Knowledge catalogue
arXiv:2609.08512v1 Announce Type: new Abstract: Autonomous exploration on uneven terrain requires ground robots to balance exploration efficiency, coverage completeness, and terrain safety. Detailed t
arXiv:2609.06242v1 Announce Type: cross Abstract: Connected and automated vehicle platoons require reliable dissemination of task-relevant hazard information to enable appropriate downstream responses
arXiv:2609.06636v1 Announce Type: cross Abstract: Fine-grained mobile traffic demand forecasting is essential for long-term planning of 5G and future 6G networks, including radio upgrades, site densif
arXiv:2609.06475v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have recently achieved remarkable progress in general-purpose video understanding. However, their application to su
arXiv:2609.07520v1 Announce Type: new Abstract: Agricultural parcel polygons play a fundamental role in geospatial applications such as precision agriculture, land administration, and crop monitoring.
arXiv:2609.07373v1 Announce Type: new Abstract: Modern Visual Place Recognition (VPR) methods excel on standard benchmarks yet remain brittle in feature-poor environments. By treating each query image
arXiv:2609.05636v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are able to achieve impressive zero-shot classification performance by aligning visual and textual representations, but ea
arXiv:2609.08216v1 Announce Type: cross Abstract: Agentic AI systems built on large language models fail in two persistent ways that scaling does not fix: they break under distribution shift, and they
Wild paper from Microsoft and colleagues. They show a new attack that reconstructs the text a local LLM generates by watching CPU cache activity while it detokenizes. Earlier cache attacks needed some
When building consumer-facing generative AI applications, balancing high generation quality with fast response times across diverse media types, can be challenging. KDDI, a major telecommunications ca
arXiv:2609.04539v1 Announce Type: new Abstract: A critical challenge in deploying Large Language Models (LLMs) is developing reliable mechanisms to estimate their confidence, enabling systems to deter
arXiv:2609.04369v1 Announce Type: new Abstract: Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby place, yet its robustness is often degraded b
arXiv:2609.04253v1 Announce Type: cross Abstract: Audio-video (AV) editing aims to modify audio and video content according to a target prompt. Unlike single-modality editing, AV editing requires mode
arXiv:2609.04292v1 Announce Type: new Abstract: Human mobility predictability concerns the best prediction performance attainable from a given target and input information, but its ground truth is not
arXiv:2609.05210v1 Announce Type: new Abstract: Recent hybrid Structure-from-Motion (SfM) systems combine the robustness of feed-forward 3D reconstruction with the accuracy of traditional bundle adjus
arXiv:2609.04716v1 Announce Type: new Abstract: Visual counting is commonly formulated at the instance level, aiming to estimate how many objects of a queried category appear in an image. However, rea
arXiv:2609.04851v1 Announce Type: cross Abstract: Remote robotic systems operating over wireless networks must maintain reliable control despite limited communication resources, changing channel condi
arXiv:2609.05245v1 Announce Type: new Abstract: Human knowledge is inherently structured and interdependent: mastery of a concept requires prior mastery of its prerequisites, a principle formalized by
arXiv:2609.04690v1 Announce Type: cross Abstract: Multimodal emotion recognition has attracted growing interest due to its importance in human-computer interaction, remote education, and healthcare. T
arXiv:2609.04512v1 Announce Type: cross Abstract: Oral potentially malignant disorders (OPMDs) are critical precursors to oral cancer, yet clinical detection remains challenging because of substantial
arXiv:2609.04815v1 Announce Type: new Abstract: Detecting orchestrated cyberattack campaigns that span multiple organizations traditionally requires sharing sensitive telemetry and threat intelligence
arXiv:2609.05325v1 Announce Type: new Abstract: Achieving robust SLAM in large-scale underground coal mines with complex structures and severe degeneracies remains highly challenging. Dense smoke and
arXiv:2609.05207v1 Announce Type: cross Abstract: Dynamical symbolic regression methods identify governing differential equations from noisy data, balancing interpretability and predictive accuracy. H
arXiv:2512.14779v2 Announce Type: replace Abstract: Standard weather forecast evaluations focus on the forecaster's perspective and on a statistical assessment comparing forecasts and observations. In
arXiv:2512.15751v2 Announce Type: replace-cross Abstract: Agentic Workflows (AWs) have emerged as a promising paradigm for solving complex tasks. However, automatically generating high-quality AWs rem
arXiv:2609.04442v1 Announce Type: cross Abstract: Large language models deployed in high-stakes settings frequently generate plausible but ungrounded claims. Standard retrieval-augmented generation (R
arXiv:2609.04585v1 Announce Type: cross Abstract: The Multi-Level Intermediate Representation (MLIR) has made reusable compiler infrastructure practical for domain-specific computation. However, MLIR'
Our research team has been exploring an alternative approach to achieving interactivity and better responsiveness with LLM systems. One of the team members wrote up a post about it: https://research.y
arXiv:2609.04645v1 Announce Type: cross Abstract: Multimodal Vision-Language Models (VLMs) have demonstrated remarkable capabilities in cross-modal understanding, yet a fundamental challenge persists
arXiv:2609.04939v1 Announce Type: new Abstract: The visual aesthetics of photographs are deeply influenced by lens characteristics such as aperture shape, optical vignetting and optical diffraction, w
arXiv:2609.04846v1 Announce Type: new Abstract: Weakly supervised 3D occupancy prediction reduces the reliance on costly 3D annotations by learning from 2D pseudo-labels generated by vision foundation
arXiv:2609.04866v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) create opportunities to enrich simulation-based energy policy analysis, particularly by supporting struc
arXiv:2609.04698v1 Announce Type: new Abstract: Vision transformers typically treat every image token as equally important, yet for most tasks in computer vision only a fraction are needed. Adaptive c
arXiv:2609.05070v1 Announce Type: new Abstract: Automated gastrointestinal (GI) endoscopy classification requires models that generalize across diverse modalities and class distributions, often far fr
arXiv:2609.04348v1 Announce Type: new Abstract: Object-centric visual representations are important for physical-world perception, but existing visual pretraining methods often capture semantic catego
arXiv:2609.05212v1 Announce Type: cross Abstract: Forecasting time series accurately is critical for applications with complex data ranging from energy systems to healthcare and finance. Among current
arXiv:2512.06813v3 Announce Type: replace-cross Abstract: High-performance concrete (HPC) requires complex mix design decisions involving interdependent variables and practical constraints. While data
arXiv:2609.05038v1 Announce Type: new Abstract: Species identification in camera trap images has been widely studied, but key ecological modeling tasks such as species abundance or density estimation
arXiv:2609.04880v1 Announce Type: new Abstract: Designing effective and fiscally sustainable policies for solar photovoltaic (PV) adoption requires balancing adoption gains against public expenditure
arXiv:2609.04751v1 Announce Type: new Abstract: 3D surface cutting and UV unwrapping are fundamental problems in computer graphics. Traditional geometric optimization methods mainly focus on reducing
arXiv:2609.05262v1 Announce Type: new Abstract: Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two fac
arXiv:2601.18049v2 Announce Type: replace Abstract: Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regarding feature extraction and classification perfo
arXiv:2603.29566v2 Announce Type: replace Abstract: We study polynomial group convolutional neural networks (PGCNNs) for an arbitrary finite group G. In particular, we introduce a new mathematical fra
arXiv:2609.05084v1 Announce Type: new Abstract: Reliable autonomous mapping, environmental sampling, last-mile logistics, and infrastructure deployment depend on the optimal surface area-balanced dist
https://huggingface.co/XHToken/Spark-X2.5-4B-GGUF https://huggingface.co/XHToken/Spark-X2.5-1.7B-GGUF from XHToken: We are introducing Spark-X2.5-4B and Spark-X2.5-1.7B, two compact, general-purpose l
arXiv:2609.03884v1 Announce Type: cross Abstract: Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These c
arXiv:2609.03129v1 Announce Type: cross Abstract: Several classical machine-learning methods, such as KRRs and SVRs, are both computationally and analytically tractable since their estimators either a
arXiv:2609.03366v1 Announce Type: new Abstract: Accountability means a decision can be examined, justified, and contested. LLMs make this hard: fluent output may be ungrounded, incomplete, or unfaithf
arXiv:2609.03860v1 Announce Type: new Abstract: Retail supply chain operations rely on coupled decision modules that must adapt as requirements evolve. LLMs offer a natural-language interface for this
arXiv:2609.03716v1 Announce Type: new Abstract: Data centers are increasingly optimized by artificial intelligence and, at the same time, increasingly loaded by it. The literature treats these as two
arXiv:2511.20591v3 Announce Type: replace Abstract: The emergence and evolution of feature reliance in deep reinforcement learning agents remain poorly understood. Here, we introduce a methodological
arXiv:2609.03953v1 Announce Type: new Abstract: Understanding the frequency of factual errors in chatbot-generated text and evaluating systems that detect these errors is critical for determining chat
arXiv:2605.06508v2 Announce Type: replace-cross Abstract: Research artifacts are widely shared to support reproducibility, and artifact evaluation (AE) has become common at many leading conferences. H
arXiv:2609.03463v1 Announce Type: new Abstract: Automated pig monitoring is essential for assessing their health, behaviour, and welfare. To date, most pig monitoring solutions operate on the group-le
arXiv:2609.03497v1 Announce Type: cross Abstract: Developing humanoid robots capable of leveraging human behavioral data is essential for general-purpose embodiment, yet conventional development remai
arXiv:2609.02899v1 Announce Type: new Abstract: Benchmark contamination, the leakage of test items into training data, is widely described as a threat to the reliability of large language model (LLM)
arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent
arXiv:2509.17154v2 Announce Type: replace-cross Abstract: Hamiltonian dynamics describe a wide range of physical systems. As such, data-driven simulations of Hamiltonian systems are important for many
arXiv:2609.03100v1 Announce Type: new Abstract: Geostationary atmospheric motion vectors (AMVs) provide the dense horizontal wind vectors (u,v) and heights ingested into data assimilation systems. Tra
arXiv:2609.03673v1 Announce Type: new Abstract: Video generators build long videos by composing shorter parts, either by generating segments one after another or by autoregressively extending chunks.