Knowledge catalogue
arXiv:2610.17462v1 Announce Type: new Abstract: Precise control of movement across various robotic embodiments is a longstanding challenge. Modeling complex robotic structures requires significant tim
arXiv:2610.17638v1 Announce Type: new Abstract: World Action Models (WAMs) use generative visual representations to condition robot actions, yet how these representations organize action-relevant info
arXiv:2404.01867v2 Announce Type: replace-cross Abstract: Efficiently tackling multiple tasks within complex environments, such as those found in robot manipulation, remains an ongoing challenge in ro
arXiv:2610.14549v1 Announce Type: new Abstract: Physical systems and distributed AI workflows can retain past information, receive delayed feedback and combine conflicting signals. These features pose
arXiv:2610.14963v1 Announce Type: new Abstract: Sparse-view Cone-Beam Computed Tomography (CBCT) reconstruction is essential for reducing radiation dose and scan effort, but remains underconstrained d
arXiv:2605.06149v2 Announce Type: replace Abstract: The discount factor in reinforcement learning controls both the effective planning horizon and the strength of bootstrapping, yet most deep RL metho
arXiv:2610.14252v1 Announce Type: new Abstract: Looped transformers reuse the same layer multiple times, allowing inference compute to be adjusted without changing the model. Recent adaptive-depth met
arXiv:2610.16624v1 Announce Type: new Abstract: Human motion prediction during human-robot collaboration is critical for achieving safe and efficient interactions in shared environments. Unlike previo
arXiv:2610.15810v1 Announce Type: new Abstract: The introduction of long chain-of-thought (CoT) reasoning and external tools has substantially improved the performance of multimodal large language mod
arXiv:2610.15723v1 Announce Type: cross Abstract: We study adaptive confidence sets for mean vectors of multivariate Gaussians with identity covariance under Huber contamination when the contamination
arXiv:2610.15623v1 Announce Type: new Abstract: Hybrid federated semantic communication enables user equipment (UEs) to contribute model updates or semantic features under a shared training framework.
arXiv:2610.15359v1 Announce Type: new Abstract: Deep classifiers deployed in safety-critical services like autonomous-driving perception remain vulnerable to small adversarial perturbations. Certified
arXiv:2610.14553v1 Announce Type: new Abstract: Autoregressive video generation models generate videos sequentially, with each new block conditioned on previously generated blocks. By training on the
arXiv:2610.16012v1 Announce Type: cross Abstract: Autonomous driving (AD) relies on multi-sensor perception to interpret the surrounding environment. However, the robustness of camera--radar fusion un
arXiv:2610.16630v1 Announce Type: new Abstract: Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions unde
arXiv:2610.16532v1 Announce Type: cross Abstract: This work develops a geometric theory of aerodynamic promptness for multirotor platforms whose propeller directions depend on a smooth orientation-mec
arXiv:2603.17712v1 Announce Type: cross Abstract: Zero-Shot Object Navigation (ZSON) in unknown multi-floor environments presents a significant challenge. Recent methods, mostly based on semantic valu
arXiv:2610.18305v1 Announce Type: new Abstract: The world encompasses both physical environments and human actors. Predicting its evolution requires understanding both physical laws and how emotions s
arXiv:2610.18420v1 Announce Type: cross Abstract: We trained Agaram 2.5B, a 2.5-billion-parameter Tamil-English language model, from scratch on about 50 billion tokens (58% Tamil, the rest English, ma
arXiv:2610.16280v1 Announce Type: cross Abstract: Before changing a deployed AI agent (a stricter safety gate, a new model), organizations must approve the change, starting from existing logs. Extendi
Server consolidation is getting a second look as agentic AI drives a surge in demand for general-purpose compute. Graphics processing units dominate the AI infrastructure conversation, but the agents
arXiv:2610.14238v1 Announce Type: cross Abstract: LLM data engineering requires iterative experimentation to determine how data selection, rewards, and curricula affect model learning, making it a nat
arXiv:2610.17832v1 Announce Type: new Abstract: Materials and chemical optimization must choose the next synthesis, characterization, or high-fidelity simulation from sequential observations under a l
arXiv:2610.17881v1 Announce Type: new Abstract: Can an AI agent turn high-level user intent into a functioning robot and teach it how to behave? We study this question from two complementary aspects:
arXiv:2610.17786v1 Announce Type: cross Abstract: We study industrial fault diagnosis as a classification task that assigns sensor time-series windows to predefined health states or fault types. Scarc
arXiv:2610.14210v1 Announce Type: cross Abstract: ScanRefer Multiple queries require spatial disambiguation: several instances of the target class are present, and the referencer must pick one. When p
arXiv:2610.16891v1 Announce Type: new Abstract: Inferring tumor-growth laws from sparse, noisy observations requires more than accurate curve fitting. We study an AI-assisted workflow involving symbol
Modal Labs Inc., a provider of artificial intelligence infrastructure, today announced that it has raised 750 million in late-stage funding. Accel led the Series D round. It was joined by Kleiner Perk
AI coding ROI is earned in review. @Harvard / @_jellyfish_co : agents added 30% more code, but there was no significant gain in software output. PR review-to-merge time rose 49%. Most AI code review t
arXiv:2610.16555v1 Announce Type: cross Abstract: We introduce qtBench, a benchmark of 29 open problems in algebraic combinatorics. These problems ask for a simple combinatorial algorithm that explain
arXiv:2610.17944v1 Announce Type: new Abstract: Current image-guided neuronavigation techniques, such as intraoperative MRI and ultrasound, are limited by high costs, limited sensitivity and operation
AI is mass decompiling games. That's both awesome and scary. Indie game developer Popcar talks about the recent wave of AI-powered decompilation of existing games, enabling weird mashups between exist
AI labs need 100 agents constantly running product walkthroughs on their own products and funneling findings and workflows into a repo. 24/7 product testing on a loop. When I ask a question about how
Google’s Gemini 4 Argon is now generally available (GA), offering coding, knowledge‑work, enterprise‑workflow, and cyber‑defense features via the paid Gemini API, Google AI Pro/Ultra in the Gemini app
arXiv:2610.18724v1 Announce Type: new Abstract: The rapid advancement of image-to-text extraction systems and large language models (LLMs) poses new challenges for educational assessment by making ass
arXiv:2610.14248v1 Announce Type: new Abstract: Diffusion models provide expressive trajectory priors for multi-robot motion planning (MRMP), but scaling them to large teams requires coordinating indi
arXiv:2610.15015v1 Announce Type: new Abstract: In the presence of feedback loops, algorithmic decisions at one time step can influence observed data in subsequent steps, potentially introducing selec
arXiv:2610.14734v1 Announce Type: new Abstract: Set-based variational autoencoders (VecSet VAEs) represent 3D shapes as compact sets of latent tokens. Although each token originates from a query at a
arXiv:2610.17970v1 Announce Type: cross Abstract: Long-running agents retain KV caches across turns and sessions for hours or days. Compressing these persistent caches requires reducing storage while
arXiv:2604.02706v2 Announce Type: replace Abstract: Odometry estimation using light detection and ranging (LiDAR) and an inertial measurement unit (IMU), known as LiDAR-inertial odometry (LIO), often
arXiv:2508.06313v2 Announce Type: replace Abstract: This paper presents a unified system-level modeling and control framework for an all-electric heavy-duty robotic manipulator (HDRM) driven by electr
arXiv:2610.17975v1 Announce Type: cross Abstract: We introduce STRUCTURES-P, a machine-learned all-electron orbital-free density functional for periodic CHNO systems. Electrostatics are evaluated anal
arXiv:2610.16143v1 Announce Type: new Abstract: SLAM (Simultaneous Localization and Mapping) is a core technology in autonomous systems that enables them to estimate their own position and build a map
arXiv:2610.15488v1 Announce Type: cross Abstract: Formulaic alpha mining seeks interpretable expressions that rank assets by future returns. The task is challenging because it demands simultaneous pro
arXiv:2610.14959v1 Announce Type: cross Abstract: Formulaic alpha mining seeks to discover executable expressions that capture predictive market signals in a vast, noisy search space. Recent LLM-based
arXiv:2610.18652v1 Announce Type: cross Abstract: Audio memory must recognise recurring sources across acoustic changes while keeping their attributes up to date. Overall accuracy does not reveal how
arXiv:2610.16736v1 Announce Type: cross Abstract: Monte Carlo sampling algorithms aim to produce samples from a target distribution with a given unnormalised probability density function. The high cos
arXiv:2610.16669v1 Announce Type: cross Abstract: Bayesian inference for latent point process intensities often relies on per-dataset sampling or optimization, making repeated inference computationall
arXiv:2512.08659v2 Announce Type: replace-cross Abstract: Clinical communication is central to patient outcomes, yet large-scale human annotation of patient-provider conversation remains labor-intensi
arXiv:2610.14932v1 Announce Type: cross Abstract: Clustering is typically performed using only object features, although additional information about relationships between objects may be available and
arXiv:2610.15590v1 Announce Type: new Abstract: In practical engineering and scientific computing, a real physical system can be reduced to a boundary value problem, and the adequate boundary informat
arXiv:2610.17463v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are promising for energy-efficient spatiotemporal pattern recognition at the edge, but efficient deployment and on-devi
arXiv:2610.15308v1 Announce Type: new Abstract: Combining aerial robots with soft continuum manipulators promises safe, compliant interaction with the environment, but the coupled dynamics of a free-f
arXiv:2610.17511v1 Announce Type: new Abstract: This work presents an algorithm for changing from longitudinal to latitudinal formation of autonomous aircraft squadrons. The maneuvers are defined dyna
arXiv:2610.15558v1 Announce Type: new Abstract: Visual self-modelling lets robots learn body models from observations, but such models usually encode kinematics implicitly rather than exposing metric
arXiv:2610.15328v1 Announce Type: new Abstract: We introduce Anchor-and-Harvest Curriculum (AHC), a domain-informed, rule-based training system for Craftax-Full. AHC combines achievement-oriented task
arXiv:2610.15097v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer new opportunities for controllable text generation. However, their controllability, defined as the ability to sat
And extra thanks to @swyx for another example of where taste meets vision. It's nice to see true community-building vs. transactional behavior happening again We hosted the AI Engineer NYC speaker din
arXiv:2603.15046v2 Announce Type: replace Abstract: In this study, we address the problem of language-guided robotic manipulation, where a robot is required to manipulate a wide range of objects based
arXiv:2610.16324v1 Announce Type: new Abstract: Training-free language-based video anomaly detection (VAD) uses frozen vision--language models (VLMs) and large language models (LLMs) to localize abnor