Knowledge catalogue
arXiv:2609.22055v1 Announce Type: new Abstract: A desirable property of a world model is the ability to learn continually across tasks, adapting to new environments without forgetting what the agent h
arXiv:2609.21599v1 Announce Type: new Abstract: Fraudulent job posting detection aims to identify job advertisements that are corrupted either through fake content, misleading information, or negative
arXiv:2609.21362v1 Announce Type: new Abstract: Conventional tokenizers represent text as characters or statistically derived subwords, overlooking the internal phonological structure of syllables and
arXiv:2609.21763v1 Announce Type: new Abstract: A medical model's benchmark score does not establish that the same conclusion holds under a different evaluation. This study tests whether claims about
arXiv:2609.21276v1 Announce Type: cross Abstract: In automated Printed Circuit Board Assembly (PCBA) inspection, standards-guided decisions require systems to jointly reason over fine-grained visual c
arXiv:2603.13099v3 Announce Type: replace Abstract: We introduce CRYSTAL (Clear Reasoning via Yielded Steps, Traceability, and Logic), a diagnostic benchmark with 6,372 instances that evaluates multim
arXiv:2609.21656v1 Announce Type: new Abstract: Recent Joint-Embedding Predictive Architectures (JEPAs) prevent representation collapse by constraining learned representations to follow a prescribed t
arXiv:2609.21909v1 Announce Type: new Abstract: In this work, we conduct a systematic comparison of two state-of-the-art motion-imitation reinforcement learning (MIRL) pipelines, one built on SCONE/Hy
arXiv:2609.21231v1 Announce Type: new Abstract: Reference-based metrics for Grammatical Error Correction (GEC) such as M^2 and ERRANT assume that the reference set enumerates all valid edits, and ther
arXiv:2609.20828v1 Announce Type: new Abstract: ASR systems optimised for Word Error Rate (WER) often miss named entities and filled pauses in accented conversational English, both critical for langua
arXiv:2609.20886v1 Announce Type: cross Abstract: Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tabl
arXiv:2609.21758v1 Announce Type: new Abstract: Topology optimization (TO) represents a significant step towards automating the design process: given a working simulation, TO can produce a viable prot
arXiv:2609.20904v1 Announce Type: cross Abstract: Hybrid motor-imagery brain-computer interfaces (MI-BCIs) combining EEG and fNIRS can outperform EEG-only systems by exploiting complementary electroph
arXiv:2609.20844v1 Announce Type: new Abstract: Deepresearch (DR) agents interact with real-world web environments through multi-turn search and visit, causing their contexts to grow rapidly over time
arXiv:2609.22064v1 Announce Type: new Abstract: Advances in large-scale neural recording have made it possible to collect data across many animals and distributed brain regions, raising the question o
arXiv:2609.21422v1 Announce Type: cross Abstract: Deep representation learning often selects hidden features and fits the final predictor on the same sample, so fixed-feature analysis performed after
arXiv:2609.21619v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning models by learning the token-level discrepancy between a stronger teacher and an on-policy student. Howe
arXiv:2609.20981v1 Announce Type: new Abstract: Autoregressive (AR) models suffer from local greediness, while diffusion language models (DLMs) often lack the strict causal structure required for reas
arXiv:2609.21157v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly being explored for chip design, but most existing approaches operate directly at RTL. We ask whether
arXiv:2609.21982v1 Announce Type: new Abstract: Robot demonstration collection often produces imperfect or failed trajectories in addition to successful demonstrations. Existing methods typically expl
arXiv:2609.21793v1 Announce Type: cross Abstract: Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, b
arXiv:2506.07327v4 Announce Type: replace Abstract: Saliency methods are widely used to visualize which input features are deemed relevant to a model's prediction. However, their visual plausibility c
arXiv:2609.21022v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation by combining semantic knowledge from pretrained vision-lang
arXiv:2609.21887v1 Announce Type: new Abstract: The gold standard datasets for mapping connectomes are electron microscopy volumes of densely labeled neural tissue at nanometer resolution. Yet reconst
arXiv:2609.21344v1 Announce Type: cross Abstract: For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical access can attack the implementation directly,
arXiv:2609.21637v1 Announce Type: cross Abstract: Debate adjudication requires tracking how arguments develop through interaction, yet existing datasets rarely combine fine-grained debate transcripts
arXiv:2609.21872v1 Announce Type: new Abstract: We introduce Chronosphere, a spatio-temporal neural field that learns representations of climate. A central challenge in geographic representation learn
arXiv:2609.21722v1 Announce Type: cross Abstract: Chinese social media has generated a vast and continually evolving lexicon of internet buzzwords whose meanings are often non-literal and deeply roote
arXiv:2609.21686v1 Announce Type: cross Abstract: Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it diff
arXiv:2609.21570v1 Announce Type: cross Abstract: Renewable energy communities (RECs) coordinate buildings, photovoltaic generation, batteries, electric vehicles and flexible loads. Controller studies
arXiv:2609.21812v1 Announce Type: cross Abstract: Recent advances in diffusion models have enabled high-performance, instance-adaptive compressed sensing through posterior sampling, without task-speci
arXiv:2609.21149v1 Announce Type: new Abstract: Before patients can use AI-assisted psychiatric intake systems, health systems need practical ways to routinely evaluate these tools against their clini
arXiv:2609.21334v1 Announce Type: cross Abstract: Effective evaluation of zero-day jamming detectors requires robust adversarial models. However, existing attack models often assume prior knowledge of
arXiv:2603.12488v2 Announce Type: replace Abstract: In many robotic manipulation tasks, the robot repeatedly solves motion-planning problems that differ mainly in the location of the goal object and i
arXiv:2609.20842v1 Announce Type: new Abstract: Text-to-SQL translates natural-language questions into executable SQL queries, but open-source large language models still require task-specific post-tr
arXiv:2609.22068v1 Announce Type: new Abstract: Training capable coding agents via reinforcement learning (RL) requires diverse tasks with reliable verifiers. Open-source codebases offer a rich source
arXiv:2609.21259v1 Announce Type: new Abstract: Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increa
arXiv:2609.21154v1 Announce Type: new Abstract: Good tutoring adapts to the individual: it tracks what a learner knows, notices why they go wrong, and asks the next question that will help most. Most
arXiv:2508.03030v3 Announce Type: replace Abstract: Mixed-integer linear programming (MILP) has been a fundamental problem in combinatorial optimization. Conventional MILP solving mainly relies on car
arXiv:2609.21304v1 Announce Type: new Abstract: Reliable plant-level information from unmanned aerial vehicle (UAV) imagery is important for automated crop monitoring. However, in dense crop canopies,
arXiv:2609.21908v1 Announce Type: new Abstract: Although vision-language-action (VLA) policies have advanced rapidly, long-horizon execution may still progress to the next task stage before the requir
arXiv:2609.21787v1 Announce Type: new Abstract: Learned world models may have compact interventions even when their recurrent state is high-dimensional, but it is unclear what happens to such a correc
arXiv:2609.21455v1 Announce Type: new Abstract: While diffusion-based text-to-video (T2V) models have demonstrated impressive capability in generating realistic and temporally coherent videos, they of
arXiv:2609.21759v1 Announce Type: cross Abstract: We present the first complete machine learning method for accelerating plane-wave density functional theory (DFT) in materials under the projector aug
arXiv:2609.22012v1 Announce Type: new Abstract: Every multiparameter persistence vectorization we know of carries a one-sided Lipschitz upper bound and nothing below it: without a lower gauge there is
arXiv:2609.20973v1 Announce Type: cross Abstract: Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step
arXiv:2609.21651v1 Announce Type: cross Abstract: Farmer.Chat is Digital Green's farm advisory service for smallholder farmers. When something looks wrong with a crop, the farmer takes a photograph an
arXiv:2609.21340v1 Announce Type: cross Abstract: Empirical identity leakage from released text is increasingly driven by attackers that combine large language models (LLMs) with auxiliary knowledge t
arXiv:2609.21387v1 Announce Type: cross Abstract: Relexicalization is a pivotal technique in clinical NLP, as it facilitates robust masking of sensitive information while synthesizing datasets that re
arXiv:2605.06445v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents demonstrate strong performance in autonomous code generation under loose specifications. However, production
arXiv:2609.21046v1 Announce Type: new Abstract: Choreographed aquatic performances require small autonomous surface vehicles to track precise paths under per-thruster force and rate limits, including
arXiv:2609.21803v1 Announce Type: new Abstract: Contact-rich motion planning (CRMP) is essential for robotic manipulation and locomotion, yet remains computationally challenging due to combinatorial c
arXiv:2609.20906v1 Announce Type: new Abstract: Quasars are luminous objects in the universe that exhibit stochastic brightness variations encoding information about the supermassive black holes power
arXiv:2404.01897v3 Announce Type: replace-cross Abstract: Continuous graph neural networks (CGNNs) have garnered significant attention due to their ability to generalize existing discrete graph neural
arXiv:2601.21583v2 Announce Type: replace Abstract: Many learning problems require predicting sets of objects when the number of objects is not known beforehand. Examples include object detection, mol
arXiv:2609.21617v1 Announce Type: new Abstract: Self-play in high-throughput simulators yields driving policies with robust closed-loop performance, but improvement per unit of simulation diminishes a
arXiv:2609.21761v1 Announce Type: new Abstract: We present CRISP (Contact-RIch Simulation Platform), a high-fidelity physics engine tailored for complex multi-contact simulations such as tight-toleran
arXiv:2609.20875v1 Announce Type: cross Abstract: Parkinson's disease (PD) often manifests through speech impairments, facilitating accessible, non-invasive, and cost-effective severity assessment for
arXiv:2609.22081v1 Announce Type: new Abstract: Occupational accident narratives contain valuable information about work situations, unfavourable conditions, accident events, and their consequences. A
arXiv:2609.21347v1 Announce Type: new Abstract: Recent progress in 3D Gaussian Splatting (3DGS) has enabled dense visual SLAM with pinhole cameras, yet most pipelines are not designed for panoramic im