Knowledge catalogue
arXiv:2509.20666v2 Announce Type: replace-cross Abstract: Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which sub
arXiv:2609.19878v1 Announce Type: cross Abstract: Multimodal reasoning requires models to draw on information from multiple modalities throughout the reasoning process. Yet existing methods often conc
arXiv:2609.20570v1 Announce Type: new Abstract: This paper presents the kinematic and dynamic modeling, trajectory generation, and stability analysis of an 8-degree-of-freedom (DOF) biped robot walkin
arXiv:2509.24368v3 Announce Type: replace-cross Abstract: We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary
arXiv:2609.19647v1 Announce Type: cross Abstract: A neural turbulence closure defines a new boundary-value problem, R(U)=N(U)+F(U)=0, with a coupled Jacobian J(U)=N'(U)+F'(U), where N is the original
arXiv:2609.19212v1 Announce Type: new Abstract: Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to s
arXiv:2607.10116v2 Announce Type: replace-cross Abstract: We study robust generalization under spurious correlations: tasks where a shortcut feature is correlated with the true label in training but a
arXiv:2609.20193v1 Announce Type: new Abstract: Retrieval plug-ins supply a deep forecaster with information its lookback window cannot carry. Published evaluations report consistent gains, and each c
arXiv:2609.19671v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex tasks but exhibit systematic inefficiency: they often overthink easy problems and un
arXiv:2609.20593v1 Announce Type: new Abstract: Word-in-Context (WiC) remains challenging for language models, despite recent progress on lexical-semantic tasks. We hypothesise that this difficulty ar
arXiv:2609.20057v1 Announce Type: new Abstract: Because of its collaborative nature, Wikidata suffers from errors, in- consistencies, and excessive complexity, such as redundant classes, ambiguity bet
arXiv:2609.19238v1 Announce Type: cross Abstract: This paper describes the participation of the YNU-HPCC team in subtask A of task 11, Bridging the Gap in Text-Based Emotion at SemEval-2025. Our best-
arXiv:2609.19868v1 Announce Type: cross Abstract: Autoregressive language models (ARMs) are constrained by sequential, left-to-right generation, while masked diffusion models (MDMs) enable parallel de
arXiv:2609.17804v1 Announce Type: new Abstract: Large language models solve grade-school math word problems with high accuracy, yet a single irrelevant clause inserted into the problem can collapse it
arXiv:2609.19083v1 Announce Type: cross Abstract: Kernel methods, and Gaussian Processes (GPs) in particular, require a Hilbertian distance measure---one whose square is conditionally negative definit
arXiv:2509.19276v2 Announce Type: replace-cross Abstract: Solving ill-posed inverse problems requires powerful and flexible priors. We propose leveraging pretrained latent diffusion models for this ta
arXiv:2609.18212v1 Announce Type: cross Abstract: Over the years, Convolutional Neural Networks (CNNs) have demonstrated strong capability in cancer detection and classification using medical images.
arXiv:2609.18399v1 Announce Type: cross Abstract: Identifying isolated points is important in image processing applications such as medical imaging, astronomy and quality control management. Other dom
arXiv:2609.18739v1 Announce Type: cross Abstract: Poor quality or noisy annotations in Named Entity Recognition (NER), as in any other NLP task, make it challenging to achieve state-of-the-art perform
arXiv:2502.12048v4 Announce Type: replace Abstract: Decoding neural activity into human-interpretable representations is a key research direction in brain-computer interfaces (BCIs) and computational
arXiv:2609.17731v1 Announce Type: new Abstract: High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management
arXiv:2604.00239v3 Announce Type: replace Abstract: The world's 7,000+ languages vary widely in the availability of resources for NLP, motivating efforts to systematically categorize them by their deg
arXiv:2609.17691v1 Announce Type: cross Abstract: Speculative sampling accelerates diffusion model generation by drafting inexpensive candidate states and correcting them under a coupling that preserv
arXiv:2609.18577v1 Announce Type: new Abstract: We consider the problem of estimating the trace of an implicit matrix mathbf{A} in R^{d^pimes d^p} that can only be accessed through matrix-vector produ
arXiv:2501.02059v2 Announce Type: replace Abstract: Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecu
arXiv:2609.17832v1 Announce Type: new Abstract: Legged robots have demonstrated a remarkable ability to traverse various terrains, yet generating effective loco-manipulation behaviors remains challeng
arXiv:2609.17853v1 Announce Type: cross Abstract: AfriSyCo studies answer switching around African-language factual content with two complementary layers: native-language follow-ups and a controlled c
arXiv:2609.17779v1 Announce Type: cross Abstract: AI systems have begun to report solutions, disproofs, and substantive advances on long-standing mathematical problems, raising questions about whether
arXiv:2511.18060v3 Announce Type: replace-cross Abstract: Wasserstein-Fisher-Rao (WFR) gradient flows have been recently proposed as a powerful sampling tool that combines the advantages of pure Wasse
arXiv:2609.18169v1 Announce Type: new Abstract: Self-motion manifold (SMM) characterizes the geometric structure of the infinite inverse kinematic solutions set of a redundant manipulator at a fixed e
arXiv:2604.08194v2 Announce Type: replace Abstract: The Maxey-Riley-Gatignol equations (MaRGE) model the motion of spherical inertial particles in a fluid. They contain the Basset force, an integral t
arXiv:2609.17943v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound. Self-speculative decoding alleviate
arXiv:2609.18813v1 Announce Type: new Abstract: Multi-robot task and motion planning (MR-TAMP) requires jointly reasoning about discrete task decisions and continuous collision-free motions of multipl
arXiv:2602.16218v2 Announce Type: replace Abstract: Bayesian quadrature is a probabilistic, model-based approach to numerical integration, the estimation of intractable integrals, or expectations. Alt
arXiv:2609.18273v1 Announce Type: new Abstract: Web browsing often appears ephemeral: users visit a few websites, complete a task, and move on. However, even short fragments of browsing activity can c
arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re
arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed st
arXiv:2609.18804v1 Announce Type: new Abstract: Identifying technological trends is a core scientometric task, yet traditional frequency-based approaches struggle to capture substantial meaning shifts
arXiv:2609.18100v1 Announce Type: cross Abstract: Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve
arXiv:2609.18314v1 Announce Type: new Abstract: Loss spikes are recurrent instabilities in neural-network training and can arise from multiple mechanisms. For Adam in particular, macroscopic loss spik
arXiv:2609.18723v1 Announce Type: new Abstract: We introduce Mahalanobis-Ensemble Decoding (ME-Decoding), a novel Large Language Model (LLM) decoding framework that frames candidate token selection as
arXiv:2609.17892v1 Announce Type: cross Abstract: The manifold hypothesis suggests a natural criterion for clustering: partition data according to the manifold component from which each point is drawn
arXiv:2406.13668v4 Announce Type: replace Abstract: A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on t
arXiv:2609.18489v1 Announce Type: cross Abstract: This study analyses kinetic energy (KE) spectra, difference kinetic energy (DKE) spectra, and signatures of KE transfer across spatial scales in four
arXiv:2609.17820v1 Announce Type: new Abstract: Fine-grained recognition of visually similar industrial parts is challenging when classes differ primarily in physical dimensions. Normalizing detected
arXiv:2609.17882v1 Announce Type: cross Abstract: An important component of urban accessibility, particularly for wheelchair users and people with reduced mobility, is sidewalk compliance with measura
arXiv:2609.19000v1 Announce Type: new Abstract: Emergent capabilities are widely treated as unpredictable: loss improves smoothly while abilities appear abruptly. Prior work offers early-warning indic
arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence
arXiv:2609.18131v1 Announce Type: cross Abstract: In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computa
arXiv:2609.19004v1 Announce Type: cross Abstract: Code optimization plays a crucial role in the development of virtual machine compilers, with optimization frameworks significantly enhancing the perfo
arXiv:2609.18928v1 Announce Type: cross Abstract: In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter f
arXiv:2506.24048v2 Announce Type: replace-cross Abstract: Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical prop
arXiv:2508.08307v2 Announce Type: replace-cross Abstract: Machin-like arctangent relations are classical tools for computing pi, with efficiency quantified by the Lehmer measure (lambda). We present a
arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly
arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction
arXiv:2609.18394v1 Announce Type: new Abstract: We report the results of a Turing Test conducted in Finland in the Finnish language. Because languages and cultural contexts are unevenly represented in
arXiv:2609.17535v1 Announce Type: new Abstract: Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Compa
arXiv:2609.17886v1 Announce Type: new Abstract: EEG decoding tasks can rely on different temporal dynamics and cross-channel relationships. We test whether specialized modules improve a fully fine-tun
arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha
arXiv:2609.17721v1 Announce Type: cross Abstract: Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after sys