Knowledge catalogue
arXiv:2609.11900v1 Announce Type: cross Abstract: Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant un
arXiv:2508.05830v3 Announce Type: replace Abstract: Large Language Model (LLM) studies that use language responses elicited from depression assessments to predict scores on those same assessments ofte
arXiv:2604.04036v2 Announce Type: replace-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challengin
arXiv:2603.22437v2 Announce Type: replace-cross Abstract: We present mmFHE, the first system that executes the entire cloud-side mmWave sensing pipeline including the DSP and ML inference under fully
arXiv:2609.11601v1 Announce Type: new Abstract: Gait recognition is commonly studied using RGB videos or their derived silhouettes and poses. Yet human walking produces heterogeneous photometric, geom
arXiv:2609.09591v1 Announce Type: cross Abstract: Sixth-generation (6G) wireless networks are expected to provide a key infrastructure for large-scale embodied intelligence, where heterogeneous robots
arXiv:2609.11842v1 Announce Type: new Abstract: Diffusion and flow-matching schedules control the signal and noise coefficients that mix data and noise along affine probability paths. Minimizing a kin
arXiv:2609.11338v1 Announce Type: new Abstract: Closed kinematic chains complicate modular modeling by coupling active and passive coordinates through nonlinear closure constraints. This paper present
arXiv:2609.10385v1 Announce Type: cross Abstract: Animation and VFX pre-production review requires teams to translate loosely specified creative intent--briefs, evolving specifications, heterogeneous
arXiv:2609.10664v1 Announce Type: cross Abstract: Language models leave a distinctive vocabulary in the prose they help write, and we measure how much of the astronomy literature now carries it. From
arXiv:2609.11357v1 Announce Type: new Abstract: Human-to-humanoid retargeting has largely been studied on legged platforms, while comparatively few wheeled-humanoid systems support coupled locomotion
arXiv:2609.10545v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed model training without centralizing data but suffers from high communication overhead. To address this, we
arXiv:2609.09565v1 Announce Type: new Abstract: Agentic graph learning (AGL) has recently achieved promising results on graph reasoning tasks, where an agent powered by a large language model (LLM) se
arXiv:2609.11439v1 Announce Type: new Abstract: It is natural for humans to walk and talk simultaneously. This paper tackles the challenge of replicating such natural behaviors in 3D avatar motion gen
arXiv:2609.11322v1 Announce Type: new Abstract: Computational recognition of verbal humour remains a challenging task, requiring an understanding of language, delivery style, emotions, and cultural co
arXiv:2609.10758v1 Announce Type: new Abstract: Multilingual large language models (LLMs) are increasingly used for open-ended text generation, yet their behaviour in low-resource languages remains po
arXiv:2609.11673v1 Announce Type: new Abstract: Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or e
arXiv:2609.11655v1 Announce Type: new Abstract: Muon has emerged as a highly effective optimizer for large language model training, often achieving superior convergence and performance compared with t
arXiv:2609.11253v1 Announce Type: cross Abstract: Erasing concept-specific information from representations has been proven useful for mitigating bias or interpreting model decisions. The joint object
arXiv:2512.18041v2 Announce Type: replace Abstract: Processing overlapping narrative documents, such as legal testimonies or historical accounts, often aims not for compression but for a unified, cohe
arXiv:2609.10715v1 Announce Type: new Abstract: We introduce NCP-ArchPreview, a latent-space language model that pushes autoregressive pretraining beyond standard next-token prediction (NTP). Alongsid
arXiv:2506.19695v2 Announce Type: replace-cross Abstract: This paper studies the ell^p-Lipschitz constants of ReLU neural networks Phi: R^d o R with random parameters for p in [1,infty]. The distribut
arXiv:2609.11807v1 Announce Type: cross Abstract: We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence o
arXiv:2609.11699v1 Announce Type: new Abstract: On-Policy Self-Distillation (OPSD) has emerged as a popular paradigm for large language model (LLM) self-improvement, allowing models to act as their ow
arXiv:2609.11022v1 Announce Type: cross Abstract: A model first sees an image from one physical measurement experiment, such as how far a block coasted, and must answer a question about a new trial, s
arXiv:2408.10077v4 Announce Type: replace-cross Abstract: We study the welfare-maximizing allocation of heterogeneous objects when screening uses costly effort rather than monetary transfers. No-scree
arXiv:2609.11892v1 Announce Type: new Abstract: As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for
arXiv:2609.10632v1 Announce Type: cross Abstract: Machine-learning systems are built almost exclusively on a few large Python-orchestrated frameworks, and they inherit those stacks' engineering costs:
arXiv:2609.10918v1 Announce Type: cross Abstract: Imitation learning has achieved impressive results in robotic manipulation, yet most existing approaches assume clean backgrounds and lack explicit me
arXiv:2609.11244v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse tasks, they suffer from hallucinations where generated o
arXiv:2609.11582v1 Announce Type: new Abstract: As Omni-modal large language models (Omni-LLMs) take in audio, video and text together, their KV cache memory cost grows. KV cache quantization is the d
arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom
arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft
arXiv:2510.23693v2 Announce Type: replace Abstract: This PhD thesis investigates the societal impact of machine learning (ML). ML increasingly informs consequential decisions and recommendations, sign
arXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs---generated code, hypotheses, or papers---yet discard the reasoning process
arXiv:2603.20278v2 Announce Type: replace-cross Abstract: Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. Howev
arXiv:2609.10550v1 Announce Type: cross Abstract: AI deployment performance is shaped not by model architecture alone, but by interactions among compression, compiler transformations, and serving poli
arXiv:2308.01030v2 Announce Type: replace-cross Abstract: In out-of-distribution (OOD) detection, fine-tuning with auxiliary outlier data often improves detection performance at the cost of classifica
arXiv:2609.11737v1 Announce Type: cross Abstract: Collective intelligence depends not only on the capabilities of individual members, but also on how those members are organized. Yet artificial multi-
arXiv:2609.11271v1 Announce Type: new Abstract: Perineural invasion (PNI) is an adverse histopathologic marker in intrahepatic cholangiocarcinoma (ICC), but it is usually confirmed only after resectio
arXiv:2601.02031v3 Announce Type: replace-cross Abstract: Pretraining of large language models is not only expensive but also prone to certain training instabilities. A specific instability that often
arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t
arXiv:2609.11117v1 Announce Type: new Abstract: Reproducibility is essential to scientific progress, yet the growing volume and complexity of scientific publications make exhaustive manual verificatio
arXiv:2609.09789v1 Announce Type: cross Abstract: Organizational design in the era of artificial intelligence requires experimental methods that can test how human-AI groups coordinate, delegate, and
arXiv:2602.11498v2 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets) have shown promising potential to generate high-scoring candidates with probability proportional to their rewar
arXiv:2609.11538v1 Announce Type: new Abstract: Generative Marginalization Models (MaMs) have been recently introduced as efficient neural sampling models for any-order autoregressive modelling of dis
arXiv:2503.17970v2 Announce Type: replace-cross Abstract: Breast cancer survival prediction in computational pathology presents a remarkable challenge due to tumor heterogeneity. For instance, differe
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:2508.02604v4 Announce Type: replace Abstract: Robotic cutting is a challenging, contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large conta
arXiv:2603.23821v2 Announce Type: replace Abstract: Linguistic representation learning in deep neural language models (LMs) has been studied for decades, but finding representations in LMs remains an
arXiv:2609.11133v1 Announce Type: new Abstract: Datacenter GPU power is the binding constraint on LLM serving capacity, and production serving has shifted to prefill/decode (PD) disaggregation. Deploy
arXiv:2609.10976v1 Announce Type: new Abstract: Associative memory in the Hopfield network is attractor dynamics in a disordered many-body system, and higher-order and exponential extensions turn its
arXiv:2510.25566v2 Announce Type: replace-cross Abstract: We present PitchFlower, a flow-based neural audio codec with explicit pitch controllability. Our approach promotes pitch disentanglement throu
arXiv:2609.10905v1 Announce Type: new Abstract: Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the config
arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv
arXiv:2609.09664v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as personalized assistants that interact with users over extended periods of time. As conversatio
arXiv:2609.11477v1 Announce Type: new Abstract: Brain metastases exhibit high inter-lesion variability in size, enhancement pattern, and post-treatment appearance, making volumetric segmentation of bo
arXiv:2609.11780v1 Announce Type: new Abstract: Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine learning models, however current state-of-the-art at
arXiv:2609.11277v1 Announce Type: cross Abstract: Reliable railway operations depend increasingly on real-time environmental intelligence delivered through wireless sensor infrastructures, a capabilit
arXiv:2609.11330v1 Announce Type: new Abstract: Optical coherence tomography is a promising modality for markerless motion tracking due to its high spatial resolution and inherent depth perception. Ho