Knowledge catalogue
arXiv:2610.01408v1 Announce Type: new Abstract: Trajectory crossing remains a critical bottleneck in Flow Matching (FM), and previous works typically view these crossings from a theoretical optimizati
arXiv:2610.02023v1 Announce Type: new Abstract: While Large Language Models (LLMs) advance 3D indoor scene synthesis, current pipelines fail to retain user-specific preferences across sessions, making
arXiv:2607.09086v2 Announce Type: replace Abstract: We present Subtoken Vision Transformer (SubViT), a selective image tokenization method for fine-grained visual recognition. Standard Vision Transfor
arXiv:2610.01388v1 Announce Type: cross Abstract: We present a method for learning binaural sound localization using egomotion as a supervisory signal. Over the course of a video, the cameras directio
arXiv:2610.01135v1 Announce Type: new Abstract: Intracranial aneurysm rupture is associated with substantial morbidity and mortality, yet aneurysm detection remains challenging, particularly for small
arXiv:2610.01973v1 Announce Type: new Abstract: Reinforcement learning (RL) for video generation usually assigns one scalar reward to an entire sampled video. Yet a video is not uniformly flawed: some
arXiv:2610.01052v1 Announce Type: new Abstract: We argue that as video generation extends to longer durations, subject consistency should be evaluated over extit{dynamic subject sets}. We therefore in
arXiv:2610.02190v1 Announce Type: new Abstract: Step-size selection remains a central challenge in large-scale neural network optimization; conservative steps slow convergence, while aggressive steps
arXiv:2610.01452v1 Announce Type: new Abstract: While state-of-the-art automated models for medical image segmentation achieve high mean performance, they frequently suffer from localized, catastrophi
arXiv:2610.01835v1 Announce Type: cross Abstract: We present Varda-single-1.0, a medium-range data-driven weather prediction system built for the Alpine domain. It provides hourly deterministic region
arXiv:2510.08944v2 Announce Type: replace Abstract: Real-world time-series regression often involves non-stationarity, heteroscedasticity, and regime changes, under which recent prediction errors may
arXiv:2610.00757v1 Announce Type: new Abstract: Long-video question answering is limited by the high cost of visual tokens and by the fixed context width of current VLMs. A long-video question may req
arXiv:2610.00012v1 Announce Type: new Abstract: LLM agents increasingly act through modular systems, such as order, payment, inventory, and shipment services, where actions in one module change which
Had opus 5.5 do the bring up.. super solid results. Using only 4 GPU results in KV of like 120k with image on. 27B TP=4 results in >200 tok/s with dflash, prefill around 2.5-3.5k. Both these are runni
arXiv:2609.38339v1 Announce Type: cross Abstract: Federated learning (FL) has become a foundational paradigm for multi-institutional medical AI, allowing hospitals and research centers to jointly trai
arXiv:2609.39066v1 Announce Type: new Abstract: Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large la
'Tuesday, sorry Thursday' is not the same as 'Tuesday Thursday'. And losing 'don't' is a pretty big edit. What do you put in tests for the cleanup step? I'd start with corrections, names and numbers,
Hey everyone! I’ve been working on ASTRABOX: an arcade interface where you describe a game, the AI builds it, and you can ask for changes by voice while playing. Each game gets its own visuals and gam
arXiv:2609.40320v1 Announce Type: new Abstract: Most vision architectures assume that observations lie on a regular grid, an effective abstraction for natural images but a restrictive one for sensing
arXiv:2609.40269v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static ob
arXiv:2609.39816v1 Announce Type: new Abstract: Fast matrix multiplication saves multiplications through exact cancellation, but rounding sums that mix token rows can leave contributions from later to
arXiv:2509.13972v4 Announce Type: replace Abstract: Monitoring building construction sites requires comparing the as-planned design with the as-built state, which can be estimated in real time using S
arXiv:2609.39709v1 Announce Type: new Abstract: Recent diffusion-based pipelines have achieved promising progress in image-to-3D synthesis. However, generating high-fidelity details remains challengin
The Nvidia Deploy repository provides open‑source C++ samples that pair ONNX Runtime with the TensorRT RTX execution provider to accelerate local inference on Windows and Linux. It separates model exp
arXiv:2609.39250v1 Announce Type: new Abstract: Federated learning (FL) is a promising paradigm of machine learning, which preserves user privacy by enabling learning without sharing raw data with a c
arXiv:2609.38639v1 Announce Type: new Abstract: LLM-guided evolutionary search can discover complex programs, but existing methods mostly only save candidate programs and fitness scores while discardi
Hello everyone. I've recently ran some experiments comparing DDR4/PCIe4 and DDR5/PCIe5 for AI workstations on a pre-training run, and would like to hear yours thoughts. First of all, and as a summary
arXiv:2609.38386v1 Announce Type: new Abstract: Concurrent autoregressive inference creates a fundamental interference problem: prefilling a newly arrived long prompt can delay tokens for requests tha
arXiv:2609.38776v1 Announce Type: cross Abstract: Training data attribution for diffusion models aims to identify the training samples that influence a generated instance, but existing methods either
Hi everyone — I'm behind Autonomous Workday, and I'm sharing an English-language architecture walkthrough about building an event-driven workflow around local inference. The proposed flow separates fi
arXiv:2609.39021v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning ability of multimodal language models through verifiable rewards and increasingly f
arXiv:2609.39006v1 Announce Type: new Abstract: Cross-embodiment dexterous grasp generation remains challenging because robotic hands differ substantially in geometry, topology, and kinematics. Existi
arXiv:2609.38911v1 Announce Type: new Abstract: Learning must acquire new capabilities while preserving both prior responsibilities and the capacity to learn again. We introduce Generalized Residual C
arXiv:2609.39116v1 Announce Type: new Abstract: Prior-free 6D object pose tracking seeks to recover the trajectory of an unseen object from a single RGB video without object-specific CAD models, posed
arXiv:2609.39883v1 Announce Type: new Abstract: Video temporal grounding supports applications such as video search, content review, and automated editing by localizing events described in natural lan
arXiv:2609.39323v1 Announce Type: cross Abstract: Robot demonstration generation requires a system to identify where an interaction should occur, plan a feasible motion, and execute the required conta
arXiv:2609.39074v1 Announce Type: cross Abstract: Federated learning (FL) on memory-constrained edge devices faces a dilemma: first-order (FO) optimization (i.e., backpropagation) demands substantial
arXiv:2609.39767v1 Announce Type: cross Abstract: The scale and expense of pre-training language models make efficient hyperparameter tuning essential, yet a principled guidance is still missing. In t
I built a free tool that lets your coding agent make videos like this one. You give your agent the link to the repo and say what the video should be about. It writes the words, draws the scenes, and y
arXiv:2609.39194v1 Announce Type: new Abstract: Wireless split learning (SL) reduces on-device computation by offloading upper layers to a server, yet transmitting high-dimensional intermediate featur
arXiv:2609.39938v1 Announce Type: cross Abstract: Hour-scale audio-visual question answering is constrained by a context dilemma: dense whole-recording encoding rapidly exhausts context limits, wherea
arXiv:2609.38383v1 Announce Type: new Abstract: Random exploration reveals how an environment can be traversed before a goal is specified. Can this experience support long-range planning without polic
arXiv:2609.39899v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) enables assessment of cardiac anatomy, ventricular function, and myocardial tissue characteristics. Clinicians
arXiv:2609.40170v1 Announce Type: new Abstract: MANETs enable flexible infrastructure-less wireless connectivity in dynamic and resource-constrained environments. As modern MANETs exploit multiple fre
Anyone else experiencing this issue this week in particular? I am getting WAY less requests this week than usual, no matter what model I am on. I actually had to discontinue things I was doing because
arXiv:2609.39182v1 Announce Type: cross Abstract: World Models are appearing as the next major frontier in computer vision. However, their robustness is currently largely unexplored. We identify the p
arXiv:2609.38985v1 Announce Type: new Abstract: Generating compact, artist-style meshes with explicit topology typically relies on autoregressive models which incur prohibitive sequential per-token co
arXiv:2609.38718v1 Announce Type: new Abstract: Steering large language models typically relies on linear, context-independent interventions in activation space, an assumption that recent work has cha
arXiv:2410.02159v3 Announce Type: replace-cross Abstract: Language models (LMs) can 'memorize' information, i.e., encode training data in their weights in such a way that inference-time queries can le
arXiv:2609.39525v1 Announce Type: cross Abstract: Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intract
arXiv:2603.06350v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly adopt Mixture-of-Experts (MoE) architectures to scale efficiently under stringent resource constrain
arXiv:2609.39324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently incorporated world models to provide richer dynamic supervision beyond sparse action labels. However
arXiv:2609.39915v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents
arXiv:2609.38930v1 Announce Type: cross Abstract: In semantic segmentation, a recent line of RankSEG methods directly optimizes Dice/IoU scores at inference time, improving alignment with evaluation m
arXiv:2609.39504v1 Announce Type: cross Abstract: We present PartiCam, a training-free Particle filtering rooted method for improved Camera controlled video generation. Generating videos that follow a
arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica
arXiv:2609.38780v1 Announce Type: cross Abstract: Audio is increasingly used for human activity recognition (HAR) because it captures object interactions, environmental events, and contextual cues in
arXiv:2609.39149v1 Announce Type: new Abstract: Textual skills enable large language model (LLM) based agents to accumulate reusable procedural knowledge without updating model parameters. Yet existin
arXiv:2609.38833v1 Announce Type: new Abstract: Federated continual learning must integrate new tasks over time without losing earlier-task knowledge. Most existing methods attach an anti-forgetting m
arXiv:2609.38578v1 Announce Type: cross Abstract: Cross-structural motion retargeting aims to transfer motion between different skeletal topologies. Despite recent progress, existing state-of-the-art