Knowledge catalogue
arXiv:2606.23293v1 Announce Type: new Abstract: 6D pose estimation is a key task in computer vision and embodied AI, widely used in robotic manipulation, augmented reality, etc. Existing methods direc
arXiv:2602.06226v2 Announce Type: replace Abstract: The ubiquity of monocular videos capturing daily hand-object interactions presents a valuable resource for embodied intelligence. While 3D hand reco
arXiv:2606.21993v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) face driving scenarios ranging from routine traffic to rare events. To assess safety it is crucial to reproduce these scenar
arXiv:2512.13491v3 Announce Type: replace-cross Abstract: We inspect the deductive connection between the neural scaling law and Zipf's law -- two statements discussed in machine learning and quantita
GLM 5.2 is already top 10 on OpenRouter this week, sitting right next to Opus 4.8. it's also been really strong in Deep Agents across long-horizon coding, big context, tool use, and verifying work bef
GLM-5.2 is available in Perplexity's Agent API. Just tested it, and it's powerful when paired with the Search SDK inside a sandbox. - Spin up a sandbox environment - Call the web search tool (people s
arXiv:2606.22917v1 Announce Type: new Abstract: Learning instability is a long-standing problem across machine learning, but it is especially acute in the overparameterized regime that defines modern
arXiv:2606.19636v2 Announce Type: replace Abstract: Math and science reasoning benchmarks rely on pass@k, the fraction of sampled chains that reach gold, as the canonical per-example difficulty signal
arXiv:2606.20962v1 Announce Type: new Abstract: High-performing human-human teams learn intelligent and efficient communication and coordination strategies to maximize their joint utility. These teams
arXiv:2606.21136v1 Announce Type: new Abstract: Learning accurate value functions plays a decisive role for reinforcement learning (RL) agents to solve long-horizon, complex tasks. Conventional tempor
Companies are asking how to build specialized AI that fits with the way their workflows actually run. The first wave of enterprise AI was about access. Companies experimented with new frontier and ope
arXiv:2606.22971v1 Announce Type: cross Abstract: Occupancy prediction at voxel-level granularity is essential for safe robotic navigation and interaction in complex environments. Existing occupancy d
i dont think anyone is correctly doing the math around how SpaceX, the NeoCloud+NeoLab, is currently going to market? SpaceX has already recouped about HALF its investment in Cursor, in compute deals.
arXiv:2405.10231v3 Announce Type: replace-cross Abstract: Social media influencers account for a growing share of marketing worldwide. We demonstrate the existence of a novel form of market failure in
arXiv:2606.16878v3 Announce Type: replace Abstract: Retail marketing measurement increasingly requires granular campaign-level insights without relying on user-level tracking. However, the two dominan
arXiv:2606.19538v2 Announce Type: replace-cross Abstract: Convolutional networks, recurrent networks, and transformers each encode different inductive biases -- locality, sequential memory, and conten
arXiv:2509.22307v2 Announce Type: replace Abstract: Lightweight 3D medical image segmentation remains constrained by a fundamental extit{``efficiency / robustness conflict''}, particularly when proces
arXiv:2606.22113v1 Announce Type: new Abstract: Generalizing manipulation policies across robot embodiments remains difficult because standard policies entangle task reasoning with embodiment-specific
arXiv:2606.21358v1 Announce Type: new Abstract: Supervised video pretraining is a common transfer learning practice for improving downstream action recognition performance. However, it requires large-
arXiv:2606.20729v1 Announce Type: cross Abstract: Quantum chemistry simulations underpin modern materials discovery, yet their impact is limited by steep computational cost and dependence on fixed app
arXiv:2606.23110v1 Announce Type: cross Abstract: Outer-loop link adaptation (OLLA) is widely deployed in 5G NR to track channel variations, yet its reliance on first-order, single-bit feedback degrad
arXiv:2606.22662v1 Announce Type: new Abstract: Forecasting chaotic dynamical systems such as the Lorenz attractor is notoriously difficult: small numerical errors are amplified exponentially over lon
arXiv:2304.12319v2 Announce Type: replace-cross Abstract: Recently, numerous end-to-end optimized image compression neural networks have been developed and proved themselves as leaders in rate-distort
arXiv:2606.23489v1 Announce Type: cross Abstract: Meshes are among the most common 3D scene representations, but directly generating meshes is challenging because the representation contains important
arXiv:2606.21943v1 Announce Type: new Abstract: Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a nar
arXiv:2606.21135v1 Announce Type: new Abstract: Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into sing
arXiv:2606.20920v1 Announce Type: new Abstract: Characterizing non-Gaussian posterior distributions in partially observed high-dimensional nonlinear systems remains a fundamental challenge in data ass
arXiv:2606.18658v2 Announce Type: replace Abstract: Learning unsupervised representations of medical imaging cohorts can reveal clinically meaningful prototypes without expert labels, which are often
arXiv:2606.22352v1 Announce Type: new Abstract: Dictionary learning has long been studied from both optimization and probabilistic perspectives. While formulations with element-wise sparsity regulariz
arXiv:2606.22101v1 Announce Type: cross Abstract: Precision medicine in ophthalmology requires accurate longitudinal predictions, but the fragmented nature of multimodal clinical data remains a barrie
arXiv:2606.21396v1 Announce Type: new Abstract: Robot-Assisted Surgery is integral to modern minimally invasive procedures, with automation emerging as the next frontier to enhance precision and reduc
arXiv:2606.23256v1 Announce Type: new Abstract: The increasing maturity of embodied AI platforms has driven a growing interest in procedural video representation learning to support intelligent assist
arXiv:2603.24196v2 Announce Type: replace-cross Abstract: Neural Physics recasts local discretisations of partial differential equations (PDEs) as fixed convolutional operators, providing a physics-pr
arXiv:2606.22647v1 Announce Type: cross Abstract: Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Lar
arXiv:2606.23361v1 Announce Type: new Abstract: Backdoor attacks on molecular graph neural networks (GNNs) are typically evaluated as abstract graph edits, but real molecular learning pipelines do not
arXiv:2606.21756v1 Announce Type: cross Abstract: In this work, we present SemanticVessel, a dataset for fine-grained brain vessel segmentation in computed tomography angiography scans. Based on the d
arXiv:2606.23448v1 Announce Type: new Abstract: Deep learning methods have achieved state-of-the-art in time series forecasting, yet their accuracy varies considerably across samples, as some instance
arXiv:2606.20918v1 Announce Type: new Abstract: Accurate short-term electricity demand forecasting is critical for reliable power system operation, energy market planning, and infrastructure optimizat
arXiv:2606.21099v1 Announce Type: new Abstract: Variational inference (VI) is a powerful method for principled posterior inference for scientific inverse imaging. VI learns the posterior distribution,
arXiv:2606.13589v2 Announce Type: replace Abstract: We present Simplex-Constrained Sparse Bagging (SCSB), a mathematically rigorous framework for post-training compression and probability calibration
arXiv:2606.22308v1 Announce Type: cross Abstract: Lesion segmentation in breast ultrasound involves two related challenges. In images with lesions, speckle noise, low tissue contrast, and posterior ac
arXiv:2606.21973v1 Announce Type: new Abstract: Physiological signals such as EEG, ECG, and PPG are widely used in clinical monitoring. Recent self-supervised learning (SSL) methods offer an attractiv
arXiv:2606.23254v1 Announce Type: new Abstract: Visual text editing aims to precisely modify text in images and videos while preserving stylistic consistency and visual realism. Despite significant ad
arXiv:2606.20856v1 Announce Type: new Abstract: Multi-view surface reconstruction is a core problem in computer vision. One prominent line of work represents the surface implicitly as a signed distanc
arXiv:2507.03318v3 Announce Type: replace Abstract: Explainable artificial intelligence approaches accelerate drug discovery by improving molecular representation learning, identifying key molecular s
arXiv:2606.23477v1 Announce Type: cross Abstract: Over the past decade, deep neural networks (DNNs) have achieved remarkable success on complex machine-learning tasks, yet the theoretical foundations
arXiv:2606.21866v1 Announce Type: new Abstract: Co-design of legged robots with elastic elements is challenging due to the non-differentiability of contact dynamics and mechanism engagement. This pape
arXiv:2606.20864v1 Announce Type: cross Abstract: Developing robust intrusion detection systems (IDS) for IoT environments requires large, labeled datasets capturing realistic traffic distributions ac
arXiv:2606.17055v2 Announce Type: replace Abstract: The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based
arXiv:2606.21189v1 Announce Type: new Abstract: Non-stationary partial differential equations (PDEs) arise throughout scientific computing, where the dominant frequency content and energy distribution
arXiv:2505.11579v3 Announce Type: replace-cross Abstract: As AI systems evolve from static tools to dynamic agents, traditional categorical governance frameworks -- based on fixed risk tiers, levels o
arXiv:2602.15136v2 Announce Type: replace-cross Abstract: We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achi
arXiv:2606.23503v1 Announce Type: new Abstract: Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where
arXiv:2606.22787v1 Announce Type: new Abstract: Current end-to-end multi-view 3D reconstruction methods achieve impressive results, but rely on a restrictive static assumption: the scenes is entire di
arXiv:2606.22371v1 Announce Type: cross Abstract: Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existi
GLM-5.2 represents a significant advancement in open-source AI agent capabilities, marking a notable improvement over previous versions in terms of performance and functionality. The article from Inte
I have been trying Sakana Fugu Ultra-high and, first, it is incredibly slow: my typical coding tests (shaders, interactive scenes) take 30 minutes to run And the results are... fine. It does not match
🐡 Sakana Fugu リリース 🐡 マルチエージェントを指揮する、一つのモデル ブログ：https://sakana.ai/fugu-release/#Japanese 本日、Sakana AIは新しいプロダクト「Sakana Fugu」の提供を開始しました。Sakana Fuguは、最先端のモデル群からなるマルチエージェントシステム全体を、単一のモデルAPIとして提供します。 難しいタスク
Tried & liked it on http://archive.tw. Fugu Ultra pairs well as a advisor & planner with Composer 2.5. For scope/architecture, it’s on par with Fable orchestration. Advisor doesn’t slow the loop if th
Use Case 4: Computer Aided Design of Mechanical Iris Can an AI generate precise, functional mechanical designs? We tasked Fugu Ultra with creating a mechanical iris in CAD, similar to a camera apertur