Knowledge catalogue
arXiv:2608.15784v1 Announce Type: new Abstract: Soft piezoresistive strain sensors are one of the most common sensing solutions for wearable and soft robotic applications due to their flexibility and
arXiv:2608.15951v1 Announce Type: new Abstract: We study when a wearable stress system should surface a prediction rather than change it. In low-stakes reflection and summary settings, aggregate accur
arXiv:2608.15269v1 Announce Type: new Abstract: Long-horizon robot policies require compact access to recent observations and reusable experience without expanding the vision-language-action (VLA) con
Reminder that the data that feeds large language models – and thereby influences the world - can change at any moment, without warning. looks like reddit is almost wiped from chatgpt sources the query
arXiv:2608.16484v1 Announce Type: new Abstract: Remote-sensing systems usually describe urban content with detection boxes, semantic masks, or vector boundaries. Such outputs locate classes and suppor
arXiv:2608.16087v1 Announce Type: new Abstract: Removing wearables from physiological monitoring also removes their supervision: the signal indicating where and when a stress response occurred. Contac
arXiv:2608.16011v1 Announce Type: new Abstract: We introduce ReRef-3D, a benchmark for language-guided placement in 3D scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning
arXiv:2608.15889v1 Announce Type: cross Abstract: Currency arbitrage (CA) involves trading currencies in cycles to exploit discrepancies in market valuations. Quadratic unconstrained binary optimizati
arXiv:2608.14685v1 Announce Type: new Abstract: Knowledge distillation (KD) is widely used to transfer the capabilities of large language models (LLMs) to smaller students, but existing objectives oft
arXiv:2412.18911v3 Announce Type: replace-cross Abstract: Diffusion Transformers (DiT) have become the dominant methods in image and video generation yet still suffer substantial computational costs.
arXiv:2608.14947v1 Announce Type: new Abstract: Detecting opioid craving from wearable physiological signals is critical yet difficult, with the potential to support proactive interventions for indivi
arXiv:2608.16005v1 Announce Type: new Abstract: This paper studies the problem of molecule-text alignment, which aims to project molecules and their textual descriptions into a joint latent space for
arXiv:2608.16111v1 Announce Type: cross Abstract: Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they a
arXiv:2608.16786v1 Announce Type: new Abstract: Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We stud
arXiv:2608.15938v1 Announce Type: new Abstract: Action chunking --- the practice of predicting a sequence of actions and executing a prefix open-loop --- has emerged as a key enabler of recent progres
arXiv:2608.16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and
arXiv:2606.06227v3 Announce Type: replace-cross Abstract: Reinforcement-learning controllers optimise specified rewards, but in physical systems those rewards often capture only part of the true contr
arXiv:2608.15555v1 Announce Type: new Abstract: Video models are increasingly used to predict what happens next in a scene, yet the metrics commonly used to compare their outputs say little about whet
arXiv:2608.14660v1 Announce Type: cross Abstract: This study proposes a ring-based SpatialTransformer to learn how building uses at different distances from a railway station interact to generate pede
arXiv:2507.20776v3 Announce Type: replace Abstract: Remote sensing (RS) images from multiple modalities and platforms exhibit diverse details due to differences in sensor characteristics and imaging p
arXiv:2608.16480v1 Announce Type: cross Abstract: We present RISE (Roadside Infrastructure Sequence Understanding and Evaluation), a framework spanning metric 3D tracking and structured vision-languag
arXiv:2608.14991v1 Announce Type: new Abstract: Cloud-hosted vision-language models (VLMs) offer greater contextual reasoning capabilities than smaller onboard models, but frequent visual uploads incr
arXiv:2608.15817v1 Announce Type: new Abstract: The growing ecosystem of large language models (LLMs) offers huge potential to optimize performance-cost trade-offs. However, their heterogeneous capabi
arXiv:2608.15680v1 Announce Type: cross Abstract: Vision-language-action (VLA) models improve robotic manipulation but remain vulnerable to compounding errors, scene changes, and off-trajectory states
arXiv:2512.23649v4 Announce Type: replace-cross Abstract: Humans learn locomotion through visual observation, interpreting visual content first before imitating actions. However, state-of-the-art huma
arXiv:2608.16195v1 Announce Type: new Abstract: Achieving human-level competitive intelligence and physical agility in humanoid robots remains a profound challenge, particularly in contact-rich and hi
arXiv:2608.16433v1 Announce Type: new Abstract: Traversal Risk Graphs (TRGs) provide a compact, terrain-aware representation for global navigation, but native TRG costs are computed over circular node
arXiv:2608.15251v1 Announce Type: new Abstract: Integrated 3D reconstruction from aerial-ground images is essential for generating high-precision urban 3D models, yet severe variations in viewpoint, s
arXiv:2507.12399v3 Announce Type: replace Abstract: Test-time scaling aims to improve language model performance by leveraging additional compute during inference. Many works have empirically studied
arXiv:2608.15785v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel-view synthesis but remains limited on GPUs at high resolutions. Through a stage-wise Roofline chara
arXiv:2608.15946v1 Announce Type: new Abstract: Rerouting the tendon path in tendon driven continuum manipulators (TDCMs) enables a broad range of deformation modes. This work presents a Reconfigurabl
arXiv:2608.15621v1 Announce Type: new Abstract: Human Activity Recognition (HAR) with self-administered wearables, such as at-home rehabilitation and exercise monitoring, often requires reattaching in
arXiv:2608.14682v1 Announce Type: new Abstract: Real-world time series inherently intertwine global periodic structures with localized non-stationary variations. Existing approaches process these hete
arXiv:2608.15787v1 Announce Type: cross Abstract: Two Mixture-of-Experts (MoE) forward passes can share every weight yet route the same token through different experts. This creates a possible blind s
arXiv:2608.15694v1 Announce Type: cross Abstract: Conditional image-to-image generators are single-shot: they map input features to an output in one forward pass and treat it as final, with no opportu
NVIDIA cuML and cuVS now support multi‑GPU all‑neighbors kNN graph construction in UMAP, enabling end‑to‑end scaling of the dimensionality reduction algorithm to hundreds of billions of vectors. The i
I managed to run the 143–144 GiB DeepSeek-V4-Flash-0731 UD-Q4_K_XL GGUF on four RTX 3060 12GB cards while keeping a 360k–376k context window. Hardware: CPU: Intel Core i9-10920X, 12C/24T RAM: 128 GB D
arXiv:2608.15018v1 Announce Type: new Abstract: Deploying large language models (LLMs) for inference on edge devices is challenging due to severe memory and bandwidth constraints. While speculative de
arXiv:2608.15920v1 Announce Type: cross Abstract: Intelligent systems are increasingly deployed in safety-critical settings with black-box controllers, including neural networks. The properties and be
arXiv:2608.15075v1 Announce Type: new Abstract: RS-LVLMs have advanced multimodal understanding of Earth observation imagery, yet their performance is fundamentally constrained by high-resolution proc
arXiv:2608.16081v1 Announce Type: new Abstract: Open-weight and frontier vision-language models (VLMs) perform well on general image understanding, but their ability to interpret fine-grained hand ges
arXiv:2608.15429v1 Announce Type: new Abstract: Prior embedding models for sequential recommendation typically operate within a homogeneous action space, limiting their ability to capture cross-surfac
arXiv:2608.15336v1 Announce Type: new Abstract: Current surgical scene graph generation methods depend on dense multi-modal supervision and specialized hardware (synchronized RGB-D sensors, calibratio
Alex Heath / Time: Sam Altman says OpenAI's decision to pace its AI development was caused by a collection of research observations showing “various degrees of misalignment” — “I think it is a good ti
arXiv:2608.15360v1 Announce Type: cross Abstract: While Parameter-Efficient Fine-Tuning (PEFT) has substantially reduced the hardware cost of adapting Large Language Models (LLMs) by decreasing the nu
arXiv:2608.16249v1 Announce Type: new Abstract: Machine unlearning in Large Language Models (LLMs) faces a critical trade-off between erasing target knowledge and preserving general utility. We propos
arXiv:2608.15652v1 Announce Type: new Abstract: The rapid proliferation of generative models raises the model attribution problem: given only an image, can we determine which model produced it? Existi
arXiv:2608.15144v1 Announce Type: cross Abstract: Posterior sampling with a pretrained diffusion prior is governed by a conditional score whose intermediate likelihood component is generally intractab
arXiv:2608.16287v1 Announce Type: new Abstract: Joint-embedding predictive world models plan by scoring predicted terminal embeddings against a goal embedding using a cost defined on the representatio
arXiv:2608.15863v1 Announce Type: cross Abstract: Operating household appliances requires long-horizon planning that is state-dependent and robust to disturbances, yet existing large models fall short
arXiv:2608.16041v1 Announce Type: new Abstract: We introduce ScenarioCharacterization, an open-source framework for automated, dataset-agnostic profiling of driving scenarios in trajectory datasets. O
arXiv:2608.15834v1 Announce Type: new Abstract: Tool-calling LLM agents navigate unfamiliar codebases with a handful of generic primitives for listing, reading and searching files (ls, cat, grep). A k
arXiv:2608.15567v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) enables the deployment of large language models under tight memory budgets, but accuracy often collapses at
arXiv:2608.15043v1 Announce Type: new Abstract: Video world models are increasingly used as simulators for planning and embodied decision making, yet improving them at inference time introduces a subt
arXiv:2303.07152v3 Announce Type: replace-cross Abstract: Achieving optimal statistical performance while ensuring the privacy of personal data is a challenging yet crucial objective in modern data an
arXiv:2608.15289v1 Announce Type: new Abstract: Autonomous UAVs enter enclosed environments such as caves and collapsed structures that confine the vehicle and degrade perception. Conformal prediction
arXiv:2608.16251v1 Announce Type: new Abstract: Face recognition templates are compact identity representations, yet they also encode rich semantic information about facial appearance. Prior work has
arXiv:2608.15824v1 Announce Type: new Abstract: Adam retains a moving average of past squared gradients in its denominator, but the optimization cost of this memory is not well understood. We show tha
arXiv:2608.15101v1 Announce Type: new Abstract: Policy evaluation often estimates direct benefits and costs while treating the institutional environment as fixed. In practice, a policy changes the sys
arXiv:2608.16187v1 Announce Type: cross Abstract: AI-assisted development tools generate vulnerable code at significant rates, yet few automated mechanisms exist to detect, enrich, fix, and verify sec