Knowledge catalogue
arXiv:2610.17171v1 Announce Type: cross Abstract: Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well s
arXiv:2610.18736v1 Announce Type: new Abstract: While conventional camera-based surveillance systems and metal detectors can provide a sufficient level of security when used appropriately, they have f
arXiv:2610.16908v1 Announce Type: new Abstract: End-to-end driving requires rich spatiotemporal representations to support scene understanding and trajectory planning under strict latency constraints.
arXiv:2610.18741v1 Announce Type: new Abstract: Reliable detection of pedestrians and road users is essential for the safe operation of autonomous vehicles. However, this task becomes increasingly cha
arXiv:2603.23356v2 Announce Type: replace-cross Abstract: We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predict
arXiv:2610.18194v1 Announce Type: new Abstract: Robotic manipulation systems commonly learn object affordances from human-annotated datasets, which reflect interaction possibilities for a human hand r
arXiv:2610.17885v1 Announce Type: new Abstract: Microscopic simulations resolve spatial patterns but are feasible only over small domains and short timescales, whereas bulk descriptions erase those pa
arXiv:2610.15185v1 Announce Type: new Abstract: Test-time memorization of sequential information is a foundational capability for any intelligent system that needs to rapidly store and retrieve data,
arXiv:2610.14873v1 Announce Type: cross Abstract: Aspect Sentiment Quadruple Prediction (ASQP) is fundamentally a relational reasoning problem: identifying aspect-opinion-category-sentiment quadruples
arXiv:2609.15308v1 Announce Type: cross Abstract: We present a deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotat
arXiv:2610.17208v1 Announce Type: cross Abstract: Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plast
arXiv:2610.17789v1 Announce Type: cross Abstract: A long-horizon manipulation task consists of primitive skills and the transitions connecting them. Learning skills that can be executed in sequence re
arXiv:2610.14013v1 Announce Type: cross Abstract: Drug development is an expensive and lengthy process requiring developers to select drugs for human trials and diseases to target. Computational tools
arXiv:2610.18867v1 Announce Type: new Abstract: Bringing general-purpose agents into the physical world calls for an executable representation of physical intelligence. Compared with vision-language-a
arXiv:2610.16149v1 Announce Type: cross Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examin
arXiv:2610.15933v1 Announce Type: new Abstract: Predictive coding networks (PCNs) promise properties not offered by backpropagation-trained networks: learning from purely local information, a single n
I've been working on Event2Vec, a small library for learning embeddings of discrete event sequences (purchases, logs, clinical codes, etc.) with a deliberately simple structure: a history is the runni
arXiv:2610.17980v1 Announce Type: new Abstract: Plurality-voting ensembles aggregate the predictions of multiple base classifiers and output the most voted class, with ties typically broken at random.
arXiv:2610.17734v1 Announce Type: new Abstract: Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR). Current methods explore mostly through independent samp
arXiv:2610.14588v1 Announce Type: cross Abstract: Test-time sampling promises to turn one action prediction into a set of distinct executable candidates that a verifier can choose among. Downstream fi
arXiv:2610.18030v1 Announce Type: new Abstract: Closed-loop evaluation of end-to-end (E2E) driving systems typically relies on generating sensor observations and re-processing them through the percept
arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu
arXiv:2610.14568v1 Announce Type: new Abstract: In autoregressive video generation, retaining all historical key-value (KV) states increases memory usage and per-step attention costs as videos grow lo
arXiv:2610.16058v1 Announce Type: new Abstract: Reliable scene understanding requires deciding which predictions to trust, retain, or inspect. In semantic segmentation, component failure predictors su
arXiv:2610.16868v1 Announce Type: new Abstract: Simplicity bias, which can arise from sequential feature learning during training, has been proposed as a general explanation for the success of deep le
arXiv:2610.16862v1 Announce Type: new Abstract: Optical music recognition (OMR) for medieval chant lacks training data linking manuscript images to musical symbols across notational families. Using ex
arXiv:2610.15752v1 Announce Type: new Abstract: Learned real-time supersampling accumulates jittered low-resolution samples along motion vectors. Many methods use a temporal consistency loss to reduce
arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va
arXiv:2610.15110v1 Announce Type: cross Abstract: Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image datasets, long algorithm traini
arXiv:2610.14852v1 Announce Type: new Abstract: Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accura
arXiv:2610.15064v1 Announce Type: new Abstract: The world has seen several threats that include resource depletion, food security, poverty and inequality, difficulties associated with urbanization, mi
arXiv:2610.16272v1 Announce Type: new Abstract: Feed-forward reconstruction recovers camera poses and dense geometry from image sets whose views are assumed to come from a single scene. In practice, u
arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat
arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can
arXiv:2610.14961v1 Announce Type: cross Abstract: We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and
arXiv:2610.17030v1 Announce Type: cross Abstract: A two-dimensional electron gas in a uniform neutralizing background forms a triangular Wigner crystal at low density. In a strongly mass-asymmetric el
arXiv:2610.15830v1 Announce Type: new Abstract: When several predictions use the same internal representation, information about some targets can remain easier to recover than information about others
arXiv:2610.15760v1 Announce Type: new Abstract: Multiscale structure is central to time series forecasting: temporal signals contain slowly varying trends, intermediate seasonal patterns, and high-fre
ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hit 1.2 billion as of July - @FireworksAI_HQ crossed 1 billion
arXiv:2610.13941v2 Announce Type: replace Abstract: Multimodal diffusion transformers (MMDiTs) allow the evolving image to update internal text representations through joint attention. These represent
arXiv:2610.16627v1 Announce Type: cross Abstract: Existing human-centred XAI research predominantly evaluates explanations after they have been generated. However, this fails to provide actionable ins
Interesting new research from Meta Superintelligence Labs It discusses how reward hacking affects coordination in multi-agent coding systems. Coding agents on a team share code, memory, and plans, so
arXiv:2610.14449v1 Announce Type: cross Abstract: Experiments with remote decision-making agents depend on more than the policy: the world may change during inference, the simulator determines which a
arXiv:2607.18760v2 Announce Type: replace Abstract: In legged locomotion, divergent components of motion (DCMs) have emerged as characteristic states for balance control. They isolate the unstable mod
arXiv:2610.16522v1 Announce Type: cross Abstract: Safe robot navigation in unknown, dynamic environments requires more than geometric collision checking: a robot still far from an obstacle may be unab
arXiv:2610.16299v1 Announce Type: new Abstract: Video anomaly understanding (VAU) aims to generate language-level interpretations of anomalous events in long videos, requiring visual evidence that sup
arXiv:2610.15362v1 Announce Type: new Abstract: Object Navigation in unseen environments remains a fundamental challenge in embodied AI, as it requires agents to generalize visual and spatial reasonin
arXiv:2610.16722v1 Announce Type: cross Abstract: Visual contrastive decoding corrects answers using the prediction difference between the original image and a reference condition, yet the same contra
arXiv:2610.18393v1 Announce Type: cross Abstract: Equivariant machine learning interatomic potentials (MLIPs) promise atomistic simulations with accuracy approaching that of quantum-mechanical calcula
arXiv:2610.17053v1 Announce Type: cross Abstract: Shapley-based measures are widely used for measuring variable importance in statistics and machine learning. However, these measures have a serious is
arXiv:2610.17640v1 Announce Type: new Abstract: Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents
arXiv:2610.17354v1 Announce Type: new Abstract: Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which
arXiv:2610.14988v1 Announce Type: new Abstract: The average-reward setting for reinforcement learning is challenging because its Bellman operator is known to contract in span only when the underlying
arXiv:2610.14492v1 Announce Type: cross Abstract: Microsurgical anastomosis is one of the most challenging and sophisticated procedures for surgical robotics, requiring accurate manipulation of surgic
arXiv:2511.19548v2 Announce Type: replace Abstract: Neuroeconomics appears to offer welfare economics an evidential supplement, since neural data may help distinguish choices that express genuine pref
arXiv:2508.10688v3 Announce Type: replace Abstract: Single-image novel view synthesis requires viewpoint-dependent structural changes while retaining source-scene information and inferring unobserved
arXiv:2610.18333v1 Announce Type: cross Abstract: Random features provide a standard approach to scaling kernel methods to large datasets by approximating the kernel with a finite-dimensional feature
arXiv:2602.08331v2 Announce Type: replace-cross Abstract: Network traffic classification underpins network security and management but faces growing challenges from pervasive encryption and evolving p
arXiv:2610.17900v1 Announce Type: cross Abstract: Extended chain-of-thought reasoning improves problem-solving performance but increases inference cost and latency, motivating more accurate answers wi
arXiv:2505.03539v4 Announce Type: replace Abstract: Panoramic imaging enables capturing 360{eg} images with an ultra-wide Field-of-View (FoV) for dense omnidirectional perception, which is critical to