Knowledge catalogue
arXiv:2606.24302v1 Announce Type: new Abstract: Fine-tuning transformer-based handwritten text recognition (HTR) models on medieval manuscripts is challenging because these models are pre-trained on m
arXiv:2507.01752v4 Announce Type: replace-cross Abstract: Gradient-based optimization is the workhorse of deep learning, offering efficient and scalable training via backpropagation. However, exposing
arXiv:2606.24282v1 Announce Type: new Abstract: High frame-rate RGB-D videos are crucial for a variety of downstream tasks, including motion analysis, dynamic scene understanding, and 3D reconstructio
arXiv:2606.23754v1 Announce Type: cross Abstract: Deploying foundation models for robot control raises a central challenge: the expressive power that enables rich, multimodal perception also makes the
arXiv:2606.24124v1 Announce Type: new Abstract: Multi-step reasoning with Chain-of-Thought (CoT) prompting remains fragile: logical errors or hallucinations in early steps silently propagate, producin
arXiv:2606.24477v1 Announce Type: cross Abstract: Video large language models (LLMs) are often constrained by computation and memory budgets, leading them to use reduced frame rates and spatial resolu
arXiv:2509.04827v3 Announce Type: replace-cross Abstract: The energy cost of Large Language Model (LLM) inference is rapidly becoming a barrier to sustainable and scalable deployment. Although modern
We open-source Qwen-AgentWorld-35B-A3B (MoE, 35B/3B active, 256K context) and AgentWorldBench. Two routes, one roadmap: 🔬 Build the simulator — scalable, controllable, surpassing real environments 🧠 I
arXiv:2606.24619v1 Announce Type: new Abstract: Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natur
arXiv:2606.22447v1 Announce Type: cross Abstract: Explanation requires ground truth: to verify an account of a system we must know its inner functioning-just what is missing where explainable AI (XAI)
arXiv:2606.20742v1 Announce Type: new Abstract: UAV-based pavement inspection can reduce the cost and risk of road-surface monitoring, but real-world deployment remains difficult when traffic, pedestr
arXiv:2606.21623v1 Announce Type: new Abstract: Instruction-conditioned trajectory prediction is an emerging problem in autonomous driving, where a model predicts the future ego trajectory not only fr
arXiv:2606.20955v1 Announce Type: new Abstract: Dynamic average estimation is a critical problem in multi-agent systems, enabling agents to collaboratively estimate time-varying signals using only loc
arXiv:2603.07721v2 Announce Type: replace-cross Abstract: Brand advertising plays a critical role in building long-term consumer awareness and loyalty, making it a key objective for advertisers across
arXiv:2511.03962v2 Announce Type: replace Abstract: Accurate intrinsic calibration is a crucial yet challenging prerequisite for 3D reconstruction using light field cameras. Existing calibration model
arXiv:2606.21639v1 Announce Type: new Abstract: Minimum Spanning Trees have been used in unsupervised learning, particularly in clustering tasks, due to their ability to recognize clusters by removing
arXiv:2606.20671v1 Announce Type: new Abstract: Neural wrappers are learned pre-and postprocessing networks designed to enhance the performance of conventional video codecs. Although these approaches
arXiv:2606.23355v1 Announce Type: new Abstract: Dynamic feedback linearization (DFL) is a classical technique for trajectory tracking of unicycle-type mobile robots, but the resulting DFL-based contro
arXiv:2603.13293v2 Announce Type: replace Abstract: Accurate cardiovascular risk prediction is crucial for preventive healthcare; however, the development of robust Artificial Intelligence (AI) models
arXiv:2606.21511v1 Announce Type: cross Abstract: Respiratory rate is a vital indicator of pulmonary and cardiovascular health, yet conventional methods for estimating respiratory rate are often intru
arXiv:2606.21568v1 Announce Type: new Abstract: Student behavior detection is important for intelligent classroom analysis but remains challenging in large-class scenarios due to dense instance co-occ
arXiv:2606.22360v1 Announce Type: new Abstract: Successful conversations require speakers to align on the meaning of concepts, a challenging but crucial task for human-robot interaction. Understanding
arXiv:2606.21220v1 Announce Type: new Abstract: Inspection of offshore wind turbine rotor blades is critical for predictive maintenance to maximise efficiency and extend operational lifetime. However,
arXiv:2606.21884v1 Announce Type: new Abstract: It is tempting to assume any task solvable by a short program can be taught to a model as its chain-of-thought: write the steps out, fine-tune, and the
arXiv:2606.21244v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves exceptional real-time rendering, but its substantial computational and storage demands hinder widespread deployment. Exis
arXiv:2606.21736v1 Announce Type: new Abstract: Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain a
arXiv:2606.23678v1 Announce Type: new Abstract: Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a pi
arXiv:2602.12691v3 Announce Type: replace Abstract: We study how to improve large foundation vision-language-action (VLA) systems through human-in-the-loop reinforcement learning (RL) in real-world en
arXiv:2606.21072v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making. Despite the effectiveness of mainstream neural-
arXiv:2606.21257v1 Announce Type: new Abstract: OpenPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training qu
arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing
auto-research style proposal loops should be data driven! they largely work best only when Data/Evals/Feedback give a useful gradient to hill-climb against increasingly auto-research is a very good to
arXiv:2504.03615v2 Announce Type: replace Abstract: Rapid advances in generative AI have enabled the creation of highly realistic synthetic images, which, while beneficial in many domains, also pose s
arXiv:2606.23606v1 Announce Type: cross Abstract: Global communications rely on subsea cable infrastructure that remains vulnerable to damage from natural hazards and human activity. Autonomous underw
arXiv:2606.21279v1 Announce Type: new Abstract: Nowadays, more and more disasters of different natures are appearing. Several disaster assessment approaches have been developed in order to identify da
arXiv:2606.22999v1 Announce Type: new Abstract: The rapid deployment of Vision-Language Models (VLMs) in dynamic environments necessitates the ability to learn continuously without forgetting. However
arXiv:2606.22456v1 Announce Type: new Abstract: Maintaining accurate navigation during GNSS outages remains a significant challenge for autonomous systems relying on low-cost inertial sensors. While c
arXiv:2606.23494v1 Announce Type: new Abstract: Automated diagnosis of 3D brain CT scans is essential for critical care, yet it remains challenging due to the heavy reliance on manual annotations and
arXiv:2505.11129v2 Announce Type: replace Abstract: Representation learning is one of the key research topics in machine learning, and the framework of self-supervised learning (SSL) has revolutionize
arXiv:2606.22824v1 Announce Type: new Abstract: Speech-to-IPA transcription is useful when the desired output is pronunciation rather than orthographic text, but competitive multilingual systems are o
arXiv:2606.22389v1 Announce Type: new Abstract: Singular Learning Theory leverages the Local Learning Coefficient (LLC) to quantify the geometry of neural network loss landscapes. However, mean-energy
arXiv:2606.21809v1 Announce Type: new Abstract: The presence of confounding bias poses a key challenge in policy evaluation, as the target causal effects of actions are not identifiable (i.e., underde
arXiv:2505.01652v2 Announce Type: replace Abstract: Fair machine learning seeks to identify and mitigate biases in predictions against unfavorable populations characterized by demographic attributes,
arXiv:2606.20820v1 Announce Type: new Abstract: Can we trust evaluation scores to capture an LLM's true real-world performance? Certifiable evaluation answers this question by providing guarantee for
arXiv:2606.22939v1 Announce Type: cross Abstract: Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things (IIoT) networks. Existing detection and
arXiv:2606.19380v2 Announce Type: replace-cross Abstract: Software engineering and deployment are increasingly delegated to AI coding agents. The scale of their adoption is surfacing rare, but highly
arXiv:2606.22837v1 Announce Type: new Abstract: Sensors are critical components of modern intelligent devices. The proliferation of the Internet of Things (IoT) and wearable mobile devices has enabled
arXiv:2606.23105v1 Announce Type: new Abstract: Video world models hold promise for simulating interactive environments, yet maintaining consistent long-term memory across complex camera trajectories
arXiv:2606.23521v1 Announce Type: cross Abstract: Long-running LLM agents keep valuable state resident on GPUs: KV caches, request schedulers, communication state, and sometimes online adapters. Losin
arXiv:2602.11973v2 Announce Type: replace Abstract: In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy.
arXiv:2606.21234v1 Announce Type: new Abstract: To generate natural and accurate sentence-level sign language, synthesizing the 'gloss', the fundamental semantic unit, is essential. However, most curr
arXiv:2606.21900v1 Announce Type: cross Abstract: Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid a
arXiv:2606.22945v1 Announce Type: cross Abstract: Realistic integration of user-specified textures into scene images is a fundamental task in computer graphics and image editing. While existing materi
arXiv:2606.23364v1 Announce Type: new Abstract: Training dynamics is central to understanding neural networks, yet its theoretical analysis remains difficult even for simple architectures and becomes
arXiv:2411.07724v2 Announce Type: replace Abstract: The LION (evoLved sIgn mOmeNtum) optimizer for deep neural network training was found by Google via program search, with the simple sign update yet
arXiv:2606.22757v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) is a problem that requires computing collision-free paths for a set of agents from their start locations to designated g
arXiv:2606.21932v1 Announce Type: new Abstract: Remote sensing change detection (CD) from bi-temporal imagery is critical for applications such as urban monitoring, disaster assessment, and environmen
arXiv:2606.23015v1 Announce Type: new Abstract: Optimizing instructional policies in Intelligent Tutoring Systems (ITS) typically requires costly online experimentation or student simulators that may
arXiv:2510.15623v2 Announce Type: replace Abstract: Complex query answering (CQA) goes beyond the widely studied link prediction task by addressing more sophisticated queries that require multi-hop re
arXiv:2606.22317v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is widely viewed as a promising path toward continuously improving large language models. Recent w