Knowledge catalogue
arXiv:2607.06233v1 Announce Type: new Abstract: LLM-powered data agents are playing an increasingly important role in data-driven decision making. However, existing data agents struggle to generalize
arXiv:2607.05685v1 Announce Type: cross Abstract: Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive
arXiv:2607.06523v1 Announce Type: new Abstract: Long-context language model inference is increasingly limited by the memory bandwidth and capacity required to store key-value caches, yet existing comp
arXiv:2607.05787v1 Announce Type: new Abstract: Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. A
arXiv:2607.05439v1 Announce Type: new Abstract: Many all-atom generative protein models can in principle design large multimeric complexes by jointly modelling all chains, but their quadratic token- a
arXiv:2607.06296v1 Announce Type: cross Abstract: This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The
arXiv:2607.06063v1 Announce Type: cross Abstract: Eco-acoustic monitoring generates vast volumes of audio data, making active learning a promising approach for reducing annotation effort while efficie
arXiv:2507.10177v2 Announce Type: replace-cross Abstract: Although Large Language Models (LLMs) have demonstrated significant advancements in natural language processing tasks, their effectiveness in
arXiv:2607.05883v1 Announce Type: new Abstract: In dual-arm dexterous teleoperation, cross-platform generalization of motion retargeting and interactivity of grasping are crucial. However, the heterog
arXiv:2607.06256v1 Announce Type: new Abstract: Long-horizon household tasks require robots to compose many language-conditioned skills, yet the boundary between consecutive skills is rarely explicit.
Didn't even have time to write up thoughts on my early access to the new GPT voice, but it is really good & much closer to the science fiction experience of talking to AI (in part because it is much s
arXiv:2607.05866v1 Announce Type: cross Abstract: Under a fixed privacy budget, the utility of differentially private (DP) training is ultimately determined by its optimization efficiency. Standard fi
arXiv:2606.08048v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer substantial speed advantages through parallel decoding, but the lack of token dependencies limits generation qu
arXiv:2607.05995v1 Announce Type: cross Abstract: We propose a novel approach to mine patterns in spatio-temporal event data based on discovering frequent closed embedded sub-Directed Acyclic Graphs (
arXiv:2607.06320v1 Announce Type: cross Abstract: We present the dithered Gaussian mechanism, a novel alternative to the discrete Gaussian mechanism for differential privacy that discretizes the priva
arXiv:2607.05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electr
arXiv:2607.05645v1 Announce Type: new Abstract: Deep-learning-based climate downscaling aims to learn relationships from historical low-resolution (LR) and high-resolution (HR) climate data to generat
arXiv:2607.06503v1 Announce Type: new Abstract: Large language model (LLM) agents solving multi-step tasks frequently commit to trajectories that are doomed to fail, yet continue to consume substantia
arXiv:2603.19216v2 Announce Type: replace-cross Abstract: Understanding and generating 3D objects as compositions of meaningful parts is fundamental to human perception and reasoning. However, most te
arXiv:2607.05908v1 Announce Type: new Abstract: Real-world data distributions evolve over time, inducing temporal distribution shift that can substantially degrade the reliability of deployed machine
arXiv:2607.06328v1 Announce Type: new Abstract: The increasing adoption of end-to-end learning for autonomous driving introduces increased model complexity and opacity, raising the risk of learning un
arXiv:2607.06326v1 Announce Type: new Abstract: Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-l
Elon Musk posted a statement indicating openness to critical feedback, suggesting a receptive attitude toward constructive criticism. This tweet reflects Musk's public stance on accepting input and po
arXiv:2607.06507v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) acquires evidence sequentially, with each new document potentially revealing missing facts, bridge entiti
arXiv:2607.05544v1 Announce Type: new Abstract: Trajectory planning strongly influences tracking accuracy, actuator demand, and overall execution behavior in robotic manipulators. Classical planners s
arXiv:2607.06165v1 Announce Type: new Abstract: Omni-directional (360{eg}) cameras provide embodied agents with a holistic view of their surroundings, making them suited for directional reasoning in t
arXiv:2607.06258v1 Announce Type: new Abstract: Is word acquisition in children uneven with respect to semantic and lexical categories? To answer this question, we model early language learning as a s
arXiv:2607.06105v1 Announce Type: cross Abstract: High-resolution RGB imagery acquired from low-altitude UAV surveys was processed through a modular pipeline incorporating transformer-based semantic s
arXiv:2607.06217v1 Announce Type: new Abstract: Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficie
arXiv:2607.05665v1 Announce Type: new Abstract: This study proposes a neural network-based transfer learning framework for modeling the dynamics of soft, fin-actuated underwater robots. We focus on mo
arXiv:2607.06468v1 Announce Type: new Abstract: We introduce EgoPolice, a carefully curated dataset of real, egocentric police-civilian interactions, sourced from publicly available body-worn camera v
Elon Musk reveals the environmentalist viewpoint he says has become total madness 'There are 8 billion people on Earth and it would be better if there were none. I'm like, 'hey buddy, you can start wi
arXiv:2607.06565v1 Announce Type: cross Abstract: Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction re
arXiv:2607.06563v1 Announce Type: new Abstract: Traditional data physicalization is often static and disconnected from real environments, limiting its ability to convey embodied spatial dynamics and e
arXiv:2607.05457v1 Announce Type: cross Abstract: Deep neural networks often contain substantial hidden-state redundancy, but most compression methods operate directly on weights, neurons, or quantise
The next generation of AI is evolving from a tool into a platform where models, applications, and human workflows converge to create integrated operating environments capable of automating tasks and e
arXiv:2607.05933v1 Announce Type: cross Abstract: Dynamic Voltage Frequency Scaling (DVFS) on resource-constrained embedded GPU platforms is essential for energy-efficient small language model (SLM) f
arXiv:2607.06150v1 Announce Type: new Abstract: Reliable seam segmentation is essential for autonomous robotic welding in construction, where harsh illumination, specular reflections, and thin weld ge
arXiv:2607.06230v1 Announce Type: cross Abstract: Parameterized quantum circuits (PQCs) are increasingly used as policies and value functions in quantum reinforcement learning, yet it remains unclear
Enterprises don’t just need agents that perform. They need agents they can shape, govern and improve as their business evolves. That’s the idea behind our work with LangChain. Read more: https://nvda.
arXiv:2607.06497v1 Announce Type: new Abstract: We introduce EntroPath, a manifold learning method that recovers geodesic geometry from data graphs through ensembles of diffusion paths. Many existing
arXiv:2607.05559v1 Announce Type: new Abstract: Foundation machine learning force fields (MLFFs) such as MACE-MP-0 and UMA cover broad chemical space at near density functional theory (DFT) accuracy.
arXiv:2607.06327v1 Announce Type: cross Abstract: Uncertainty estimation (UE) enables LLM-powered systems to recognize when to abstain, yet existing research has predominantly focused on English. We p
arXiv:2602.11711v2 Announce Type: replace-cross Abstract: This article addresses the issue of estimating observation parameters (response and error parameters) in inverse problems. The focus is on cas
arXiv:2607.05638v1 Announce Type: cross Abstract: Teams deploying large language models in business contexts need evaluation systems, yet most treat evaluation as static model selection: run benchmark
arXiv:2607.05462v1 Announce Type: cross Abstract: As AI agents are incorporated into life science workflows, the capabilities that speed discovery might also enable misuse. We present BioSecBench-Refu
arXiv:2607.06125v1 Announce Type: cross Abstract: Neural decompilation is increasingly studied as a code-generation problem, yet its evaluation methodology remains underdeveloped for modern languages.
Entire Inc., the developer-platform startup founded by former GitHub Chief Executive Thomas Dohmke, today launched a preview of a distributed Git network built to let artificial intelligence coding ag
Excited to release Grok 4.5 with @SpaceXAI. It's an Opus-class model that's fast and low cost. It's a significant step up over any model we've developed so far, including Composer 2.5, and has become
Excited to team up with partners across the AI infrastructure + enterprise ecosystem. @EY_US @baseten @FireworksAI_HQ @nebiusai @CrusoeAI @DeepInfra @togethercompute Introducing the NemoClaw Deep Agen
arXiv:2607.05452v1 Announce Type: new Abstract: Time series forecasters that use exogenous covariates are fragile in deployment: when those covariates are noised, temporally misaligned, or missing, st
arXiv:2505.15516v3 Announce Type: replace-cross Abstract: While eXplainable AI (XAI) has advanced significantly, few methods address interpretability in embedded vector spaces where dimensions represe
arXiv:2607.06407v1 Announce Type: new Abstract: The XAI community has studied a wide range of queries and scores for explaining predictions of ML models. From a data management perspective, this proli
Fable feels very different than Opus. GPT-5.6 feels like a part of the GPT-5 family. I developed a very complex set of heuristics about when to use which. Fable was often “smarter” but was also too se
Factory (@FactoryAI) CEO Matan Grinberg (@matanSF) says 'In the next 12 months, 90% of tokens will be going to open models.' Enterprises are already shifting rapidly.. 'At the beginning of the year, <
arXiv:2607.06389v1 Announce Type: new Abstract: Video face restoration (VFR) aims to recover high-quality and temporally consistent facial details from severely degraded video sequences; however, exis
arXiv:2607.05970v1 Announce Type: cross Abstract: Dataset search depends heavily on metadata, making LLM-generated metadata a consequential form of synthetic content in retrieval systems. We study six
arXiv:2509.11819v2 Announce Type: replace-cross Abstract: Federated Domain Adaptation (FDA) is a federated learning (FL) approach that improves model performance at the target client by collaborating
arXiv:2607.05553v1 Announce Type: new Abstract: Transient stability control in smart grids requires rapid post-fault damping of generator frequency and rotor angle deviations to prevent cascading fail
arXiv:2607.05891v1 Announce Type: cross Abstract: Coreset selection aims to identify a small and highly representative subset of a massive dataset for efficient model training. The problem remains cha