Knowledge catalogue
arXiv:2609.20575v1 Announce Type: cross Abstract: Learning visual policies for locomotion and manipulation requires coordinating contact with the environment and can incur substantial computation and
arXiv:2609.20249v1 Announce Type: new Abstract: Deep knowledge tracing (DKT) models implicitly decide which students an adaptive system believes have mastered a skill, yet almost all evidence on their
arXiv:2609.20130v1 Announce Type: cross Abstract: Recent memory-augmented repository-level program repair methods reuse historical repair experiences to improve LLM-based issue resolution. However, ou
arXiv:2609.19164v1 Announce Type: new Abstract: In verifier-style RLVR, group-relative optimization often treats advantage scale as an implementation detail. This paper separates two low-variance case
arXiv:2609.19802v1 Announce Type: new Abstract: Physical teleoperation integrates human cognitive flexibility with robotic precision, yet demanding manipulation tasks frequently induce severe cognitiv
arXiv:2609.19538v1 Announce Type: new Abstract: Low-altitude wireless networks (LAWNs) are emerging as a key infrastructure for heterogeneous unmanned aerial systems that support concurrent services w
arXiv:2609.20301v1 Announce Type: new Abstract: AI agents increasingly orchestrate long-running activities with users, tools, and system resources for days and weeks. To improve agent quality, safety,
arXiv:2609.20761v1 Announce Type: cross Abstract: World Action Models (WAMs) advance beyond conventional visuomotor policies by jointly predicting future world states and robot actions, enabling the p
arXiv:2512.06438v4 Announce Type: replace Abstract: The generation of high-fidelity, animatable 3D human avatars remains a core challenge in computer graphics and vision, with applications in VR, tele
arXiv:2609.20325v1 Announce Type: new Abstract: Agricultural image understanding requires fine-grained recognition of plant diseases, pests, crop structures, and botanical species under complex real-w
arXiv:2609.20271v1 Announce Type: new Abstract: Reliable and low-latency communication is a fundamental requirement for smart city services and Industry 4.0 applications enabled by NR-V2X networks. Ho
arXiv:2609.20263v1 Announce Type: new Abstract: The proliferation of generative video models has shifted the practical detection threat from fully fabricated clips to partially manipulated footages. A
arXiv:2609.20059v1 Announce Type: cross Abstract: AI systems can strengthen democracy by supporting deliberation at scale by addressing cognitive, social, platform-design, and market-driven frictions,
arXiv:2609.19793v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable inte
arXiv:2609.19722v1 Announce Type: cross Abstract: Large language models are being integrated into malware triage workflows as reasoning components that summarize static evidence and produce analyst-fa
arXiv:2609.19748v1 Announce Type: new Abstract: In many application domains, such as student dropout, insurance fraud, loan approval, and machine failures, several labelled public datasets are availab
arXiv:2609.19518v1 Announce Type: new Abstract: We present AMB3R-SLAM, a real-time monocular SLAM system capable of reconstructing kilometer-scale trajectories over 10k frames on a single consumer-gra
arXiv:2601.15417v2 Announce Type: replace-cross Abstract: We propose Ambient Dataloops, an iterative framework for refining datasets that makes it easier for diffusion models to learn the underlying d
arXiv:2609.19915v1 Announce Type: new Abstract: Amortizing physics-informed neural networks (PINNs) across related PDEs requires describing each equation to a reusable solver. Coefficient vectors enco
arXiv:2609.20541v1 Announce Type: new Abstract: Large language models can report a numerical confidence together with generated content, but it is unclear whether this report is more than calibrated r
arXiv:2609.19519v1 Announce Type: new Abstract: Language-model agents are increasingly asked to carry out work spanning days or weeks, such as an operations remediation or a research programme. Such a
arXiv:2609.20804v1 Announce Type: new Abstract: Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing work t
arXiv:2609.19973v1 Announce Type: new Abstract: Event cameras provide low-latency, high temporal resolution perception for real-time vision tasks such as robotics.The novel circuitry (i.e. asynchronou
arXiv:2506.12374v3 Announce Type: replace-cross Abstract: Natural-language manipulation instructions specify the task goal but leave the underlying robot trajectory unspecified. We present AntiGroundi
arXiv:2609.20107v1 Announce Type: new Abstract: Visuomotor policies for multi-fingered dexterous manipulation are highly sensitive to camera viewpoint shifts. To achieve view invariance, recent method
arXiv:2609.20106v1 Announce Type: new Abstract: Robotic reward models evaluate task execution from visual observations, but their predictions can change with camera viewpoint and occlusion even when t
arXiv:2602.03128v2 Announce Type: replace Abstract: Multi-agent LLM frameworks are data-intensive systems that govern how agents orchestrate tasks, manage state, and coordinate decisions. These archit
arXiv:2604.01432v3 Announce Type: replace Abstract: Citation granularity -- whether to cite individual sentences, paragraphs, or documents -- is a critical design choice in attributed generation. Whil
arXiv:2412.18783v3 Announce Type: replace Abstract: As demand from the film and gaming industries for 3D scenes with target styles grows, the importance of advanced 3D stylization techniques increases
arXiv:2609.20034v1 Announce Type: cross Abstract: We present Astronex-World 1.0, an open controllable video world-model foundation. Given a text prompt (text-to-video) or an initial observation (image
arXiv:2609.19194v1 Announce Type: new Abstract: AthenaZero is a bimanual manipulator designed to minimize inertia without compromising control authority. By utilizing quasi-direct drive actuation and
arXiv:2609.19325v1 Announce Type: cross Abstract: Safety tuning pipelines judge only the final answer, which makes it difficult to distinguish robust refusal from two undesirable shortcuts: blanket re
arXiv:2609.19873v1 Announce Type: new Abstract: Email spam and phishing attacks remain a critical security threat. Adversaries increasingly exploit large language models to craft contextually convinci
arXiv:2609.19527v1 Announce Type: cross Abstract: Air-ground transportation research increasingly relies on co-simulation, yet constructing scenarios remains labor-intensive and difficult to validate.
arXiv:2609.19754v1 Announce Type: new Abstract: LLM agents have recently shown promise in automating machine learning engineering by editing model and training code under execution feedback. Data, how
arXiv:2609.20509v1 Announce Type: new Abstract: For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a que
arXiv:2603.25836v2 Announce Type: replace Abstract: In low-resource multilingual speech-to-text translation, uniform architectural sharing across languages frequently introduces representation conflic
arXiv:2603.19375v2 Announce Type: replace-cross Abstract: Membership inference attacks (MIAs), which enable adversaries to determine whether specific data points were part of a model's training datase
arXiv:2609.19991v1 Announce Type: cross Abstract: Omni models can describe video content, but can they locate events in time, preserve event order, and judge audio-visual synchronization? We introduce
arXiv:2609.20605v1 Announce Type: new Abstract: Recent factor graph approaches to continuum robot state estimation have been successful for quasi-static applications and spatiotemporal estimation usin
arXiv:2609.19437v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely used for optimizing expensive black-box functions, yet many real-world optimization problems contain substantially
arXiv:2609.19965v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to legal and criminal justice tasks, yet existing work focuses almost exclusively on post-arrest s
arXiv:2609.20223v1 Announce Type: new Abstract: We study weakly supervised incremental telecom fraud detection from raw telephone audio, where training provides only conversation-level labels and pred
arXiv:2512.13142v5 Announce Type: replace Abstract: People use LLMs for reproductive-health questions, including abortion-related support. A response can sound supportive while answers reinforce harmf
arXiv:2609.19989v1 Announce Type: new Abstract: The widespread adoption of LLMs has led to escalating content compliance risks. Prior works have contributed to addressing these risks in the English co
arXiv:2609.19767v1 Announce Type: new Abstract: True machine intelligence requires transcending passive pixel registration to master top-down functional reasoning over absent information via visual ne
arXiv:2609.19934v1 Announce Type: new Abstract: Depth-recurrent language models iteratively apply a small layer stack, decoupling per-token compute from distinct parameter count. To determine whether
arXiv:2609.19842v1 Announce Type: new Abstract: Effective EEG decoding requires representations that preserve organization among channels, local waveform dynamics, and long-range temporal context. Exi
arXiv:2609.19669v1 Announce Type: new Abstract: Adversarial patches to Vision-Language-Action (VLA) policies can cause both immediate action corruption and persistent state effects that remain after t
arXiv:2609.20641v1 Announce Type: cross Abstract: Physics-informed neural networks and finite element methods provide two different paradigms for the numerical approximation of partial differential eq
arXiv:2609.19966v1 Announce Type: new Abstract: Synthetic image and mask pairs can alleviate scarce colonoscopy annotations, but realistic synthesis requires preserving the supplied lesion while gener
arXiv:2609.19875v1 Announce Type: new Abstract: We propose a new probabilistic model for general-purpose medical image registration that builds upon the mutual information registration criterion. It c
arXiv:2609.19881v1 Announce Type: new Abstract: Embodied visual perception relies on temporally coherent visual experience accumulated through continuous engagement with the environment. However, coll
arXiv:2609.19180v1 Announce Type: new Abstract: Language models face unique challenges in analyzing interdisciplinary scientific research literature. In biophysics research, faithful answers require g
arXiv:2609.19242v1 Announce Type: new Abstract: Block diffusion language models (BDLMs) combine autoregressive dependencies across blocks with parallel denoising within blocks, but long-context traini
arXiv:2602.16870v2 Announce Type: replace Abstract: The Boreas Road Trip (Boreas-RT) dataset extends the multi-season Boreas dataset to new and diverse locations that pose challenges for modern autono
arXiv:2609.20147v1 Announce Type: cross Abstract: Cortical hypometabolism measured by Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a highly sensitive biomarker for dementia diagnosis.
arXiv:2509.25248v2 Announce Type: replace-cross Abstract: Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for
arXiv:2607.16682v2 Announce Type: replace-cross Abstract: The widespread adoption of high-level deep learning libraries, while accelerating model development, has increasingly abstracted away the inte
arXiv:2609.19422v1 Announce Type: cross Abstract: Burnout is a chronic occupational syndrome, and open source is close to a worst case for it: maintainers absorb unbounded demand with no manager to re