Knowledge catalogue
arXiv:2608.22963v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed as multi-step agents, where explicit reasoning supports task decomposition and tool c
arXiv:2608.22760v1 Announce Type: new Abstract: Byte-space Action Recognition (BAR) aims to recognize human actions directly from compressed image bitstreams without any pixel decoding. By operating e
arXiv:2608.21937v1 Announce Type: new Abstract: Incremental Object Detection (IOD) aims to enable detectors to continuously learn novel categories while preserving previously acquired knowledge. Howev
arXiv:2608.23336v1 Announce Type: new Abstract: Developing competitive deep learning baselines for medical imaging remains a highly iterative process requiring literature review, implementation, exper
arXiv:2608.22780v1 Announce Type: new Abstract: Reinforcement learning (RL) enables direct preference optimization for image editing through editing-specific rewards, which remain less developed due t
arXiv:2607.15721v2 Announce Type: replace Abstract: Cardiometabolic diseases remain among the most persistent drivers of preventable morbidity because diabetes, hypertension, and cardiovascular diseas
arXiv:2608.23172v1 Announce Type: new Abstract: Large-scale vision-language models (VLMs) have demonstrated remarkable versatility across a wide range of multimodal tasks. However, understanding humor
arXiv:2502.03696v2 Announce Type: replace-cross Abstract: Recent studies have demonstrated that learned Bloom filters (LBFs), which combine machine learning with the classical Bloom filter, can achiev
arXiv:2608.22899v1 Announce Type: new Abstract: Unlike static medical question answering, long-horizon diagnosis captures the sequential nature of clinical practice: evidence is progressively acquired
arXiv:2608.21860v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has significantly enhanced the multi-step problem-solving capabilities of large language models (LLMs) by introducing
arXiv:2608.23429v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have shown strong performance in high-fidelity image generation, but their sampling process remains computationally inte
arXiv:2608.21504v1 Announce Type: new Abstract: The rapid advancement of large language models (LLMs) has led to increasing interest in their application to scientific domains such as chemistry. Howev
arXiv:2608.21899v1 Announce Type: new Abstract: Human-in-the-loop real-world reinforcement learning enables rapid acquisition of effective robotic manipulation policies for individual tasks, often wit
arXiv:2608.22281v1 Announce Type: cross Abstract: Medical image segmentation requires high accuracy and robustness, yet practical commercial deployment also demands privacy preservation and computatio
arXiv:2608.22483v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly support decision-making in high-stakes domains, but they often hallucinate and express confidence that is misa
arXiv:2608.22583v1 Announce Type: cross Abstract: Clinical records contain rich evidence about patient state, but converting that evidence into reliable, structured knowledge graphs remains difficult
arXiv:2608.22003v1 Announce Type: new Abstract: Data-Free Knowledge Distillation (DFKD) preserves privacy by transferring knowledge without real data access. However, existing generator-based DFKD met
arXiv:2608.21976v1 Announce Type: new Abstract: Agentic AI has automated parts of scientific discovery, including paper generation, expert-level coding, therapeutic proposal, and autonomous experiment
arXiv:2608.22762v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) is a key task for evaluating KG-augmented Large Language Models (LLMs), and complex KGQA that requires multi-h
arXiv:2608.23153v1 Announce Type: new Abstract: In high-stakes healthcare applications, machine learning models are frequently trained on data from one patient population and deployed on another, crea
arXiv:2608.21485v1 Announce Type: new Abstract: Physical Cell Identity (PCI) assignment is essential for interference management in dense 5G networks. As cellular networks scale, PCI reuse becomes una
arXiv:2608.22533v1 Announce Type: new Abstract: Autonomous computer-use agents are increasingly applied to long-horizon tasks requiring coordinated application calls, persistent state tracking, and ve
arXiv:2608.23551v1 Announce Type: cross Abstract: Recent advances in continuous diffusion and flow-based language models (LMs) have achieved performance competitive with discrete LMs. However, existin
arXiv:2509.12811v2 Announce Type: replace Abstract: Large Language Models (LLMs) have shown remarkable prowess in text generation, yet producing long-form, factual documents grounded in extensive exte
arXiv:2608.23164v1 Announce Type: cross Abstract: Counterfactual (CF) explanations for time-series classifiers are usually evaluated one example at a time: what minimal edit flips this single window's
arXiv:2608.23390v1 Announce Type: cross Abstract: English Wikipedia is often treated as the default encyclopedic source, yet non-English Wikipedia editions can contain richer locally grounded informat
arXiv:2608.22074v1 Announce Type: cross Abstract: Identifying atomic defects at elevated temperature is difficult because thermal fluctuations blur the local symmetry that both geometric heuristics an
arXiv:2608.22059v1 Announce Type: cross Abstract: Pretrained image encoders are central to medical image classification, where expert annotation is costly and task-specific cohorts are often limited.
arXiv:2608.22115v1 Announce Type: new Abstract: Collaborative multimodal inference improves edge perception by combining observations from distributed sensing devices, but transmitting high-dimensiona
arXiv:2608.22983v1 Announce Type: new Abstract: Robot manipulators are commonly engineered around a decoupled motion-generation stack: a planner computes a collision-free path and a lower-level contro
arXiv:2608.23181v1 Announce Type: cross Abstract: As large language models (LLMs) continue to advance in coding capabilities, their potential in cybersecurity has drawn increasing research attention,
arXiv:2608.22277v1 Announce Type: new Abstract: Deep learning surrogates for forecasting chaotic dynamical systems suffer from catastrophic error accumulation over long-term autoregressive rollouts. T
arXiv:2608.22289v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) increasingly require robust visual localization in GNSS-denied environments. A common solution estimates UAV poses by ma
arXiv:2608.22126v1 Announce Type: cross Abstract: Physics reasoning requires constructing a consistent model of the underlying physical system rather than relying solely on symbolic or formula-based m
arXiv:2503.14900v2 Announce Type: replace-cross Abstract: The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual d
arXiv:2608.22615v1 Announce Type: new Abstract: Large Language Model (LLM)-based counseling agents can generate fluent and supportive responses, but they often lack the structured, goal-directed progr
arXiv:2608.21438v1 Announce Type: new Abstract: Text guided 3D scene editing provides an intuitive interface for modifying reconstructed environments, but remains difficult because natural language de
arXiv:2608.23363v1 Announce Type: cross Abstract: Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepf
arXiv:2608.22806v1 Announce Type: new Abstract: Iterative preference optimization is essential for aligning Large Language Models on mathematical reasoning tasks, yet its efficiency is often throttled
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:2608.22908v1 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:2608.22761v1 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: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:2608.22014v1 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: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:2608.21946v1 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:2608.23563v1 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:2608.22449v1 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:2608.21913v1 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:2608.21559v1 Announce Type: new Abstract: Multi-stage LLM pipelines can remain structurally valid even when evidence available to downstream stages becomes incomplete, compressed, or conflicting
arXiv:2608.22559v1 Announce Type: new Abstract: Rubrics aim to make language-model evaluation transparent by decomposing response quality into interpretable criteria. However, natural-language rubrics
arXiv:2409.16183v2 Announce Type: replace Abstract: Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in me