Knowledge catalogue
arXiv:2608.23300v1 Announce Type: cross Abstract: Algorithmic solver effort is often assumed to align with perceived puzzle difficulty, but this assumption is rarely tested against human solving data.
arXiv:2608.21559v1 Announce Type: new Abstract: Multi-stage LLM pipelines can remain structurally valid even when evidence available to downstream stages becomes incomplete, compressed, or conflicting
arXiv:2608.22671v1 Announce Type: new Abstract: The uniform car-parking process is the one-dimensional random sequential adsorption of unit cars on a segment of finite length s: cars arrive at uniform
arXiv:2608.22909v1 Announce Type: new Abstract: Dowker homology is a topological tool that may be used to analyze the relative position of two point clouds living in a common space. We investigate whe
arXiv:2408.07988v3 Announce Type: replace Abstract: Despite significant research efforts and advancements, cancer remains a leading cause of mortality. Early cancer prediction has become a crucial foc
arXiv:2608.21571v1 Announce Type: new Abstract: Lung cancer remains a leading cause of cancer-related mortality worldwide, and early diagnosis is critical for improving survival. However, early-stage
arXiv:2604.01844v2 Announce Type: replace Abstract: Gaussian Splatting (GS) has emerged as a dominating technique for image rendering and has quickly been adapted for the X-ray Computed Tomography (CT
arXiv:2608.22344v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves state-of-the-art rendering quality at real-time speeds but suffers from 'model bloat' - a large number of redundan
arXiv:2608.21750v1 Announce Type: new Abstract: Parametric retrieval-augmented generation (PRAG) injects retrieved evidence into a large language model (LLM) through passage-specific LoRA adapters, re
arXiv:2608.23308v1 Announce Type: cross Abstract: An LLM asked for a trading strategy returns three artifacts at once: a natural-language rationale, an executable implementation, and once run, a track
arXiv:2511.22024v2 Announce Type: replace Abstract: We liberate Equilibrium Propagation (EP) from the limit of infinitesimal perturbations by establishing a finite-nudge foundation for local credit as
arXiv:2602.03927v2 Announce Type: replace-cross Abstract: When does a fractional quantum Hall (FQH) liquid crystallize? Addressing this question requires a framework that treats fractionalization and
arXiv:2608.21741v1 Announce Type: cross Abstract: Polyethylene (PE) is one of the most commonly used synthetic polymers. While the synthesis and processing protocols for PE are well established, preci
arXiv:2608.23549v1 Announce Type: new Abstract: Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces a
arXiv:2608.23327v1 Announce Type: new Abstract: Flesch Reading Ease (FRE) and the Flesch-Kincaid Grade Level (FKGL) are widely used readability scores for English computed from the same two document s
arXiv:2608.22861v1 Announce Type: new Abstract: State Space Models (SSMs) have surfaced as a promising architecture in Video Frame Interpolation (VFI), as they can capture long-range dependencies with
arXiv:2510.17021v2 Announce Type: replace-cross Abstract: Large language model (LLM) unlearning is a key approach for removing undesired data, knowledge, or behaviors from pretrained models while reta
arXiv:2608.23353v1 Announce Type: new Abstract: Mixed-integer programming (MIP) lies at the core of operations research and industrial optimization. While large language models (LLMs) have recently sh
arXiv:2608.22883v1 Announce Type: new Abstract: Multimodal speculative decoding accelerates vision-language models by allowing a lightweight draft model to propose candidate tokens for parallel verifi
arXiv:2608.22522v1 Announce Type: new Abstract: Data valuation is a cornerstone of data-centric learning, where prior efforts primarily focus on designing algorithms to classify training samples as ei
arXiv:2608.22452v1 Announce Type: new Abstract: Surprisal, the negative log-probability a language model assigns to a word given its preceding context, reliably predicts adult reading times. Does it c
arXiv:2608.23070v1 Announce Type: new Abstract: With the rapid progress of diffusion models and large-scale video generation, generative world models are increasingly expected to replace traditional s
arXiv:2608.23248v1 Announce Type: cross Abstract: Traditional clinical prediction models rely on task-specific pipelines and curated, structured data, which scale poorly and underutilize unstructured
arXiv:2608.21371v1 Announce Type: cross Abstract: Perimeter-gated single-photon avalanche diodes (pg-SPADs) are known for their dynamic dark noise modulation capabilities. They are reported to trade n
arXiv:2608.21849v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has achieved remarkable success in novel view synthesis; however, reconstructions under sparse views often exhibit noticeab
arXiv:2608.22746v1 Announce Type: cross Abstract: This paper studies the Sinkhorn distributionally robust hypothesis testing (SDRHT) problem, seeking a robust detector against least-favorable distribu
arXiv:2608.22453v1 Announce Type: new Abstract: We propose a holonomy-based framework for discretizing curvature on graphs equipped with local symmetric positive-definite metrics. Each vertex carries
arXiv:2608.22619v1 Announce Type: cross Abstract: Generative segmentation provides an alternative to direct pixel-wise prediction by operating on learned latent representations, but effective image-to
arXiv:2608.21388v1 Announce Type: new Abstract: Reliable and continuous human tracking is essential for natural human-robot interaction, particularly for companion robots. However, many existing appro
arXiv:2608.21550v1 Announce Type: new Abstract: Disassembling end-of-life electric vehicle (EV) battery packs is dull and dangerous work, performed almost entirely by humans. We present GOLEM (General
arXiv:2603.26756v2 Announce Type: replace Abstract: Deep ConvNets suffer from gradient signal degradation as network depth increases, limiting effective feature learning in complex architectures. ResN
arXiv:2608.22381v1 Announce Type: cross Abstract: Scientific papers may relate by problem, method, result, or contribution, but document-level retrievers collapse these into a single similarity score
arXiv:2608.23054v1 Announce Type: new Abstract: SIMON and SIMECK belong to a family of Lightweight Cryptographic Algorithms (LCAs) based on the Feistel block cipher, designed for Internet of Things (I
arXiv:2607.10357v2 Announce Type: replace-cross Abstract: The automatic detection and classification of cardiovascular disease (CVD) from computed tomography (CT) images plays an important role in cli
arXiv:2608.22485v1 Announce Type: new Abstract: Current visual tokenizers in Multimodal Large Language Models (MLLMs) predominantly rely on patch-based partitioning, which causes severe semantic mixtu
arXiv:2608.22922v1 Announce Type: new Abstract: We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text source
arXiv:2608.22839v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for scientific decision support, yet reliable confidence estimation remains difficult in black-box
arXiv:2608.21446v1 Announce Type: cross Abstract: We study whether the loss design of High-Fidelity Generative Image Compression (HiFiC), a GAN-based neural codec originally built for natural photogra
arXiv:2507.21984v2 Announce Type: replace-cross Abstract: Networks of phase oscillators can serve as dense associative memories when they incorporate genuine many-body coupling beyond the classical Ku
arXiv:2608.23543v1 Announce Type: new Abstract: While AI assistance can improve human task performance in the short term, it may also undermine the development of skills in the longer term. We examine
arXiv:2608.21756v1 Announce Type: cross Abstract: Deep-learning efforts have increasingly shifted toward foundation model approaches. In experimental physics, this allows models and learned representa
arXiv:2608.22692v1 Announce Type: new Abstract: As an important operation of image composition, object placement aims to predict the plausible placement (location, scale) for the inserted foreground o
arXiv:2608.22665v1 Announce Type: cross Abstract: We investigate the token mixer in vision backbones by revisiting clustering, one of the most classic approaches in machine learning. An effective toke
arXiv:2608.22980v1 Announce Type: cross Abstract: Dense vector retrieval has become the foundation of modern semantic search, yet existing approximate nearest neighbor (ANN) indexes treat an embedding
Humanoid robots are having a moment in China. The popular machines are part of the country’s strategy to bring artificial intelligence into daily life. Embedding the technology into physical systems—a
arXiv:2407.05389v2 Announce Type: replace-cross Abstract: Underwater image enhancement (UIE) has attracted much attention owing to its importance for underwater operation and marine engineering. Motiv
arXiv:2608.23432v1 Announce Type: new Abstract: Accurate organ-at-risk segmentation is essential for radiotherapy planning, but reviewing segmentations is time-consuming and subjective. We investigate
arXiv:2608.21972v1 Announce Type: new Abstract: The sampling process of Denoising Diffusion Probabilistic Models (DDPMs) can be accelerated by leveraging second-order information in the form of approx
arXiv:2608.22244v1 Announce Type: cross Abstract: Flow-matching language models refine all token positions in parallel and can trade sampling steps for latency, yet generation quality still degrades s
arXiv:2608.21685v1 Announce Type: new Abstract: This article presents a novel 3D reconstruction and mapping of the interior of the International Space Station (ISS) using 3D Gaussian Splatting (3DGS).
arXiv:2608.22067v1 Announce Type: cross Abstract: World-Action Models (WAMs) build robot control on video-generation backbones, which jointly predict dense future visual trajectories and robot actions
arXiv:2608.22515v1 Announce Type: cross Abstract: Reliable early disruption prediction is critical for the safe operation and real-time control of tokamaks. However, machine learning based prediction
arXiv:2608.21389v1 Announce Type: cross Abstract: Generative AI enables customized misinformation at scale, yet defenses remain largely reactive. We present empirical findings from a human-subject stu
arXiv:2608.23518v1 Announce Type: new Abstract: Vision-Language Models (VLMs) achieve strong performance in visual reasoning tasks, but it remains unclear whether they understand visual relations, or
arXiv:2608.23256v1 Announce Type: new Abstract: Recent work proposes next-chunk reasoning RL for leveraging no-CoT data---corpora such as worked solutions and textbook derivations that contain reasoni
arXiv:2608.22651v1 Announce Type: new Abstract: Modern text-to-SQL systems have become increasingly elaborate, relying on schema-linking modules, retrieval-augmented prompting, candidate generation, a
arXiv:2608.23393v1 Announce Type: cross Abstract: KellyBoost is a single multi-output XGBoost model whose softmax output is the portfolio: with y the vector of per-asset holding-period returns, the tr
arXiv:2608.22916v1 Announce Type: new Abstract: Vision-language models are known to encode spatial information in their hidden states, yet often fail to use it when answering. However, it remains uncl
arXiv:2608.22389v1 Announce Type: cross Abstract: Regulation (EU) 2024/886 obliges European payment service providers to settle euro credit transfers in under ten seconds, around the clock. This remov
arXiv:2608.22457v1 Announce Type: new Abstract: An inner hood panel must meet a deflection target, stay below a stress limit, and hit a mass target. Machine-learned surrogates have made the forward di