Knowledge catalogue
arXiv:2609.17564v1 Announce Type: new Abstract: Deploying retrieval-augmented generation (RAG) on commodity GPUs such as the NVIDIA T4 (16 GB VRAM) exposes a practical failure mode we call the Compres
arXiv:2609.17535v1 Announce Type: new Abstract: Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Compa
arXiv:2606.19469v2 Announce Type: replace Abstract: Undergraduate computer science is governed by international curricular guidelines revised about once a decade, yet programs lack a reliable way to m
arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biom
arXiv:2609.14572v1 Announce Type: cross Abstract: Teaching abstract theoretical computer science (TCS) concepts such as algorithm analysis and complexity theory is challenging because students must ha
arXiv:2609.13253v1 Announce Type: cross Abstract: Multi-agent reinforcement learning in networked populations is governed by the interaction between individual adaptation, local encounters, and changi
arXiv:2609.12206v1 Announce Type: new Abstract: Bioprinting is emerging as a tissue engineering technique to replace common treatment methods for large scale injuries. While thickness of the BioPrinte
arXiv:2609.12173v1 Announce Type: new Abstract: Transportation agencies need pedestrian volume estimates across entire road networks to prioritize safety investments, yet manual counts are expensive a
arXiv:2609.12364v1 Announce Type: new Abstract: Latent embeddings have become a central data abstraction in modern machine learning, especially in biomedicine, where foundation models are increasingly
arXiv:2609.12366v1 Announce Type: new Abstract: We present ORQA, a method for testing occupation-level knowledge in large language models. Prior methods either map abstract LLM skills to occupations v
arXiv:2609.11527v1 Announce Type: new Abstract: Reliable, low-latency perception is crucial for Formula Student Driverless vehicles, yet many existing pipelines rely on deep learning and multi-sensor
arXiv:2609.11478v1 Announce Type: new Abstract: The development of autonomous driving demands comprehensive testing in mixed-traffic scenarios involving vulnerable road users (VRUs), where purely arti
arXiv:2609.10612v1 Announce Type: cross Abstract: Personalized learning systems rely on real learner data, including performance, behavior, and demographic information, but these data are highly priva
arXiv:2609.10831v1 Announce Type: cross Abstract: Longitudinal single cell atlases now capture matched pre treatment and post treatment states from responders and non responders, presenting an opportu
arXiv:2609.06708v1 Announce Type: cross Abstract: Large language models are transforming many industries with their text generation abilities. However, their outputs can be easily tampered with, creat
arXiv:2609.06831v1 Announce Type: new Abstract: AI systems are used worldwide, but they struggle to serve the needs of culturally diverse populations. Prior work on cultural understanding evaluates AI
arXiv:2509.14191v4 Announce Type: replace-cross Abstract: Recent progress in dense SLAM has primarily targeted monocular setups, often at the expense of robustness and geometric coverage. We present M
arXiv:2609.04603v1 Announce Type: new Abstract: Recent generative image-editing Diffusion Transformers (DiTs) demonstrate impressive semantic editing capabilities but still struggle with spatially con
arXiv:2609.04177v1 Announce Type: new Abstract: Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis.
arXiv:2609.03809v1 Announce Type: new Abstract: Energy consumption is one of the largest operational expenditure items for mobile network operators, yet site-level energy inefficiencies such as faulty
arXiv:2609.01673v1 Announce Type: cross Abstract: Activity-cliff ranking remains difficult because local structural changes can cause large activity differences, while high-quality data that resolve t
I’ve been running qwen on my personal Mac but I’m getting to the point where’d I’d like to have something always on, running various jobs, and some more ability to experiment and earn about fine tunin
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:2609.01369v1 Announce Type: new Abstract: Reliable evaluation of open-ended question answering remains a bottleneck for measuring answer correctness of modern LLMs. Unlike multiple-choice tasks,
arXiv:2609.00883v1 Announce Type: new Abstract: Phase retrieval in broadband coherent anti-Stokes Raman spectroscopy (BCARS) is an ill-posed inverse problem. The Raman-like signal is encoded in the im
arXiv:2608.30088v1 Announce Type: new Abstract: Accurate detection of tomato growth stages is essential for stage-specific greenhouse management and precision agriculture. In Bhutan, greenhouse cultiv
arXiv:2608.29210v1 Announce Type: new Abstract: Text-to-Image (T2I) models have recently achieved impressive visual fidelity, yet their evaluation remains constrained by benchmarks that are often diff
arXiv:2608.30451v1 Announce Type: new Abstract: Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect tempor
arXiv:2608.28339v1 Announce Type: new Abstract: Artificial intelligence can classify artistic styles and synthesize images, but it still lacks a model of the visual language that gives art meaning. Ab
arXiv:2608.28437v1 Announce Type: cross Abstract: Cloud robotics relies on the timely uplink of high-volume sensing streams, yet dynamic environments continually shift the feasible combinations of tra
arXiv:2606.14580v2 Announce Type: replace Abstract: Identifying persuasive rhetorical cues is critical across domains, from detecting information manipulation and improving AI safety to advancing publ
arXiv:2608.26618v1 Announce Type: cross Abstract: Model selection becomes particularly challenging under strong predictor dependence and model-class uncertainty, especially when there are exponentiall
arXiv:2608.26465v1 Announce Type: new Abstract: Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS
arXiv:2604.14586v4 Announce Type: replace-cross Abstract: The rapid expansion of gaming industry requires advanced recommender systems tailored to its dynamic landscape. Existing Graph Neural Network
arXiv:2608.26124v1 Announce Type: new Abstract: Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evol
arXiv:2608.26833v1 Announce Type: new Abstract: Modern AI has greatly expanded the capabilities of image processing. However, the ready availability of powerful models, public datasets, and benchmark
arXiv:2608.25135v1 Announce Type: new Abstract: This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically ne
arXiv:2601.07752v4 Announce Type: replace-cross Abstract: Estimating the Riesz representer is central to debiased machine learning, yet the generator and representer model determine which regression d
arXiv:2401.10337v5 Announce Type: replace-cross Abstract: Tactics, Techniques and Procedures (TTPs) represent sophisticated attack patterns in the cybersecurity domain, described encyclopedically in t
arXiv:2608.23835v1 Announce Type: new Abstract: Real-world decision-making in public health and social science can greatly benefit from predictive models, yet translating predictions into effective in
arXiv:2608.22672v1 Announce Type: new Abstract: Energy system operation contains a loop of work that automation has never taken over: posing the optimization problem the current cycle should solve, di
arXiv:2608.22817v1 Announce Type: new Abstract: Industrial technical reports contain high-value knowledge for maintenance, troubleshooting, and product engineering, but their heterogeneous structure (
arXiv:2608.22026v1 Announce Type: new Abstract: Accurate simulation of the long-time evolution of systems governed by partial differential equations (PDEs) is central to scientific computing. Among ex
arXiv:2608.22979v1 Announce Type: new Abstract: Deploying high-dimensional multimodal features in industrial recommender systems incurs substantial storage and latency overhead. Hard quantization is c
arXiv:2602.18699v2 Announce Type: replace-cross Abstract: Studies of semantic drift report heterogeneous signals, including embedding displacement, neighbor change, distributional divergence, and recu
arXiv:2608.22293v1 Announce Type: cross Abstract: Urban wildfire resilience depends on interactions among built form, vegetation condition, and extreme fire weather, yet city-scale risk models often o
arXiv:2608.19769v1 Announce Type: cross Abstract: Fast and accurate segmentation of Acute Ischemic Stroke (AIS) lesions is essential for stroke prognosis and treatment planning. Non-contrast CT (NCCT)
arXiv:2509.08022v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often
arXiv:2608.18903v1 Announce Type: new Abstract: This work evaluates surrogate-assisted optimization of a seven-parameter current-excited coil--core benchmark subject to geometric, manufacturing, and s
arXiv:2608.18672v1 Announce Type: cross Abstract: We present the orienteering problem with uncertain time-varying rewards (OP-UTVR), a novel variant of the orienteering problem (OP). While most existi
arXiv:2608.17923v1 Announce Type: new Abstract: Appendicitis is one of the most common abdominal emergencies worldwide and requires prompt diagnosis and treatment to prevent life-threatening condition
arXiv:2603.04061v2 Announce Type: replace-cross Abstract: Quantum measurements are the means by which we recover messages encoded into quantum states. They are at the forefront of quantum hypothesis t
arXiv:2603.26764v2 Announce Type: replace Abstract: Portable CT scanners may support earlier stroke assessment, but reduced photon counts introduce noise that affects image quality and may alter autom
arXiv:2608.18008v1 Announce Type: cross Abstract: Combining large language models with reinforcement learning is increasingly explored, yet the theoretical status of LLM-derived reward signals is ofte
arXiv:2602.17127v2 Announce Type: replace Abstract: Large language models increasingly serve as reasoning layers in multi-agent systems, where one provider's models may generate, judge, and summarize
arXiv:2608.15657v1 Announce Type: new Abstract: The rapid development and widespread application of artificial intelligence (AI) have sparked intense discussions on how to deploy responsible AI system
arXiv:2608.15780v1 Announce Type: cross Abstract: Stale recommendations are a pervasive challenge and a leading source of user complaints on large-scale content platforms. Items lose relevance through
arXiv:2608.16763v1 Announce Type: new Abstract: Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency,
arXiv:2608.14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, an
arXiv:2602.23459v2 Announce Type: replace Abstract: Psychiatric questionnaires are highly context sensitive and often only weakly predict subsequent symptom severity, which makes the prognostic relati