Knowledge catalogue
arXiv:2609.01765v1 Announce Type: new Abstract: Carbon markets put a price on emissions, yet that price remains hard to forecast. Work in this area clusters on the EU and Chinese schemes, compresses r
arXiv:2609.02830v1 Announce Type: new Abstract: LiDAR-based semantic segmentation is a core perception module for autonomous vehicles and mobile robots. Despite the strong performance of recent state-
arXiv:2510.06257v2 Announce Type: replace-cross Abstract: Quantum error correction (QEC) is essential for scalable quantum computing, yet decoding errors via conventional algorithms result in limited
arXiv:2609.02364v1 Announce Type: cross Abstract: Existing Human-Robot Interaction (HRI) literature has focused on identifying and structuring errors, failures, conflicts, and knowledge issues (called
arXiv:2609.02157v1 Announce Type: new Abstract: Physical reservoir computing (PRC) refers to the use of a physical dynamical system as a computational resource for tasks such as state estimation and c
arXiv:2609.02440v1 Announce Type: cross Abstract: Adversarially robust models often overfit to a specific attack budget, necessitating multiple specialized models for diverse and dynamic adversarial e
arXiv:2609.02861v1 Announce Type: cross Abstract: Autonomous robots powered by deep learning face a fundamental auditability challenge: when incidents occur, investigators cannot reconstruct why the s
arXiv:2609.02341v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) have shown strong potential in autonomous driving by leveraging multimodal pretraining for instruction following, v
arXiv:2609.02702v1 Announce Type: new Abstract: Transformers process information causally, but long-context reasoning may depend on task state discovered only later. We formalize this mismatch through
arXiv:2609.02006v1 Announce Type: cross Abstract: A compressed student has two shapes that need not agree: the weight it deploys at inference and the weight family its training can reach. We show that
arXiv:2609.02499v1 Announce Type: cross Abstract: Recommender-system experiments often rely on a single random training seed, assuming that run-to-run stochasticity has limited impact on evaluation co
arXiv:2609.02540v1 Announce Type: new Abstract: Diagnosing collective anomalies from urban trajectories is increasingly important for traffic governance, as it reveals what happened, who was involved,
arXiv:2609.02082v1 Announce Type: cross Abstract: Visual modality enhances the capabilities of multimodal large language models (MLLMs) but also introduces a safety concern: a benign textual query may
arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band
arXiv:2609.01731v1 Announce Type: new Abstract: Multi-Unmanned Aerial Vehicle (UAV) disaster-response systems require coordinated task assignment and local trajectory control, yet the individual and c
arXiv:2609.01738v1 Announce Type: new Abstract: Unexploded ordnance (UXO) continues to restrict civilian access, agricultural activity, infrastructure recovery, and environmental remediation in contam
arXiv:2609.02846v1 Announce Type: new Abstract: Stable 4-bit floating-point (FP4) pretraining is difficult because the E2M1 payload represents only a narrow range of magnitudes. NVIDIA's Transformer E
arXiv:2609.02476v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) captures and streams video while passing through a patient's Gastrointestinal (GI) tract and is used to examine its irr
arXiv:2609.02434v1 Announce Type: new Abstract: Restoring images degraded by adverse weather remains challenging due to spatially heterogeneous degradations. Many existing weather-specific restoration
arXiv:2609.02652v1 Announce Type: new Abstract: Leech-lattice vector quantization holds the strongest reported 2-bit quality under its own evaluation protocol. Its kernel decodes one shell; we found n
arXiv:2609.02134v1 Announce Type: new Abstract: Humanoid learning increasingly relies on transforming vast and diverse human motion data into high-quality robot reference trajectories. However, retarg
arXiv:2505.12912v2 Announce Type: replace Abstract: Pre-trained vision-language models, such as contrastive language-image pre-training (CLIP), have demonstrated a remarkable generalizability, enablin
arXiv:2609.02754v1 Announce Type: cross Abstract: Large language models now answer medical questions with expert-level performance. However, the context these systems act on can be misleading, and mis
arXiv:2609.02859v1 Announce Type: new Abstract: Harnessing naturally occurring feedback from user interactions offers a promising learning signal for Large Language Models (LLMs). However, recent stud
arXiv:2507.08468v2 Announce Type: replace Abstract: This paper provides an experimental evaluation of the capability of large language models (LLMs) to assist in legal decision-making within the frame
arXiv:2609.02421v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently demonstrated strong capabilities in automated travel itinerary generation. However, real- world travel planni
arXiv:2609.01788v1 Announce Type: cross Abstract: Real-world communication often requires pragmatic reasoning: interpreting meanings implied through context and cultural convention rather than stated
arXiv:2609.02776v1 Announce Type: new Abstract: Palm-vein biometrics are increasingly used for secure, contactless authentication. Yet real-world deployment exposes them to surface noise (sweat, dirt)
arXiv:2509.26604v2 Announce Type: replace Abstract: Existing multimodal audio generation models often lack precise user control, which limits their applicability in professional Foley workflows. In pa
arXiv:2609.01816v1 Announce Type: new Abstract: We introduce Video2Reaction, a multimodal dataset that maps short movie segments to the induced emotional reactions of viewers in the wild, as expressed
arXiv:2602.23771v2 Announce Type: replace-cross Abstract: Remote photoplethysmography (rPPG) enables contact free monitoring of vital signs and is especially valuable for neonates, since conventional
arXiv:2609.02462v1 Announce Type: new Abstract: End-to-end autonomous driving in urban environments requires robust decision-making under partial observability and complex multi-agent interactions. Se
arXiv:2609.02486v1 Announce Type: cross Abstract: Document Visual Question Answering (DocVQA) often leverages Retrieval-Augmented Generation (RAG), where late-interaction encoders are commonly used to
arXiv:2601.07795v2 Announce Type: replace Abstract: The European Space Agency (ESA), driven by its ambitions on planned lunar missions with the Argonaut lander, has a profound interest in reliable cra
arXiv:2609.02291v1 Announce Type: cross Abstract: Ultra-low bitrate video compression still faces critical challenges: traditional neural video compression inevitably introduces blurring artifacts, wh
arXiv:2512.05211v2 Announce Type: replace Abstract: Morphing aerial robots have the potential to transform autonomous flight, enabling navigation through cluttered environments, perching, and seamless
arXiv:2606.16600v2 Announce Type: replace Abstract: Expressive co-speech gestures are crucial for natural human--robot interaction, yet generating them on physical humanoid robots remains challenging
arXiv:2609.02177v1 Announce Type: cross Abstract: Multi-bit watermarking for large language models (LLMs) enables content source tracing by embedding user-identifiable messages into generated text. Ex
arXiv:2609.02322v1 Announce Type: cross Abstract: The first problem of modeling the world is not just estimating the right parameters or causal structure, but deciding what should be represented at al
arXiv:2607.17952v2 Announce Type: replace Abstract: Climate disclosure classification is a fundamental task for analysing corporate climate disclosures, yet such disclosures appear in many different s
arXiv:2609.01985v1 Announce Type: new Abstract: As LLM coding agents increasingly perform end-to-end engineering work, we lack empirical characterization of how they behave on systems-level requiremen
arXiv:2609.01741v1 Announce Type: new Abstract: Statutes are increasingly parsed by machines before people read them, and the parsers disagree: on Missouri's statutes, two independently written extrac
arXiv:2505.15276v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have achieved remarkable success on complex tasks, yet their tendency to 'overthink' leads to inefficiencies. Although
arXiv:2609.02438v1 Announce Type: new Abstract: Large language models can look capable of logical reasoning, but correct or incorrect answers alone tell us little about what the model represents inter
arXiv:2609.01814v1 Announce Type: new Abstract: Information sharing can improve a pooled estimate while eliminating independent rescue actions. This paper separates those effects in exact finite disco
arXiv:2608.27984v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) have recently moved from static workflows toward dynamically generated collaboration topologies. However, existing topolog
arXiv:2609.01621v1 Announce Type: cross Abstract: Artificial intelligence (AI) increasingly treats scientific literature as a data source for building databases, training predictive models, and guidin
arXiv:2609.02526v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to predict the responses of human participants in survey panels. Towards that goal, persona prompting
arXiv:2609.02000v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly evaluated on complex image and video understanding tasks, yet conventional metrics primarily assess final
arXiv:2609.01625v1 Announce Type: cross Abstract: Content moderation is a central form of digital governance, yet people disagree over what content should be removed from shared online spaces. While p
arXiv:2609.02452v1 Announce Type: new Abstract: Knowing where and how fast objects are moving within a scene is important across various domains. Usually, cameras are used to capture the data necessar
arXiv:2609.02413v1 Announce Type: cross Abstract: Multi-axis 3D printing enables support-free fabrication and improved part quality, but robustly processing real-world geometries remains challenging.
arXiv:2609.02651v1 Announce Type: new Abstract: While English language models have been widely examined for anti-queer bias, Dutch models remain understudied. To address this gap, we developed a cultu
arXiv:2609.01608v1 Announce Type: cross Abstract: Black-box optimization problems remain challenging because of large, weakly structured, and high-dimensional search spaces. Existing methods often suf
arXiv:2609.02159v1 Announce Type: new Abstract: World Action Models (WAMs) aim to control robots by stochastically generating visual futures and then decoding actions, but empirical observations indic
arXiv:2609.02542v1 Announce Type: new Abstract: Foothold-constrained terrain is characterized by sparse, discontinuous, or geometrically restricted feasible foot contacts, as encountered on stepping s
arXiv:2508.17635v2 Announce Type: replace Abstract: Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documen
arXiv:2609.02083v1 Announce Type: cross Abstract: Removing complete transformer layers preserves a standard serving architecture, but existing depth-compression methods can lose substantial quality, a
arXiv:2609.02318v1 Announce Type: new Abstract: Referring multi-object tracking (RMOT) aims to track every instance in a video that matches a given language expression. Despite the recent integration
arXiv:2609.02546v1 Announce Type: new Abstract: Zero-shot generalization to unseen embodiments is important for generalizable vision-language-action (VLA) models as robot hardware evolves and task-spe