Knowledge catalogue
arXiv:2605.23332v1 Announce Type: new Abstract: The integration of large language models into political discourse analysis creates new opportunities for comparative research, policy analysis, and civi
arXiv:2605.23797v1 Announce Type: cross Abstract: Aiming at identifying unexpected inputs from unknown classes, out-of-distribution (OOD) detection has emerged as a pivotal approach to enhancing the r
arXiv:2605.23355v1 Announce Type: new Abstract: Temporal Action Localization (TAL) has been extensively studied in generic video understanding, while fine-grained sports scenarios, such as professiona
arXiv:2511.10404v2 Announce Type: replace Abstract: In spite of the remarkable advancements in the field of Natural Language Processing, the task of Entity Linking (EL) remains challenging in the fiel
arXiv:2605.23281v1 Announce Type: new Abstract: Monocular metric depth estimation has achieved strong progress with large-scale training and universal-camera modeling, yet robust deployment across div
arXiv:2605.23262v1 Announce Type: new Abstract: The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowl
arXiv:2605.23445v1 Announce Type: new Abstract: Diffusion transformers have achieved remarkable success in high-quality video generation, yet their reliance on spatiotemporal 3D full attention incurs
arXiv:2602.17653v2 Announce Type: replace Abstract: Recent work has shown that language models (LMs) trained on synthetic corpora can exhibit typological preferences that resemble cross-linguistic reg
arXiv:2605.23762v1 Announce Type: new Abstract: Imitation Learning from monocular video demonstrations provides a scalable approach for teaching complex skills to humanoid robots. However, translating
arXiv:2605.23493v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has gained wide attraction as an LLM post-training paradigm due to its effectiveness in improving capabilities without intr
arXiv:2605.23096v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) enables private inference by evaluating neural networks on encrypted data. In this way, we can delegate the computa
arXiv:2605.23412v1 Announce Type: new Abstract: While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for indivi
arXiv:2603.19167v2 Announce Type: replace Abstract: We evaluate Large Language Models (LLMs) in repeated game-theoretic settings to assess whether strategic performance reflects genuine reasoning or r
arXiv:2508.07849v2 Announce Type: replace Abstract: Despite advances in legal NLP, no comprehensive evaluation of Transformer-based models customized for legal tasks (referred to as `legal-specific' m
arXiv:2605.23790v1 Announce Type: new Abstract: Saliency prediction has been extensively studied in RGB images and videos as a computational model of human visual attention. In contrast, predicting sa
arXiv:2605.23218v1 Announce Type: new Abstract: Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly
arXiv:2506.14135v5 Announce Type: replace-cross Abstract: Accurate scene perception is critical for vision-based robotic manipulation. Existing approaches typically follow either a Vision-to-Action (V
arXiv:2602.00979v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed as educational agents for automatic short answer grading (ASAG) in real-world education
arXiv:2605.23572v1 Announce Type: cross Abstract: In the competitive landscape of sponsored search, balancing retrieval quality with production latency is a critical challenge. While large retrieval m
arXiv:2605.23043v1 Announce Type: new Abstract: Agentic text-simulation systems write in sequence, with each item becoming possible context for later steps. That makes uncertainty path-dependent: an e
arXiv:2605.22940v1 Announce Type: cross Abstract: Deep learning is increasingly viewed as a dynamical process in parameter space, yet many existing theories still treat training as a closed optimizati
arXiv:2605.23109v1 Announce Type: new Abstract: AI agents increasingly excel at generating, testing, and refining code. However, they fall short on tasks requiring formal guarantees of full coverage t
arXiv:2605.23847v1 Announce Type: new Abstract: Large behaviour models have transformed the field of robotic manipulation, but prohibitive data requirements have thus far prevented a revolution simila
arXiv:2605.22892v1 Announce Type: cross Abstract: Modelling claim frequency and severity for non-life insurance pricing predominantly relies on generalised linear models, with gradient-boosted machine
arXiv:2605.22857v1 Announce Type: cross Abstract: High-resolution range profile (HRRP)-based radar automatic target recognition suffers from severe performance degradation in composite jamming environ
arXiv:2605.22825v1 Announce Type: cross Abstract: Key Value Indicators (KVIs) provide a decision oriented view of a service by summarizing how operational performance translates into stakeholder value
arXiv:2603.18551v2 Announce Type: replace-cross Abstract: We study how to construct compressed datasets that suffice to recover optimal decisions in linear programs with an unknown cost vector c lying
arXiv:2605.23470v1 Announce Type: cross Abstract: Predicting how a dynamical unit evolves over time - how an individual ages, an epidemic spreads, or a physical system degrades - typically requires de
arXiv:2605.23643v1 Announce Type: cross Abstract: Tools like Tamarin and ProVerif have achieved notable success in analyzing and verifying complex real-world protocols such as EMV, 5G, and WPA2, even
arXiv:2601.18685v3 Announce Type: replace-cross Abstract: The capabilities of generative AI in mathematics education are rapidly evolving, posing significant challenges for research to keep pace. Rese
arXiv:2605.22976v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software systems for diverse purposes, due to their versatility, flexibility, and abilit
arXiv:2505.17015v2 Announce Type: replace-cross Abstract: Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single ima
arXiv:2605.22850v1 Announce Type: cross Abstract: Prefix KV caching has become a key mechanism in LLM serving: it reduces time to first token (TTFT) by avoiding redundant computation across requests t
arXiv:2605.23409v1 Announce Type: cross Abstract: In human computer interaction, real-time detection and classification of dynamic hand gestures is challenging as: 1) the system must run in a real-tim
arXiv:2605.23297v1 Announce Type: new Abstract: AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, a
arXiv:2605.23037v1 Announce Type: new Abstract: Data-driven modeling is becoming central to multiphase transport, electronics cooling, acoustic diagnostics, and thermal-fluid digital twins, but progre
arXiv:2605.23657v1 Announce Type: new Abstract: Skills, i.e., structured workflow instructions distilled for large language models (LLMs), are becoming an increasingly important mechanism for improvin
arXiv:2605.23066v1 Announce Type: cross Abstract: In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves i
arXiv:2605.23074v1 Announce Type: new Abstract: The emergence of Large Reasoning Language Models (LRMs) has paved the way for tackling complex reasoning tasks through test-time scaling by generating l
arXiv:2605.23478v1 Announce Type: cross Abstract: Accurate crop yield prediction is crucial for sustainable agriculture and global food security. While existing methods are predominantly developed for
arXiv:2502.07489v2 Announce Type: replace Abstract: State-of-the-art methods for forecasting irregularly sampled time series with missing values predominantly rely on just four datasets and a few smal
arXiv:2605.23027v1 Announce Type: new Abstract: Recent research has demonstrated the potential of reinforcement learning in effective multi-robot collaboration, particularly in social dilemmas where r
arXiv:2603.21437v2 Announce Type: replace Abstract: Transformer-based embedding models frequently exhibit geometric pathologies, such as anisotropy and length-induced representation collapse, which ca
arXiv:2605.22855v1 Announce Type: cross Abstract: Personalized pricing negotiations are a challenging testbed for LLM agents because successful interaction does not guarantee profitable decision makin
arXiv:2605.23673v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have become important machine learning tools for graph analysis, and its explainability is crucial for safety, fairness, an
arXiv:2605.22886v1 Announce Type: cross Abstract: AI-native wireless receivers based on deep learning exhibit remarkable performance under stationary channel conditions, yet their resilience to distri
arXiv:2605.23747v1 Announce Type: new Abstract: Material segmentation, the pixel-wise classification of physical surface properties, remains a challenging problem in computer vision, requiring physico
arXiv:2605.23115v1 Announce Type: new Abstract: Bike-sharing models trained on historical station-hour data may degrade when deployed in later years because travel patterns change over time. This pape
arXiv:2403.12401v2 Announce Type: replace Abstract: Neural Representations for Videos(NeRV) have emerged as a promising paradigm for video compression by representing videos as compact neural networks
arXiv:2605.23194v1 Announce Type: cross Abstract: Fast and reliable optimal power flow (OPF) approximation is essential for reliable smart-grid operation, yet many learning-based surrogates either fla
arXiv:2605.22997v1 Announce Type: new Abstract: In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource for perception tasks such as 3D object detection.
arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen
arXiv:2605.23091v1 Announce Type: cross Abstract: The majority of software developers use or are planning to use Artificial Intelligence (AI) tools in their development processes. Their top reasons in
arXiv:2602.15258v2 Announce Type: replace Abstract: Remote Operation is touted as being key to the rapid deployment of automated vehicles. Streaming imagery to control connected vehicles remotely curr
arXiv:2605.23440v1 Announce Type: cross Abstract: Joint Entity and Relation Extraction (JERE) is highly susceptible to weak generalization due to low-quality training data. Data augmentation is a comm
arXiv:2605.23040v1 Announce Type: new Abstract: Latent steering exploits internal representations of Large Language Models (LLMs) to guide generation, yet interventions on dense states can entangle di
arXiv:2605.23597v1 Announce Type: new Abstract: Matching person names across heterogeneous records is a core challenge in entity resolution, especially within linguistically and culturally complex env
arXiv:2605.22840v1 Announce Type: cross Abstract: How much thinking can a civilisation do? Kardashev's (1964) typology ranks civilisations by total power: planetary (Type I, ~10^16 W), stellar (Type I
arXiv:2605.23071v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on long-context processing, but expanding context windows introduces substantial computational and financ
// The Efficiency Frontier in LLMs // (bookmark this one) How much are you overpaying for context you do not need? It turns out that context costs dominate production LLM bills, and the right strategy