Knowledge catalogue
arXiv:2608.03430v1 Announce Type: new Abstract: Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times,
arXiv:2608.03411v1 Announce Type: new Abstract: Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics
arXiv:2608.03410v1 Announce Type: new Abstract: Earth observation is moving from foundation models that users must run themselves toward embedding products that package model feature outputs as reusab
arXiv:2411.19896v2 Announce Type: replace-cross Abstract: Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does t
arXiv:2608.03269v1 Announce Type: cross Abstract: Video dataset distillation aims to compress a large video dataset into a compact surrogate set that preserves its training utility. Most existing appr
arXiv:2608.03171v1 Announce Type: cross Abstract: We study fair allocations of indivisible goods among agents with heterogeneous monotone valuations. As fair we consider the allocations that are envy-
arXiv:2608.02990v1 Announce Type: new Abstract: Latent diffusion models (LDMs) have recently significantly advanced embodied learning in constructing powerful embodied manipulation world models. Howev
arXiv:2608.03920v1 Announce Type: cross Abstract: Humans recognize a musical passage even when it is shifted in time or transposed in pitch, indicating a notion of equivariance in the representation s
arXiv:2608.02966v1 Announce Type: new Abstract: Most multiple-choice question (MCQ) benchmarks evaluate Large Language Models (LLMs) only by whether they select the correct answers. This binary scorin
arXiv:2608.03161v1 Announce Type: new Abstract: Lecture videos distribute knowledge across speech, slide text, diagrams, equations, and presentation order, which transcript-only retrieval does not ful
arXiv:2608.03372v1 Announce Type: cross Abstract: AI systems rewrite information constantly: conversations become stored memories, documents become answers. The rewrite can keep a claim while washing
arXiv:2608.03733v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-
arXiv:2608.03106v1 Announce Type: new Abstract: Infrared image super-resolution (IISR) is important for downstream tasks such as object detection and semantic segmentation. Existing IISR methods often
arXiv:2608.02939v1 Announce Type: new Abstract: Electronic health record foundation models are limited by institutionally siloed data and substantial performance degradation under cross-site transfer.
arXiv:2608.03436v1 Announce Type: cross Abstract: Federated learning over low Earth orbit (LEO) satellite networks is limited by frequent link changes, short contact times, and a highly dynamic topolo
arXiv:2608.03822v1 Announce Type: cross Abstract: Developing robust flood assessment models requires high-quality paired satellite imagery, yet such data remain scarce for flood-specific image generat
arXiv:2608.03597v1 Announce Type: new Abstract: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with increased risks of stroke, heart failure, and mortality.
arXiv:2608.03605v1 Announce Type: new Abstract: Federated fine-tuning with Low-Rank Adaptation (LoRA) enables efficient collaborative adaptation of Large Language Models (LLMs) without centralizing pr
arXiv:2608.03176v1 Announce Type: new Abstract: Imagined handwriting offers a temporally rich paradigm for non-invasive neural decoding, yet reliable recognition across unseen participants remains dif
arXiv:2607.18303v2 Announce Type: replace-cross Abstract: Identifying which string produces a given pitch in monophonic electric guitar audio is a classification challenge: a single pitch can often be
arXiv:2608.03508v1 Announce Type: new Abstract: Vision Transformers (ViTs) and their hierarchical variants have achieved strong performance in Computational Pathology (CPath). However, most are pre-tr
arXiv:2608.03251v1 Announce Type: cross Abstract: Commercial wearable devices continuously capture rich physiological data (e.g., heart rate, respiration), opening new possibilities for monitoring hea
arXiv:2604.01832v1 Announce Type: cross Abstract: We introduce GAP-URGENet, a generative-predictive fusion framework developed for Track 1 of the ICASSP 2026 URGENT Challenge. The system integrates a
arXiv:2608.03618v1 Announce Type: new Abstract: Inferring complete 3D geometry and semantics from onboard images remains challenging because occlusions and restricted fields of view leave large scene
arXiv:2608.03064v1 Announce Type: new Abstract: We study open-vocabulary 3D indoor layout generation, which synthesizes diverse and physically plausible scenes from unlabeled 3D assets using free-form
arXiv:2608.03729v1 Announce Type: cross Abstract: Automated Knowledge Base Construction (AKBC) is a core NLP task, and recent work proposes generating knowledge bases directly from large language mode
arXiv:2511.03170v3 Announce Type: replace-cross Abstract: The quantitative structure-activity relationship assumes a smooth mapping between molecular structure and biological activity. However, activi
arXiv:2608.03966v1 Announce Type: new Abstract: Large language models can generate fluent Arabic answers while introducing factual errors that are difficult to identify and verify. Existing Arabic hal
arXiv:2603.10582v2 Announce Type: replace Abstract: Ensembling is commonly used in machine learning on tabular data to boost predictive performance and robustness, but larger ensembles often lead to i
arXiv:2608.03264v1 Announce Type: cross Abstract: Audio-visual instance segmentation (AVIS) requires accurately identifying and tracking individual sounding objects with pixel-level masks. Existing me
arXiv:2508.01597v2 Announce Type: replace Abstract: Score Matching (SM) is a powerful framework for estimating the log-density derivatives of a distribution without calculating its normalizing constan
arXiv:2608.03511v1 Announce Type: cross Abstract: Active learning (AL) promises to reduce the cost of medical imaging projects by lowering the number of clinical labels required. However, practical de
arXiv:2608.03052v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models almost universally take robot proprioceptive state as input, yet wire it in incompatible ways -- serialized i
arXiv:2608.02711v1 Announce Type: new Abstract: Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing.
arXiv:2608.03422v1 Announce Type: new Abstract: Planar tiled diffusion denoises overlapping windows of one rectangular canvas. The hyperbolic plane has no such canvas, and its area grows exponentially
arXiv:2608.02930v1 Announce Type: new Abstract: We revisit higher-arity atomic concept learning through the geometry of hypercubes and hyperplanes of ground instances. Our starting point is the observ
arXiv:2608.03216v1 Announce Type: new Abstract: Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inferenc
arXiv:2608.03539v1 Announce Type: new Abstract: Most in-generation diffusion watermarks embed patterns independent of the image that carries them, and attackers transplant the marks onto images the ge
arXiv:2608.03035v1 Announce Type: new Abstract: Prior work has shown that LLMs encode the truth of factual propositions along linear directions in activation space. It's unclear how these representati
arXiv:2608.02807v1 Announce Type: cross Abstract: How can we better represent the impact of sociocultural structures on decision making in computational cognitive models? Modeling this impact requires
arXiv:2608.03637v1 Announce Type: new Abstract: Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We add
arXiv:2608.03851v1 Announce Type: new Abstract: Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods pri
arXiv:2608.03457v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dL
arXiv:2608.02632v1 Announce Type: new Abstract: Circuit tracing is an exciting technique for revealing the internal computation of language models, but it requires a time-intensive manual step of grou
arXiv:2608.03930v1 Announce Type: cross Abstract: Pre-pretraining language models (LMs) on symbolic data can accelerate and improve natural language acquisition. However, existing pre-pretraining task
arXiv:2608.02971v1 Announce Type: new Abstract: Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and
arXiv:2608.03769v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) enable parallel generation and bidirectional context modeling, but their positional context differs fundament
arXiv:2509.21012v4 Announce Type: replace-cross Abstract: In-context Learning (ICL) is an emerging few-shot learning paradigm based on modern Language Models (LMs), yet its inner mechanism remains unc
arXiv:2608.03740v1 Announce Type: new Abstract: Recent GUI visual grounding models generate screen coordinates as sequences of digit tokens that are parsed into numerical values and mapped to executab
arXiv:2603.15212v2 Announce Type: replace Abstract: Evaluating football player transfers is challenging because player actions depend strongly on tactical systems, teammates, and match context. Despit
arXiv:2606.15615v2 Announce Type: replace-cross Abstract: Diffusion Transformers with Mixture-of-Experts (DiT-MoE) improve model capacity under sparse activation, but diffusion inference is still bott
arXiv:2402.13822v2 Announce Type: replace Abstract: Most of the previous approaches to Time Series Classification (TSC) highlight the significance of receptive fields and frequencies while overlooking
arXiv:2608.03636v1 Announce Type: cross Abstract: Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optim
arXiv:2108.04694v2 Announce Type: cross Abstract: We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network o
arXiv:2608.03419v1 Announce Type: cross Abstract: Audio-based piano transcription performs well on onset, pitch, and velocity, but the sustain pedal lets sound persist long after key release, so audio
arXiv:2608.02629v1 Announce Type: cross Abstract: The use of variable well perforation and injection strategies can improve the efficiency of geological carbon storage operations. We develop a new mul
arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T
arXiv:2608.03941v1 Announce Type: new Abstract: Muon is a recent optimizer that orthogonalizes the update to each weight matrix with a Newton-Schulz iteration, which performs steepest descent under th
arXiv:2608.02700v1 Announce Type: cross Abstract: Analog compute-in-memory (CIM) enables energy-efficient neural network inference, but device variation and read noise can severely degrade low-bit qua
arXiv:2608.03895v1 Announce Type: new Abstract: Camera-based bird's-eye-view (BEV) 3D detection typically assumes accurate and fixed camera extrinsics. In detectors using spatial cross-attention (SCA)