Knowledge catalogue
arXiv:2604.21924v1 Announce Type: new Abstract: Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to c
arXiv:2507.03933v3 Announce Type: replace Abstract: Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist hum
arXiv:2601.18714v2 Announce Type: replace-cross Abstract: Localization in agricultural environments is challenging due to their unstructured nature and lack of distinctive landmarks. Although agricult
arXiv:2604.21905v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has emerged as the de facto standard for parameter-efficient fine-tuning (PEFT) of foundation models, enabling the adaptation
arXiv:2511.18513v2 Announce Type: replace Abstract: Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruc
arXiv:2604.20871v1 Announce Type: cross Abstract: We introduce M-CARE (Model Clinical Assessment and Reporting for Evaluation), a clinical case report framework for AI model behavioral disorders adapt
arXiv:2604.21871v1 Announce Type: new Abstract: Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decisio
arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1
arXiv:2604.21897v1 Announce Type: new Abstract: Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper,
arXiv:2602.18792v3 Announce Type: replace Abstract: Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interp
arXiv:2604.21119v1 Announce Type: cross Abstract: Rings like gold, thuds like wood! The sound we hear in a scene is shaped not only by the spatial layout of the environment but also by the materials o
arXiv:2604.21916v1 Announce Type: new Abstract: As frontier language models attain near-ceiling performance on static mathematical benchmarks, existing evaluations are increasingly unable to different
arXiv:2604.20848v1 Announce Type: cross Abstract: Large Language Model (LLM)-based recommendation systems have demonstrated remarkable capabilities in understanding user preferences and generating per
arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili
arXiv:2604.21365v1 Announce Type: cross Abstract: Multi-domain detection of the machine-generated code snippets in various programming languages is a challenging task. SemEval-2026 Task~13 copes with
arXiv:2604.21268v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogen
arXiv:2603.18740v2 Announce Type: replace-cross Abstract: Automated Code Review (ACR) systems integrating Large Language Models (LLMs) are increasingly adopted in software development workflows, rangi
arXiv:2604.21564v1 Announce Type: new Abstract: Large language models increasingly shape the information people consume: they are embedded in search, consulted for professional advice, deployed as age
arXiv:2507.01829v2 Announce Type: replace-cross Abstract: Multi-timescale sequence modeling relies on capturing both local fast dynamics and global slow context; yet, maintaining these capabilities un
arXiv:2604.21011v1 Announce Type: new Abstract: Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential fo
arXiv:2604.21326v1 Announce Type: cross Abstract: Universal Multimodal Retrieval (UMR) aims to map different modalities (e.g., visual and textual) into a shared embedding space for multi-modal retriev
arXiv:2309.07176v5 Announce Type: replace Abstract: In consequential domains, it is often impossible to compel individuals to take treatment, so that optimal policy rules are merely suggestions in the
arXiv:2604.21092v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into complex software systems enables the generation of human-understandable explanations of opaque AI processe
arXiv:2604.21767v1 Announce Type: new Abstract: Online misinformation is one of the most challenging issues lately, yielding severe consequences, including political polarization, attacks on democracy
arXiv:2604.21489v1 Announce Type: cross Abstract: Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency d
arXiv:2510.18731v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate strong capabilities in single-turn instruction following but suffer from Lost-in-Conversation (LiC), a degra
arXiv:2604.20858v1 Announce Type: cross Abstract: Sequential recommendation has rapidly advanced in click-through rate prediction due to its ability to model dynamic user interests. A key challenge, h
arXiv:2604.21370v1 Announce Type: new Abstract: We present a systematic study of multilingual polarization detection across 22 languages for SemEval-2026 Task 9 (Subtask 1), contrasting multilingual g
arXiv:2604.21836v1 Announce Type: cross Abstract: Neural networks exhibit a remarkable degree of representational convergence across diverse architectures, training objectives, and even data modalitie
arXiv:2604.21155v1 Announce Type: new Abstract: Intrinsic motivations are receiving increasing attention, i.e. behavioral incentives that are not engineered, but emerge from the interaction of an agen
arXiv:2604.21096v1 Announce Type: cross Abstract: Tip-of-the-Tongue (ToT) retrieval benchmarks have largely focused on English, limiting their applicability to multilingual information access. In this
arXiv:2604.21637v1 Announce Type: new Abstract: Where and how language models (LMs) are deployed determines who can benefit from them. However, there are several challenges that prevent effective depl
arXiv:2512.18908v2 Announce Type: replace Abstract: Mass Casualty Incidents can overwhelm emergency medical systems and resulting delays or errors in the assessment of casualties can lead to preventab
arXiv:2603.12845v2 Announce Type: replace Abstract: Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canon
arXiv:2604.21810v1 Announce Type: new Abstract: We address the ambiguities in the super-resolution problem under translation. We demonstrate that combinations of low-resolution images at different sca
arXiv:2511.20697v4 Announce Type: replace-cross Abstract: Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of
arXiv:2604.21138v1 Announce Type: cross Abstract: Multi-robot control in cluttered environments is a challenging problem that involves complex physical constraints, including robot-robot collisions, r
arXiv:2604.21896v1 Announce Type: new Abstract: This paper introduces a new paradigm for AI game programming, leveraging large language models (LLMs) to extend and operationalize Claude Shannon's taxo
arXiv:2604.21753v1 Announce Type: cross Abstract: Simulations of crystal growth are performed by using Convolutional Recurrent Neural Network surrogate models, trained on a dataset of time sequences c
arXiv:2604.21053v1 Announce Type: cross Abstract: Robotic systems operating in human environments must reason about how object interactions evolve over time, which actions are currently being performe
arXiv:2604.21222v1 Announce Type: cross Abstract: Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge f
arXiv:2506.05590v3 Announce Type: replace-cross Abstract: Recent advances have established the identifiability of a directed acyclic graph (DAG) under additive noise models (ANMs), spurring the develo
arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection
arXiv:2601.20706v2 Announce Type: replace-cross Abstract: Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, b
arXiv:2604.20911v1 Announce Type: cross Abstract: LLM agents deployed in production operate under operator-defined behavioral policies (system-prompt instructions such as prohibitions on credential di
arXiv:2604.21575v1 Announce Type: new Abstract: Fitting an underlying body model to 3D clothed human assets has been extensively studied, yet most approaches focus on either single-modal inputs such a
arXiv:2604.21204v1 Announce Type: cross Abstract: In this work, we develop a novel reasoning approach to enhance the performance of large language models (LLMs) in future occupation prediction. In thi
arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a
arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural
arXiv:2604.21602v1 Announce Type: cross Abstract: Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modes
arXiv:2604.21017v1 Announce Type: cross Abstract: Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precis
arXiv:2510.15096v2 Announce Type: replace Abstract: Real-world settings where language models (LMs) are deployed -- in domains spanning healthcare, finance, and other forms of knowledge work -- requir
arXiv:2602.01493v2 Announce Type: replace-cross Abstract: Solving diverse partial differential equations (PDEs) is fundamental in science and engineering. Large language models (LLMs) have demonstrate
arXiv:2510.13918v2 Announce Type: replace Abstract: Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language mode
arXiv:2604.21066v1 Announce Type: new Abstract: While diffusion priors generate high-quality posterior samples across many inverse problems, they are often trained on limited training sets or purely s
arXiv:2604.21510v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning, complex optimization tasks remain challenging, requiring domain knowledge and robus
arXiv:2604.20981v1 Announce Type: cross Abstract: Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma
arXiv:2601.15984v2 Announce Type: replace Abstract: We introduce extsc{k-lazyGD}, an online learning algorithm that bridges the gap between greedy Online Gradient Descent (OGD, for k{=}1) and lazy GD/
arXiv:2604.21202v1 Announce Type: cross Abstract: Local government meetings are the most common formal channel through which residents speak directly with elected officials, contest policies, and shap
arXiv:2511.21978v2 Announce Type: replace Abstract: We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simu