Knowledge catalogue
arXiv:2606.17904v2 Announce Type: replace Abstract: Language models increasingly serve as advisory systems in maintenance operations. To prevent hallucination, recent systems ground these models in pr
arXiv:2512.06582v2 Announce Type: replace-cross Abstract: End task accuracy alone cannot determine whether a memory mechanism preserves an acquired capability, exposes sample-specific stored informati
arXiv:2602.16469v2 Announce Type: replace Abstract: Machine-translated data is widely used in multilingual NLP, particularly where native text is scarce. However, translated text differs systematicall
arXiv:2608.22745v1 Announce Type: cross Abstract: Emotion Recognition in Conversation (ERC) requires models to identify subtle emotional cues that are often distributed across distant dialogue turns.
arXiv:2608.22368v1 Announce Type: new Abstract: While linear attention is a compelling mechanism for high-resolution object detection due to its reduced cost for global token mixing, converting the So
arXiv:2608.15934v1 Announce Type: cross Abstract: Different shape representations facilitate different computations. Surface representations, in particular meshes, are often used for modeling, whereas
arXiv:2511.05575v2 Announce Type: replace Abstract: Diffusion-based approaches have recently achieved strong results in face swapping, offering improved visual quality over traditional GAN-based metho
arXiv:2511.12836v2 Announce Type: replace-cross Abstract: Sampling from a target distribution induced by training data is central to Bayesian learning, with Stochastic Gradient Langevin Dynamics (SGLD
arXiv:2608.22824v1 Announce Type: new Abstract: Membership inference attacks expose whether individual records were used to train a model, yet existing attacks on diffusion models are largely heuristi
arXiv:2608.22819v1 Announce Type: new Abstract: Text-conditioned image-to-video (I2V) generation has advanced rapidly, yet generating videos with multiple subjects remains challenging. A model must si
arXiv:2608.22191v1 Announce Type: new Abstract: Software-engineering agents solve repository-level tasks through long, stochastic tool-use trajectories, and repeated attempts often find fixes missed b
arXiv:2608.22065v1 Announce Type: cross Abstract: Whether the slow solar wind originates from one coronal source or two distinct channels remains a central open question in heliophysics. Resolving thi
arXiv:2608.22085v1 Announce Type: new Abstract: Synthetic clinical data generation with large language models addresses the scarcity that limits cancer staging research, but oncology hallucinations ar
arXiv:2608.21364v1 Announce Type: cross Abstract: Both human and AI systems that process narrative or long-form content operate incrementally: input is received over time, and internal representations
arXiv:2608.23461v1 Announce Type: new Abstract: With rapid advancement over the last few years, many different methods are now widely used for classification. However, training these models requires s
arXiv:2608.01947v2 Announce Type: replace-cross Abstract: The ability to robustly maintain and update continuous variables is a hallmark of working memory. While classical continuous attractor network
arXiv:2608.21448v1 Announce Type: cross Abstract: DNA methylation provides a stable record of cellular identity, capturing epigenetic programs that distinguish specialized cell states despite a shared
arXiv:2608.21827v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to und
arXiv:2608.22638v1 Announce Type: cross Abstract: Copying a function from a chat window into an editor takes less than a second. For many uses of AI coding tools, that speed is the point; in settings
arXiv:2608.22908v1 Announce Type: cross Abstract: Spoken Language Models (SLMs) generate textual responses directly from speech, offering an alternative to cascaded systems. Despite recent advances, e
arXiv:2608.22968v1 Announce Type: new Abstract: Industrial monitoring models must detect operationally relevant deviations while satisfying target-specific data, calibration, and resource constraints.
arXiv:2608.22316v1 Announce Type: cross Abstract: Whether an intermediate stage of modern Arabic handwriting helps or hurts historical Arabic HTR is usually decided from one implementation and one com
arXiv:2608.22697v1 Announce Type: new Abstract: Search rankings are valuable because human attention is scarce and sequential. Higher-placed alternatives are easier to find, so they are examined and b
arXiv:2608.22411v1 Announce Type: new Abstract: Social interaction increasingly takes place in multicultural settings, where individuals may draw on multiple cultural influences and adapt their commun
arXiv:2608.22761v1 Announce Type: cross Abstract: Large Language Models generate text autoregressively, but open-ended generation is prone to verbatim looping, in which models repeat spans already pre
arXiv:2608.22885v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) aims to generate a pixel-level mask for the object specified by a language expression. Recent methods based on m
arXiv:2510.14383v4 Announce Type: replace Abstract: Accurate brain tumor segmentation is significant for clinical diagnosis and treatment but remains challenging due to tumor heterogeneity. Mamba-base
arXiv:2608.22278v1 Announce Type: new Abstract: Vision-based whole-body loco-manipulation on humanoid robots is challenging due to partial observability, contact-rich dynamics, and the difficulty of l
arXiv:2608.23268v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-lev
arXiv:2608.22215v1 Announce Type: new Abstract: Large language model (LLM) agents operate in dynamic environments where knowledge continuously evolves. Existing memory systems typically treat external
arXiv:2608.22399v1 Announce Type: new Abstract: Conversational speech emotion recognition must reconcile acoustic evidence across temporal scales with two interaction processes: cross-speaker contextu
arXiv:2409.19616v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have proven effective in various medical imaging applications, such as automated disease diagnosis. However, due to the
arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza
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:2608.23284v1 Announce Type: new Abstract: Dynamic Embedded Topic Models (D-ETM) provide an interpretable framework for modeling temporal semantic evolution, but cross-corpus comparison remains d
arXiv:2603.16459v2 Announce Type: replace Abstract: Diffusion large language models (D-LLMs) have emerged as a promising alternative to auto-regressive models due to their iterative refinement capabil
arXiv:2608.21998v1 Announce Type: new Abstract: Regional climate risk assessment is critical for applications such as infrastructure design, disaster forecasting, and insurance resource allocation. Ho
arXiv:2608.23253v1 Announce Type: cross Abstract: Vision-language models typically encode an image into hundreds of visual tokens, incurring substantial inference latency and GPU memory overhead. Exis
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:2608.21755v1 Announce Type: new Abstract: Long-horizon agents need memory that identifies relevant experience, resolves revisions, and exposes checkable provenance. We present ECHO (Embodied Con
arXiv:2608.23189v1 Announce Type: new Abstract: We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, e
arXiv:2608.21946v1 Announce Type: cross Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable expl
arXiv:2608.21424v1 Announce Type: new Abstract: Interactive video generation and editing are becoming increasingly important for creative design. In this report, we introduce EditStream: a unified fra
arXiv:2505.24255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for com
arXiv:2608.22201v1 Announce Type: cross Abstract: We introduce a new class of regression models for scan statistics on real-valued signals. These allow for improved fitting of non-stationary signals t
arXiv:2608.23563v1 Announce Type: cross Abstract: Road traffic injuries remain a major challenge in low- and middle-income countries, where proactive road safety auditing is limited by incomplete cras
arXiv:2608.22721v1 Announce Type: cross Abstract: Machine-learning malware detectors often achieve high clean-data accuracy, but operational triage also requires evidence about uncertainty, novelty, r
arXiv:2608.21697v1 Announce Type: new Abstract: Generating expressive facial behavior in virtual humans (VHs) remains a central challenge in affective computing and character animation. This paper pre
arXiv:2608.22449v1 Announce Type: cross Abstract: Forecasting dexterous hand motions from egocentric observations is fundamental to intelligent interactive systems. Existing VLM-based methods typicall
arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution su
arXiv:2608.22093v1 Announce Type: new Abstract: Minimally invasive procedures performed within confined anatomical spaces depend on continuous endoscopic visualization. Current robotic endoscope syste
arXiv:2608.21463v1 Announce Type: new Abstract: The study employed an Artificial Neural Network in combination with the optimized Adaptive Moment Estimation (Adam) algorithm, currently the only AQI fo
arXiv:2608.22629v1 Announce Type: new Abstract: Transferring reinforcement learning policies from simulation to Real-World robots remains a major challenge, particularly when dealing with low-level to
arXiv:2608.22695v1 Announce Type: cross Abstract: Agent ecosystems now include thousands of MATS components (Models, Agents, Tools, and Skills), yet their discovery still relies on in-context routing.
arXiv:2608.21913v1 Announce Type: new Abstract: Completing dental records from cone-beam computed tomography (CBCT) is difficult when annotation is scarce and individual clinical fields are supported
arXiv:2508.02609v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNN) have been extensively applied to industry recommendation systems, as seen in models like GraphSageite{GraphSage},
arXiv:2509.11250v3 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) agents are increasingly deployed to interact with online web services, yet their exposure to open-world content
arXiv:2608.21925v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. Howe
arXiv:2608.21420v1 Announce Type: new Abstract: Thematic analysis (TA) has long been regarded as an inherently human, reflexive, and interpretive process. However, the extent to which LLM-generated TA
arXiv:2608.22652v1 Announce Type: cross Abstract: LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into