Knowledge catalogue
arXiv:2602.14255v2 Announce Type: replace Abstract: Industrial robots are increasingly deployed in construction and manufacturing tasks, where the deployment of end-to-end visuomotor policies is chall
arXiv:2608.21818v1 Announce Type: new Abstract: Thin-walled truncated conical shells are widely used in aerospace, marine, offshore, and lightweight infrastructure systems due to their high strength-t
arXiv:2608.22338v1 Announce Type: new Abstract: Interactive PDF form fields are often absent from documents that visually resemble forms, leaving users unable to enter data without printing or externa
arXiv:2608.22606v1 Announce Type: new Abstract: Topology optimization, using both physic-based approaches and deep learning surrogates, serves as a cornerstone for generative design agents in cyber-ma
arXiv:2607.18429v2 Announce Type: replace-cross Abstract: Phishing emails remain one of the most persistent cybersecurity threats, and machine-learning classifiers are widely used to detect them. Most
arXiv:2608.21444v1 Announce Type: new Abstract: Multi-drone systems are increasingly positioned for safety-critical missions such as search and rescue (SAR) and critical infrastructure monitoring. Yet
arXiv:2603.12031v3 Announce Type: replace-cross Abstract: Cloud-native container orchestration requires resource schedulers capable of balancing infrastructure expenditure, fault resilience, and node
arXiv:2608.23078v1 Announce Type: new Abstract: Large language models increasingly operate over large collections of tools, functions, APIs, and specialized agents. As the candidate action space grows
arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b
arXiv:2608.22894v1 Announce Type: cross Abstract: Arabic harmful-language detection has received considerable attention, yet Arabic text detoxification remains underexplored. We introduce AraDetox, a
arXiv:2608.21712v1 Announce Type: new Abstract: Transformer-based models are widely used for clinical prediction from electronic health records (EHRs), yet their architectures still require substantia
arXiv:2505.23197v4 Announce Type: replace-cross Abstract: Path planning for autonomous robots faces a fundamental trade-off between path length and obstacle clearance. While existing algorithms typica
arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models
arXiv:2607.10358v2 Announce Type: replace-cross Abstract: Foundation models are increasingly used as image feature extractors for mammography, but their robustness under external domain shift remains
arXiv:2608.22753v1 Announce Type: new Abstract: Large language models (LLMs) excel at text understanding and generation, yet still struggle to reliably understand and apply externally provided procedu
arXiv:2608.21927v1 Announce Type: cross Abstract: Zero-cost proxies enable neural architecture search (NAS) to rank candidate networks from statistics computed at initialization, avoiding repeated tra
arXiv:2608.01033v2 Announce Type: replace-cross Abstract: Language models small enough to run on a handset, quantized to a few bits, are increasingly capable of acting on their user's behalf -- which
arXiv:2608.22376v1 Announce Type: new Abstract: Large language models generate tokens sequentially, but can they execute multiple tasks concurrently while forming each token? Broader attention allocat
arXiv:2607.15721v2 Announce Type: replace Abstract: Cardiometabolic diseases remain among the most persistent drivers of preventable morbidity because diabetes, hypertension, and cardiovascular diseas
ChatGPT Work can now use its computer and browser to sign in to websites on web and mobile, without ChatGPT ever seeing your username or password. That means you can ask it to: • Set up utilities for
arXiv:2608.23152v1 Announce Type: new Abstract: Counterspeech effectively neutralizes the impact of online hate. Although prior work explores automated counterspeech generation, it largely emphasizes
arXiv:2608.21784v1 Announce Type: new Abstract: Few-step text-to-image models increasingly replace slower generators, yet acceleration can silently change distributions over unspecified attributes eve
arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix gen
arXiv:2608.23525v1 Announce Type: new Abstract: Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards mak
arXiv:2607.16646v2 Announce Type: replace-cross Abstract: Large language models now translate natural-language descriptions of decision problems into solver-ready optimization models, and they fail si
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:2608.23070v1 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:2602.18422v2 Announce Type: replace Abstract: Extended reality (XR) demands generative models that respond to users' tracked real-world motion, yet current video world models accept only coarse
arXiv:2608.22229v1 Announce Type: new Abstract: Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment r
arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle
arXiv:2608.21928v1 Announce Type: new Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied s
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:2608.22192v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused.
arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.
arXiv:2608.22990v1 Announce Type: new Abstract: Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-languag
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:2608.22284v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in re
arXiv:2608.21867v1 Announce Type: new Abstract: LLM agents are moving from single-prompt use to long task streams in which reusable memory becomes a core capability for terminal, software-engineering,
arXiv:2509.19005v2 Announce Type: replace-cross Abstract: The Minimum Bisection Problem is a fundamental, computationally hard graph partitioning problem with applications in parallel computing, netwo
arXiv:2606.17978v2 Announce Type: replace Abstract: Trajectory similarity is a fundamental task in analyzing mobility patterns, essential for applications such as route pattern extraction, mobility pr
arXiv:2608.23373v1 Announce Type: new Abstract: Forecasting long-range influenza-like illness (ILI) matters for public health readiness. Publicly available surveillance datasets typically pair numeric
arXiv:2508.13533v2 Announce Type: replace Abstract: Within a model family, a smaller variant is often deployed as a drop-in replacement for a larger one when their performance is similar. However, per
arXiv:2608.21840v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures are commonly motivated as a way to increase expressivity by decomposing complex systems into simpler local dynami
arXiv:2608.22750v1 Announce Type: new Abstract: Object-centric world models forecast future videos by evolving a set of entity slots, but the variables receiving dynamics supervision are often unconst
arXiv:2608.22926v1 Announce Type: new Abstract: Gaze is increasingly used as an input signal for vision and multimodal models, yet no consensus exists on how to represent it across datasets. Raw trace
arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers
arXiv:2608.22637v1 Announce Type: new Abstract: Recent vision-language models (VLMs) show strong capabilities in robotic perception and spatial reasoning, yet their ability to reason about complex mec
arXiv:2608.22971v1 Announce Type: new Abstract: Embodied Reasoning constitutes a fundamental capability of embodied intelligence, serving as the basis for autonomous perception, reasoning, and interac
arXiv:2608.21381v1 Announce Type: cross Abstract: Personal intelligence is becoming a central frontier for user-facing AI agents. To be helpful in everyday life, agents must understand users across th
arXiv:2608.23086v1 Announce Type: new Abstract: Black-box large language models need confidence scores that can separate likely-correct from likely-incorrect outputs, enabling systems to prioritize hu
arXiv:2608.21543v1 Announce Type: cross Abstract: Object placement is critical in image composition, requiring spatially and semantically coherent positioning of objects within diverse scenes. Existin
arXiv:2608.22388v1 Announce Type: cross Abstract: Propaganda detection includes several related prediction levels, ranging from sentence-level decisions to technique classification and span identifica
arXiv:2608.22214v1 Announce Type: new Abstract: In domain-specific multimodal long documents, images and text jointly convey complex knowledge that cannot be fully captured by plain text alone. Howeve
arXiv:2608.21985v1 Announce Type: new Abstract: As the adoption of large language models (LLMs) grows in Arabic-speaking regions, ensuring their safety and cultural alignment is increasingly critical.
arXiv:2608.22849v1 Announce Type: new Abstract: Full-length RNAs, particularly messenger RNAs, often exceed the context lengths used to pretrain existing RNA foundation models, limiting complete-trans
arXiv:2608.22227v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved tremendous success in recent years. However, the classical foundations of RL do not account for the risk sensit
arXiv:2608.22419v1 Announce Type: cross Abstract: Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that
arXiv:2608.21398v1 Announce Type: cross Abstract: A trained reinforcement learning policy does not determine the complete behavior that users encounter: deployment code still schedules, admits, suppre
arXiv:2512.04529v3 Announce Type: replace Abstract: Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story t