Knowledge catalogue
arXiv:2511.07308v2 Announce Type: replace Abstract: Understanding the training dynamics of deep neural networks remains a major open problem, with physics-inspired approaches offering promising insigh
arXiv:2511.14751v2 Announce Type: replace Abstract: We propose Confidence-Guided Token Merging (Co-Me), an acceleration mechanism for visual geometric transformers without retraining or finetuning the
arXiv:2605.14795v1 Announce Type: new Abstract: Referring Multi-Object Tracking (RMOT) faces a fundamental structural contradiction between the high-discriminability demand and the sparse semantic sup
company that steals IP urges US government not to allow others to steal their IP Anthropic drops a paper on the US-China AI race They believe the US and its allies may be able to lock in a 12-24 month
arXiv:2605.14067v1 Announce Type: new Abstract: Financial distress prediction remains a significant challenge in enterprise risk analysis due to the highly imbalanced nature of real-world financial da
arXiv:2605.15062v1 Announce Type: new Abstract: Background. RGB-trained capsule-endoscopy classifiers underperform on small-vessel vascular findings by conflating hemoglobin contrast with bile and ill
arXiv:2605.14495v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent fr
arXiv:2510.02952v3 Announce Type: replace Abstract: Inferring trajectories from longitudinal spatially-resolved omics data is fundamental to understanding the dynamics of structural and functional tis
arXiv:2509.01299v2 Announce Type: replace Abstract: Cross-domain few-shot segmentation (CD-FSS) aims to segment unseen categories with very limited samples while alleviating the negative effects of do
arXiv:2605.11611v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG)
arXiv:2405.07459v3 Announce Type: replace Abstract: Text-based person search (TBPS) aims to retrieve specific images of individuals from large datasets using textual descriptions. Existing TBPS method
arXiv:2605.14220v1 Announce Type: cross Abstract: Modern LLM RL systems separate rollout generation from policy optimization. These two stages are expected to produce token probabilities that match ex
arXiv:2507.04049v4 Announce Type: replace Abstract: Most end-to-end autonomous driving methods rely on imitation learning from single expert demonstrations, often leading to conservative and homogeneo
arXiv:2605.14104v1 Announce Type: new Abstract: Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing
arXiv:2502.00270v3 Announce Type: replace-cross Abstract: The performance of an LLM depends heavily on the relevance of its training data to the downstream evaluation task. However, in practice, the d
arXiv:2605.14014v1 Announce Type: cross Abstract: Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such a
arXiv:2605.14742v1 Announce Type: new Abstract: Understanding human--environment interactions from egocentric vision is essential for assistive robotics and embodied intelligent agents, yet existing m
arXiv:2509.21261v3 Announce Type: replace Abstract: Micro-action Recognition is vital for psychological assessment and human-computer interaction. However, existing methods often fail in real-world sc
arXiv:2605.13853v1 Announce Type: cross Abstract: Facial editing is an important task with applications in entertainment, virtual reality, and digital avatars. Most existing approaches rely on generat
arXiv:2605.14868v1 Announce Type: new Abstract: Generating adversarial examples at scale is a core primitive for robustness evaluation, adversarial training, and red-teaming, yet even 'fast' attacks s
arXiv:2605.13974v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) and related flow-based architectures are now among the strongest text-to-image generators, yet the internal mechanisms t
arXiv:2605.14168v1 Announce Type: new Abstract: Learning of continuous exponential family distributions with unbounded support remains an important area of research for both theory and applications in
arXiv:2603.03577v2 Announce Type: replace Abstract: Detecting and segmenting novel object instances in open-world environments is a fundamental problem in robotic perception. Given only a small set of
arXiv:2605.14445v1 Announce Type: new Abstract: Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tas
arXiv:2605.14501v1 Announce Type: cross Abstract: This paper proposes a fully dynamic Deep Reinforcement Learning (DRL) method for rebalancing dockless bike-sharing systems, overcoming the limitations
arXiv:2605.15018v1 Announce Type: cross Abstract: Shapley value and its priority-aware extensions are widely used for valuation in machine learning, but existing methods require pairwise priority to b
Had the honor of sharing the stage with the one and only @sydneyrunkle at Interrupt 2026 to talk about Deep Agents. Sign-up for the Managed Deep Agents waitlist today to get early access! https://www.
Honda previewed two new hybrid prototypes scheduled to launch by 2028 after absorbing a 9.2 billion EV-related loss, its largest in company history. The company indefinitely suspended its planned 15 b
arXiv:2602.01828v2 Announce Type: replace Abstract: Many complex networks exhibit hierarchical, tree-like structures, making hyperbolic space a natural candidate wherein to learn representations of th
A Reddit post showcasing a humorous AI-generated image created by asking ChatGPT to produce a still frame from a 1950s movie, where the comedic elements become increasingly apparent upon closer inspec
arXiv:2605.14774v1 Announce Type: new Abstract: In the world of AI and advanced technologies investigation aspects identification of a crime or criminal plays a major problem. In this research we focu
arXiv:2605.14239v1 Announce Type: new Abstract: Hyperspectral image (HSI) classification is challenging in complex scenes due to spectral ambiguity, spatial heterogeneity, and the strong coupling betw
arXiv:2605.14455v1 Announce Type: new Abstract: The Intelligence Impact Quotient (IIQ) is a composite metric intended to quantify the depth to which AI systems are integrated into organizational work
it’s kind of awesome that continual learning has now come to the agent & harness level. i remember when online learning was the big craze in traditional ml a couple of years ago, that transitioned int
arXiv:2605.14998v1 Announce Type: new Abstract: From subcellular structures to entire organisms, many natural systems generate complex organisation through self-organisation: local interactions that c
arXiv:2512.02920v3 Announce Type: replace-cross Abstract: We consider analyzing traffic accident patterns using both road network data and satellite images aligned to road graph nodes. Previous work f
arXiv:2605.14494v1 Announce Type: new Abstract: Two-Stage Robust Optimization (2RO) with discrete uncertainty is challenging, often rendering exact solutions prohibitive. Scenario reduction alleviates
arXiv:2605.14346v1 Announce Type: new Abstract: Single-frame Infrared Small Target Detection (ISTD) aims to localize weak targets under heavy background clutter, yet dense pixel-wise annotations are e
arXiv:2605.14454v1 Announce Type: cross Abstract: As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line
arXiv:2605.14548v1 Announce Type: new Abstract: Gait recognition, as a promising biometric technology, identifies individuals through their unique walking patterns and offers distinctive advantages in
arXiv:2605.14407v1 Announce Type: new Abstract: The dominant discourse on AI limitations frames the boundary of AI capability as a divide between digital tasks (where AI excels) and physical tasks (wh
arXiv:2605.14980v1 Announce Type: cross Abstract: Analyzing microscopy images to extract biological object properties (e.g., their morphological organization, temporal dynamics, and population density
arXiv:2509.14159v3 Announce Type: replace Abstract: As robots become more integrated in society, their ability to coordinate with other robots and humans on multi-modal tasks (those with multiple vali
arXiv:2605.14660v1 Announce Type: new Abstract: Post-Traumatic Stress Disorder (PTSD) is fundamentally a neuroplastic problem traumatic contact events encode over-reactive neural pathways through Hebb
arXiv:2605.14781v1 Announce Type: new Abstract: Monocular 3D object detection remains challenging because metric size and depth are underdetermined by single-view evidence, particularly under occlusio
arXiv:2605.14199v1 Announce Type: new Abstract: Motion planning for autonomous vehicles requires generating collision-free and dynamically feasible trajectories in complex environments under real-time
arXiv:2512.16768v3 Announce Type: replace-cross Abstract: Flow matching (FM) constructs continuous-time ODE samplers by prescribing probability paths between a base distribution and a target distribut
arXiv:2510.13583v4 Announce Type: replace-cross Abstract: Causal discovery from i.i.d. observational data is known to be generally ill-posed. We demonstrate that if we have access to the distribution
arXiv:2507.21023v2 Announce Type: replace Abstract: Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. Using a reasonable mathematical anomaly
arXiv:2605.14277v1 Announce Type: new Abstract: Parallelization has played an instrumental role in the field of artificial intelligence (AI), drastically reducing the time taken to train and evaluate
arXiv:2605.14098v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning with self-consistency improves performance by aggregating multiple sampled reasoning paths. In this setting, correctn
arXiv:2605.14269v1 Announce Type: cross Abstract: Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has d
PipelineIQ is a Databricks solution that leverages data analytics and AI to provide predictive sales intelligence, enabling sales teams to forecast pipeline outcomes and identify actionable opportunit
arXiv:2605.14125v1 Announce Type: new Abstract: How do artificial neural networks bind concepts to form complex semantic structures? Here, we propose a simple neural code, whereby the existence and th
arXiv:2605.14297v1 Announce Type: cross Abstract: We study reinforcement learning in hybrid discrete-continuous action spaces, such as settings where the discrete component selects a regime (or index)
arXiv:2605.15164v1 Announce Type: cross Abstract: This position paper argues that behavioural assurance, even when carefully designed, is being asked to carry safety claims it cannot verify. AI govern
arXiv:2605.14294v1 Announce Type: new Abstract: Formal verification of transformers has become increasingly important due to their widespread deployment in safety-critical applications. Compared to cl
arXiv:2605.14991v1 Announce Type: cross Abstract: Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year surviva
arXiv:2605.14758v1 Announce Type: new Abstract: History-dependent policies induced by recurrent neural networks (RNNs) rely on latent hidden state dynamics, making verification in partially observable
arXiv:2605.14561v1 Announce Type: new Abstract: Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate