffer from complex flaws -- *Step Internal Flaws* (logical errors, hallucinations, etc.) and *Step-wise Flaws* (overthinking, unde
arXiv:2604.13256v1 Announce Type: new Abstract: Neural models for TCR-pMHC binding prediction are susceptible to shortcut learning: they exploit spurious correlations in training data -- such as pepti
arXiv:2604.13738v1 Announce Type: cross Abstract: We investigate stochastic combinatorial semi-bandits, where the entire joint distribution of outcomes impacts the complexity of the problem instance (
arXiv:2405.19088v3 Announce Type: replace Abstract: Recent advancements in large multimodal language models have demonstrated remarkable proficiency across a wide range of tasks. Yet, these models sti
arXiv:2604.13956v1 Announce Type: cross Abstract: Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate ou
arXiv:2604.13543v1 Announce Type: cross Abstract: Long Short-Term Memory (LSTM) neural networks have penetrated healthcare applications where real-time requirements and edge computing capabilities are
arXiv:2604.13070v1 Announce Type: new Abstract: Palaeohispanic languages are those spoken in the Iberian Peninsula before the arrival of the Romans in the 3rd Century B.C. Their study was really put o
arXiv:2406.12632v3 Announce Type: replace-cross Abstract: Positron emission tomography (PET) provides molecular biomarkers for Alzheimer's disease and related dementias (ADRD) and is increasingly used
arXiv:2604.13594v1 Announce Type: cross Abstract: Binary droplet collisions are ubiquitous in dense sprays. Traditional deterministic models cannot adequately represent transitional and stochastic beh
arXiv:2510.26491v2 Announce Type: replace Abstract: Data selection is a critical aspect of Reinforcement Learning with Verifiable Rewards (RLVR) for enhancing the reasoning capabilities of large langu
arXiv:2604.13413v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising paradigm for large language models (LLMs), yet the non-deterministic behavior of DLMs remai
arXiv:2604.13551v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify entities referring to the same real-world object across different knowledge graphs (KGs). Recent approaches based
arXiv:2508.09532v2 Announce Type: replace Abstract: Federated fine-tuning has emerged as a promising approach for adapting foundation models (FMs) to diverse downstream tasks in edge environments. In
arXiv:2604.14044v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general vision-language tasks, their application to remote sensing change understanding is hinde
arXiv:2402.01720v3 Announce Type: replace-cross Abstract: University students often spend a considerable amount of time seeking answers to common questions from administrators or teachers. This can be
arXiv:2604.13307v1 Announce Type: new Abstract: An unsupervised framework for hyperspectral image (HSI) clustering is proposed that incorporates masked deep representation learning with diffusion-base
arXiv:2604.13075v1 Announce Type: new Abstract: Effective de-escalation is critical for law enforcement safety and community trust, yet traditional training methods lack scalability and realism. While
arXiv:2604.13589v1 Announce Type: new Abstract: We present Dehaze-then-Splat, a two-stage pipeline for multi-view smoke removal and novel view synthesis developed for Track~2 of the NTIRE 2026 3D Rest
arXiv:2511.13417v2 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries from satellite imagery is essential for land management and crop monitoring, yet existing meth
arXiv:2512.17326v2 Announce Type: replace Abstract: Vision-language models (VLMs) have the potential to become co-pilots for pathologists. However, most VLMs either focus on small regions of interest
arXiv:2604.13060v1 Announce Type: new Abstract: Dental triage is a safety-critical clinical routing task that requires integrating multimodal clinical information (e.g., patient complaints and radiogr
arXiv:2604.13995v1 Announce Type: new Abstract: This paper introduces a novel approach for image and video orientation estimation by leveraging depth distribution in natural images. The proposed metho
arXiv:2604.13131v1 Announce Type: cross Abstract: Satellite sea surface temperature (SST) products underpin global coral bleaching monitoring, yet they measure only the ocean skin. Corals inhabit dept
arXiv:2604.13761v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) layers have been shown to substantially increase model capacity without a proportional increase in computational cost an
arXiv:2604.13088v1 Announce Type: new Abstract: In sparse termination rewards, intra-group comparisons have become the dominant paradigm for fine-tuning reasoning models via reinforcement learning. Ho
arXiv:2604.13608v1 Announce Type: new Abstract: Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term quantum machine learning. However, their practical pe
arXiv:2604.13416v1 Announce Type: new Abstract: Advances in radiance fields have enabled photorealistic novel view synthesis. In several domains, large-scale real-world datasets have been developed to
arXiv:2603.00192v2 Announce Type: replace Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk est
arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid
arXiv:2604.14001v1 Announce Type: new Abstract: Diffusion language models have recently emerged as a leading alternative to standard language models, due to their ability for bidirectional attention a
arXiv:2604.13366v1 Announce Type: new Abstract: Accurate modeling of robot dynamics is essential for model-based control, yet remains challenging under distributional shifts and real-time constraints.
arXiv:2604.13902v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant advances in the reasoning capabilities of Large Language Models (LLMs).
arXiv:2509.21912v2 Announce Type: replace Abstract: Guidance provides a simple and effective framework for posterior sampling by steering the generation process towards the desired distribution. When
arXiv:2604.13509v1 Announce Type: new Abstract: Recent advances in video generation models has significantly accelerated video generation and related downstream tasks. Among these, video stylization h
arXiv:2604.13899v1 Announce Type: new Abstract: Instruction-tuned LLMs can annotate thousands of instances from a short prompt at negligible cost. This raises two questions for active learning (AL): c
arXiv:2604.13731v1 Announce Type: new Abstract: Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existin
arXiv:2604.13076v1 Announce Type: new Abstract: We investigate the robustness of value alignment via finetuning with synthetic documents, using animal compassion as a value that is both important in i
arXiv:2604.13230v1 Announce Type: new Abstract: Exploratory Landscape Analysis (ELA) provides numerical features for characterizing black-box optimization problems. In high-dimensional settings, howev
arXiv:2604.14129v1 Announce Type: new Abstract: While Audio-Visual Language Models (AVLMs) have achieved remarkable progress over recent years, their reliability is bottlenecked by cross-modal halluci
arXiv:2604.13797v1 Announce Type: new Abstract: Few-shot Font Generation aims to generate stylistically consistent glyphs from a few reference glyphs. However, capturing complex font styles from a few
arXiv:2604.13796v1 Announce Type: cross Abstract: In daily fantasy sports (DFS), match participation is highly time-sensitive. Users must act within a narrow window before a game begins, making match
arXiv:2604.13278v1 Announce Type: new Abstract: Aerial object detection in UAV imagery presents unique challenges due to the high prevalence of tiny objects, adverse environmental conditions, and stri
arXiv:2604.13878v1 Announce Type: new Abstract: Driver drowsiness significantly impairs the ability to accurately judge safe braking distances and is estimated to contribute to 10%-20% of road acciden
arXiv:2604.14030v1 Announce Type: new Abstract: Product bundling boosts e-commerce revenue by recommending complementary item combinations. However, existing methods face two critical challenges: (1)
arXiv:2602.20981v3 Announce Type: replace Abstract: Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and
arXiv:2604.13586v1 Announce Type: new Abstract: Existing multi-view three-dimensional (3D) object detection approaches widely adopt large-scale pre-trained vision transformer (ViT)-based foundation mo
arXiv:2604.13800v1 Announce Type: new Abstract: Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model setti
arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi
arXiv:2604.13371v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly described as possessing strong reasoning capabilities, supported by high performance on mathematical, logi
arXiv:2604.13677v1 Announce Type: new Abstract: Mobile robots joining public spaces like sidewalks must care for pedestrian comfort. Many studies consider pedestrians' objective safety, for example, b
arXiv:2510.20169v3 Announce Type: replace Abstract: Traveling Salesman Problem (TSP) is a classic NP-hard problem that has garnered significant attention from both academia and industry. While neural-
arXiv:2604.13286v1 Announce Type: new Abstract: Despite the widespread multilingual deployment of large language models, post-training pipelines remain predominantly English-centric, contributing to p
arXiv:2604.13491v1 Announce Type: new Abstract: With the rapid progress of Multimodal Large Language Models (MLLMs), unified MLLMs that jointly perform image understanding and generation have advanced
arXiv:2604.13271v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to complex telecommunications tasks, including 3GPP specification analysis and O-RAN network troub
arXiv:2604.13508v1 Announce Type: new Abstract: Sparse Upcycling provides an efficient way to initialize a Mixture-of-Experts (MoE) model from pretrained dense weights instead of training from scratch
arXiv:2604.13598v1 Announce Type: new Abstract: Recent reinforcement learning (RL) approaches have advanced radiology report generation (RRG), yet two core limitations persist: (1) report-level reward
arXiv:2604.13633v1 Announce Type: new Abstract: Coordinating navigation and manipulation with robust performance is essential for embodied AI in complex indoor environments. However, as tasks extend o