Knowledge catalogue
arXiv:2606.15034v2 Announce Type: replace Abstract: Computer-use agents can complete benign user instructions while violating important constraints of the user's environment. We introduce OSGuard, a d
arXiv:2610.07766v1 Announce Type: new Abstract: We present Open Telco (OTel), an open telecom AI resource that releases derived telecom datasets for retrieval, reranking, instruction tuning, and safet
Our SynthID technology lets you easily verify if an image, video, or audio file is AI-generated, and today we’re expanding access. Now anyone can go to http://synthid.com to check files for a SynthID
arXiv:2610.08296v1 Announce Type: new Abstract: Generative models have the potential to accelerate inorganic materials discovery by enabling inverse design, but generating experimentally realisable cr
arXiv:2610.07917v1 Announce Type: new Abstract: Demonstration-conditioned policies provide a natural interface for specifying robot behavior, yet long-horizon manipulation remains difficult when visua
arXiv:2610.08627v1 Announce Type: new Abstract: Long-horizon world-model planning typically relies on autoregressive rollouts, where predicted states are repeatedly fed back into the model. This prese
arXiv:2610.08662v1 Announce Type: new Abstract: As coding agents increasingly undertake real-world work autonomously, judging whether their risk treatments are warranted has become important. Existing
arXiv:2610.08532v1 Announce Type: new Abstract: Trajectory optimization (TO) under nonlinear dynamics, actuation limits and collision avoidance constraints is a fundamental problem in robotics, albeit
arXiv:2610.08142v1 Announce Type: new Abstract: Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous par
I recently installed ollama on my machine to test using AI locally, I don't know if you will be able to hear it on the video but every time my terminal outputs a response there is this weird writing/s
arXiv:2610.08672v1 Announce Type: new Abstract: Mesh-agnostic facial animation retargeting transfers expressions across meshes with different structures, but preserving facial motion without surface a
arXiv:2610.08784v1 Announce Type: new Abstract: Pretrained robotic policies can suffer substantial performance degradation under out-of-distribution (OOD) conditions encountered during deployment, mot
arXiv:2610.08153v1 Announce Type: cross Abstract: Multiple-choice question answering (MCQA) is commonly used to evaluate large language models under the assumption that one of the provided options is
arXiv:2610.08272v1 Announce Type: new Abstract: Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative pred
arXiv:2610.07725v1 Announce Type: new Abstract: Modern voice assistants may be shared by multiple users and should be able to answer questions about earlier conversations such as 'When did I originall
arXiv:2610.07782v1 Announce Type: new Abstract: Decomposing long-context inference across cooperating agents bounds the active KV cache per call rather than total evidence, which matters when KV-cache
arXiv:2610.07588v1 Announce Type: new Abstract: Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the
arXiv:2610.08527v1 Announce Type: new Abstract: Hybrid architectures combining linear sequence models with softmax attention provide an effective balance between efficient long-context modeling and pr
arXiv:2610.08737v1 Announce Type: new Abstract: The adoption of humanoid robots in education and research remains limited by high hardware costs, complex sensing systems, and substantial computational
arXiv:2610.06929v1 Announce Type: new Abstract: Improvements in human-robot physical interaction (pHRI) can have major implications for physical therapy, search and rescue, and telemedicine. However,
arXiv:2610.07609v1 Announce Type: new Abstract: Neural simulation of high-fidelity deformable bodies is a foundational challenge in computer graphics and physical AI. Long-horizon prediction for high-
arXiv:2610.08068v1 Announce Type: new Abstract: Realistic physical interaction is a cornerstone of embodied intelligence, yet collecting paired visual--tactile data remains costly. Visual-to-tactile s
arXiv:2610.08188v1 Announce Type: new Abstract: Event cameras record asynchronous log-image-irradiance changes with microsecond latency and high dynamic range. These properties are useful for photomet
arXiv:2610.07127v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models yield strong performance on static perception and reasoning benchmarks, yet such evaluations largely o
arXiv:2605.06021v2 Announce Type: replace Abstract: Systematic reviews and meta-analyses often need numerical data reported only in figures, and extracting them with interactive digitisers usually req
arXiv:2610.07298v1 Announce Type: cross Abstract: Cyber threat analysis increasingly depends on evidence distributed across vendor advisories, vulnerability databases, and threat intelligence sources.
arXiv:2610.08082v1 Announce Type: new Abstract: LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors m
arXiv:2610.08346v1 Announce Type: new Abstract: Polarization imaging provides physical cues beyond intensity imaging but typically requires specialized hardware. Recent methods infer polarization from
LIBERO is a robot manipulation benchmark: 130 tasks across five suites (spatial, object, goal, scene10, scene90), each with human demos and a language goal. It is the standard testbed for language-con
arXiv:2610.08421v1 Announce Type: new Abstract: A stable grasp does not guarantee kinematically feasible robotic insertion because the object-in-gripper transform may force the robot towards singulari
arXiv:2610.08756v1 Announce Type: new Abstract: The same Gaussian of a 3D Gaussian Splatting model is seen from many views, and these views do not always agree on the class it belongs to. The Gaussian
arXiv:2508.19819v3 Announce Type: replace-cross Abstract: Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly stro
arXiv:2510.14878v3 Announce Type: replace-cross Abstract: We study kernel regression with common rotation-invariant kernels on real datasets including CIFAR-5m, SVHN, and ImageNet. We give a theoretic
arXiv:2610.08715v1 Announce Type: cross Abstract: The following motif is common in spatiotemporal settings: we have a sequence of covariate and label pairs observed for a relatively short, recent time
arXiv:2610.07540v1 Announce Type: new Abstract: Robotic systems often exhibit unstable modes, along which small perturbations and disturbances can cause unbounded growth unless corrected through feedb
arXiv:2610.08670v1 Announce Type: cross Abstract: Language models increasingly act as agents. An agent that says an action is wrong and then takes it anyway is a different failure from one that does n
arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experi
arXiv:2610.07842v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a language model to match a copy of itself conditioned on privileged context. Existing work varies what privil
arXiv:2610.06999v1 Announce Type: new Abstract: Rapid adaptation to a new environment requires a robot to acquire useful knowledge about local objects, states, and interactions from limited experience
arXiv:2610.08689v1 Announce Type: new Abstract: Counterfactual inference in Gaussian-process structural causal models (GP-SCMs) has been developed primarily for continuous endogenous variables, limiti
arXiv:2401.09918v2 Announce Type: replace Abstract: Rule set learning has recently been frequently revisited because of its interpretability. Existing methods have several shortcomings though. First,
arXiv:2610.07515v1 Announce Type: new Abstract: Accurately modeling and tracking the deformation of soft tissue is critical for a wide range of interventional and surgical procedures. However, current
Project Suncatcher is our moonshot exploring whether we can one day host machine learning infrastructure in space 🚀 To do so, we need to know whether our AI hardware can operate in orbit. Can our TPUs
arXiv:2507.02115v3 Announce Type: cross Abstract: Synthesizing second-language (L2) speech is potentially highly valued for L2 language learning experience and feedback. However, due to the lack of L2
arXiv:2610.07464v1 Announce Type: new Abstract: Protective perturbations aim to stop malicious instruction-guided editing of personal photos, but they are optimized and evaluated at the editor's worki
arXiv:2610.08078v1 Announce Type: cross Abstract: Standard causal identification methods often assume no unmeasured confounding and can fail when relevant confounders are unobserved. Proximal causal i
arXiv:2603.27101v2 Announce Type: replace Abstract: Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field ma
arXiv:2610.07936v1 Announce Type: new Abstract: Systematicity, the probabilistic mapping of form to meaning, permeates language at all levels, and sublexical cues have been shown to govern human pseud
arXiv:2610.07473v1 Announce Type: new Abstract: Large language models show promise in clinical reasoning, but psychiatric interviewing requires guiding an evolving conversation. Their ability to carry
arXiv:2508.16821v2 Announce Type: replace Abstract: We introduce PuzzleJAX, a GPU-accelerated puzzle game engine and description language designed to support rapid benchmarking of tree search, reinfor
arXiv:2610.08789v1 Announce Type: cross Abstract: Flow policies have become a standard policy class for learning robot behaviors from demonstrations, but reinforcement learning is still critical for i
arXiv:2610.06936v1 Announce Type: new Abstract: Irregular multivariate time series forecasting is a challenging yet important problem in real-world applications, where observations are often irregular
arXiv:2511.00053v2 Announce Type: replace-cross Abstract: The design of learning objectives is central to training time-series forecasting models. Existing learning objectives such as mean squared err
arXiv:2610.07545v1 Announce Type: new Abstract: We present a fully offline speech-to-speech translation pipeline that runs on a Jetson Nano (4 GB) and corrects its own weak translations without retrai
arXiv:2603.08231v2 Announce Type: replace-cross Abstract: Paralinguistic speech tasks are often considered relatively language-agnostic, as they rely on extralinguistic acoustic cues rather than lexic
arXiv:2602.02140v2 Announce Type: replace Abstract: Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whethe
arXiv:2610.07781v1 Announce Type: new Abstract: Post-training quantization reduces the cost of deploying language-model agents, but its effect on recovery from temporary tool failures can depend on ho
arXiv:2610.08216v1 Announce Type: new Abstract: Multimodal vision-language systems typically fuse image and text embeddings through classical operators such as concatenation, attention, bilinear pooli
arXiv:2510.11593v3 Announce Type: replace-cross Abstract: For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across mu
I've always been kind of into computers since I was young. And then when film started to move from analog film to digital, I became more interested in that aspect of it. And the visual effects workflo