Knowledge catalogue
arXiv:2603.18480v2 Announce Type: replace-cross Abstract: Inferring human engagement from gameplay video is important for game design and player-experience research, yet it remains unclear whether vis
arXiv:2610.01955v1 Announce Type: new Abstract: Outcome-based reinforcement learning can train language models to forecast real-world events, but prior forecasting work either freezes research context
arXiv:2610.01133v1 Announce Type: cross Abstract: Scaling reasoning typically spends more compute on reinforcement learning (RL) or on inference. We show that a completed RL training history can yield
arXiv:2610.00030v1 Announce Type: new Abstract: Object detection models often experience performance degradation when deployed under distribution shifts, caused by for example changes in weather type,
arXiv:2610.00040v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have enabled open-vocabulary and referring segmentation by distilling semantic knowledge from 2D foundation mod
arXiv:2601.22153v2 Announce Type: replace-cross Abstract: Manipulating dynamic objects remains an open challenge for Vision-Language-Action (VLA) models. Although recent VLAs generalize well in static
arXiv:2610.00801v1 Announce Type: new Abstract: A robot may lose sight of an object it must later retrieve, need to recall what a person demonstrated earlier, or track which steps of a task it has alr
arXiv:2610.01219v1 Announce Type: new Abstract: Simulation-to-robot transfer can fail when velocity commands produce motion and feedback that differ from those modeled during policy training. We prese
arXiv:2610.00568v1 Announce Type: cross Abstract: Large language models are characterized by three key properties: capability, alignment, and faithfulness. Prior work studies the tradeoffs between cap
arXiv:2610.00607v1 Announce Type: cross Abstract: Historical music restoration (HMR) has almost exclusively focused on constrained problems such as Super-Resolution or the restoration of solo pieces,
arXiv:2610.01746v1 Announce Type: cross Abstract: Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offe
arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co
arXiv:2610.00791v1 Announce Type: new Abstract: Enterprise information is represented through artifacts shaped by applications, projects, technologies, organizational boundaries, and local requirement
arXiv:2610.00212v1 Announce Type: new Abstract: Public-service recommendations require evidence that matches the requested service, scope, and date. Yet treating every missing detail as decisive can w
arXiv:2610.00383v1 Announce Type: new Abstract: Modern text-to-image (T2I) systems can be improved without modifying generator parameters by adapting the external system around frozen generators. Howe
arXiv:2601.06701v2 Announce Type: replace-cross Abstract: Complex AI systems make better predictions but often lack transparency, limiting trustworthiness, interpretability, and safe deployment. Commo
arXiv:2610.00610v1 Announce Type: cross Abstract: Explainable suicide-risk assessment requires models not only to estimate risk severity, but also to identify supporting language and the risk and prot
arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and car
arXiv:2610.00385v1 Announce Type: cross Abstract: Replay selectors often rank cached trajectories by format feedback, confidence, freshness, or response length, although cache-level correctness and do
arXiv:2603.08961v2 Announce Type: replace Abstract: Maintaining balance under external hand forces is critical for humanoid bimanual manipulation, where interaction forces propagate through the kinema
arXiv:2610.02144v1 Announce Type: new Abstract: We introduce Faynt, a family of 10M- and 75M-parameter Transformer policies for Super Smash Bros. Melee, each controlling all 26 characters with a singl
arXiv:2610.01510v1 Announce Type: new Abstract: Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, locati
arXiv:2610.01620v1 Announce Type: new Abstract: Federated training of foundation models is constrained by client memory and communication costs. LoRA-based methods reduce these costs through low-rank
arXiv:2610.01262v1 Announce Type: new Abstract: Timely and specific feedback is one of the strongest influences on student learning, yet it is difficult to sustain in large electrical engineering clas
arXiv:2610.01739v1 Announce Type: new Abstract: Sampling from discrete, unnormalized distributions without access to data is a challenging problem. Neural samplers offer a promising approach by traini
arXiv:2610.00858v1 Announce Type: new Abstract: Background and Objective: Clinicians expect recurrence risk to climb with cancer severity. In a UK multicentre trial, an unconstrained XGBoost model lea
arXiv:2610.01192v1 Announce Type: new Abstract: Streaming vision-language models must process continuously growing video streams under a bounded compute budget, creating a persistent tension between r
arXiv:2610.00053v1 Announce Type: new Abstract: Four-bit floating-point (FP4) Tensor Cores accelerate matrix multiplication, but scale computation, operand packing, layout construction, and saved back
arXiv:2506.11030v2 Announce Type: replace-cross Abstract: Training neural networks has traditionally relied on backpropagation (BP), a gradient-based algorithm that, despite its widespread success, su
arXiv:2610.01872v1 Announce Type: cross Abstract: While the literature on blockchain-assisted intrusion detection and prevention systems (IDS/IPS) for Internet of Things (IoT) and Industrial Internet
arXiv:2610.00580v1 Announce Type: new Abstract: In collaborative foundation model fine-tuning, client data is rarely homogeneous. Instead, clients typically possess unknown mixtures of distinct data d
arXiv:2610.01729v1 Announce Type: new Abstract: Algorithmic mathematical reasoning requires reliable decomposition, computation, and aggregation. Final-answer rewards provide limited guidance on inter
arXiv:2607.16956v2 Announce Type: replace Abstract: Social navigation requires the robot to reason and respond in complex real-world environments. While recent works attempt to incorporate human-level
arXiv:2610.00978v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of nor
arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr
arXiv:2610.00576v1 Announce Type: new Abstract: In this paper, we propose Gestalt, a new paradigm of large multimodal model built around multimodal interplay. Despite rapid advances, large multimodal
arXiv:2610.01023v1 Announce Type: cross Abstract: Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries
arXiv:2610.01128v1 Announce Type: new Abstract: Large language models can produce economic policy responses that sound reasonable, but this does not show that their actions are consistent with economi
arXiv:2610.00948v1 Announce Type: cross Abstract: The executable harness surrounding a GUI model determines how observations are assembled, actions are executed, and verification, recovery, and termin
arXiv:2610.00984v1 Announce Type: new Abstract: Accurate medication recommendation is central to clinical decision-making, directly determining therapeutic efficacy and patient safety. However, existi
Wen Shao / Fortune: Halluminate, which builds AI training environments for complex financial workflows, raised a 30M Series A led by Oak HC/FT, taking its total funding to 38.5M — Halluminate, a nine-
arXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off
arXiv:2610.00026v1 Announce Type: cross Abstract: Private domain speech is difficult to collect and redistribute, while compact models need task-specific supervision. We study an auditable synthetic p
arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo
arXiv:2610.00435v1 Announce Type: cross Abstract: We study how AI agents discover and validate scientific formulas using a controlled case study of the hydrotope, a recently discovered geometric formu
arXiv:2610.00921v1 Announce Type: new Abstract: The cross-entropy method (CEM) uses world-model scores to select action sequences and fit the distribution sampled in its next iteration. A scoring erro
arXiv:2606.19138v2 Announce Type: replace Abstract: Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based e
arXiv:2610.00355v1 Announce Type: new Abstract: Efficient indoor LiDAR perception is challenging because mobile robots must understand cluttered three-dimensional environments under strict latency and
Hi all! I am a former SWE who has recently transitioned into inference engineering. I launched a side hustle a few months back and I've just taken it full time due to excessive demand. Its been such a
arXiv:2610.00035v1 Announce Type: new Abstract: Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningf
arXiv:2610.00391v1 Announce Type: cross Abstract: Synthetic medical tabular data generation has become essential for developing and validating computer-based medical systems (CBMSs) when real clinical
arXiv:2610.01674v1 Announce Type: new Abstract: Building datasets remains one of the most manual and brittle parts of AI development. In this technical report, we focus on the most extreme but also mo
arXiv:2610.01269v1 Announce Type: new Abstract: Bayesian Optimisation (BO) is a powerful framework for the optimisation of expensive black-box functions, but typically requires refitting a surrogate a
arXiv:2610.01026v1 Announce Type: cross Abstract: Tackling complex real-world tasks can exceed the capabilities of a single large language model (LLM), motivating the use of multi-agent workflows that
arXiv:2510.15125v3 Announce Type: replace-cross Abstract: Social media platforms play a pivotal role in shaping political discourse, but the scale and rapid evolution of online content make systematic
arXiv:2602.18639v2 Announce Type: replace Abstract: World models learned from high-dimensional visual observations allow agents to make decisions and plan directly in latent space, avoiding pixel-leve
arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models
arXiv:2610.00930v1 Announce Type: new Abstract: Post-training quantization for diffusion models increasingly exploits timestep, feature, and layer structure. While recent work has begun incorporating
arXiv:2610.00074v1 Announce Type: new Abstract: K-Dense BYOK (bring your own keys) is a free, open-source AI research assistant for scientists in any field that runs on the researcher's own computer.
arXiv:2610.01062v1 Announce Type: new Abstract: Activation steering provides a simple, training-free mechanism for controlling attributes of generative models such as sentiment, style, and helpfulness