Knowledge catalogue
arXiv:2609.20114v1 Announce Type: new Abstract: Collecting real-world navigation data for mobile robots typically requires platform-specific teleoperation, making large-scale collection expensive and
arXiv:2603.12808v2 Announce Type: replace Abstract: Artificial intelligence in molecular science must move beyond pattern recognition toward chemically valid and interpretable reasoning. We present a
arXiv:2609.18520v1 Announce Type: new Abstract: Collective intelligence is a collaborative autonomy paradigm in which multiple agents pursue shared objectives through local perception, information exc
arXiv:2609.18131v1 Announce Type: cross Abstract: In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computa
arXiv:2609.18470v1 Announce Type: cross Abstract: Video-based Multimodal sentiment analysis (MSA) must handle information from text, audio, and image sequence in human speaking videos, yet current met
arXiv:2609.17590v1 Announce Type: cross Abstract: Evolutionary Ensemble Search (EES) constructs machine-learning procedures through expert-guided program evolution. A role-specialized council turns ta
arXiv:2609.18256v1 Announce Type: new Abstract: Reliability under sparse and heterogeneous failures remains a fundamental challenge for medical image segmentation. High average accuracy can conceal a
arXiv:2609.18238v1 Announce Type: new Abstract: Observational decision-support systems often expose one causal estimate as a recommendation even when plausible estimators disagree. The inherent engine
arXiv:2609.18623v1 Announce Type: cross Abstract: State-of-the-art vision-language-action models (VLA) for autonomous driving face critical limitations: excessive parameter counts, inefficient high-re
arXiv:2609.18766v1 Announce Type: cross Abstract: Large audio-language models have shown promise for anti-fraud detection by directly processing speech and reasoning over fraud-related evidence. Their
arXiv:2609.18688v1 Announce Type: cross Abstract: AI models for multimodal medical imaging must balance modality-specific specialization with cross-modal shared representations, a trade-off that pure
arXiv:2609.18465v1 Announce Type: new Abstract: Feed-forward 3D foundation models such as VGGT predict cameras, depth, and point maps in a single pass, but can fail silently under low overlap, low par
At Google, we see firsthand how the speed, scale, and sophistication of cyber threats continue to challenge traditional enterprise defenses. Today’s defenders can’t rely on reactive triage or fragment
arXiv:2609.18416v1 Announce Type: cross Abstract: Stochastic subspace methods have gained popularity as gradient descent based techniques for large scale optimisation problems, especially in distribut
arXiv:2609.17568v1 Announce Type: cross Abstract: Additive-congestion constraints in single-source unsplittable flow can enforce stable-set structure. This note isolates and generalises that mechanism
arXiv:2609.19048v1 Announce Type: new Abstract: In the context of differentiated on-demand goods delivery services, this study proposes an integrated optimization method for automated guided vehicles
arXiv:2609.18825v1 Announce Type: new Abstract: Background: Molecular testing for NPM1 and FLT3-ITD mutations guides critical early treatment decisions in acute myeloid leukemia (AML), but results can
arXiv:2609.18315v1 Announce Type: new Abstract: Non-intrusive load monitoring (NILM) estimates appliance power sequences from aggregate power, but models trained on source households commonly lose acc
arXiv:2609.17560v1 Announce Type: cross Abstract: Every production model is updated, by retraining, fine-tuning, quantization, or a silent vendor swap, and each update risks being worse than what it r
arXiv:2609.17831v1 Announce Type: cross Abstract: Molecular property prediction is often limited by the small size of labeled downstream datasets, motivating pretraining on large corpora of unlabeled
arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-
arXiv:2609.18037v1 Announce Type: new Abstract: Segment Anything Models provide reusable priors, yet they require user prompts and cannot support fully automatic instrument segmentation. Automatic pro
arXiv:2609.18966v1 Announce Type: new Abstract: Linear RNNs with input-dependent Householder-product transitions (DeltaNet/DeltaProduct-class) can provably represent hard state-tracking automata, yet
arXiv:2609.18704v1 Announce Type: cross Abstract: Modern networks must support changing topologies, configurations, and performance objectives, motivating fast and reliable performance estimation. Net
arXiv:2609.18435v1 Announce Type: new Abstract: Automating biological research requires general-purpose, reproducible robot systems that allow individual wet-lab researchers to delegate robot tasks wi
arXiv:2609.17571v1 Announce Type: cross Abstract: Where in a Transformer is the change from memorization to generalization functionally expressed? We introduce Transition Games--behavior-aligned exact
I find another new model at HF: https://huggingface.co/XingChen-AGI/Xing4.0-29B-A4B 'Xing4.0-29B-A4B is a next-generation large language model in the Xing series (formerly TeleChat), developed by Chin
arXiv:2609.16382v1 Announce Type: cross Abstract: A language model's representation geometry is not predetermined; it evolves as the model runs. A faithful account of that geometry must capture that d
Banger paper from NVIDIA. It's on the topic of choosing which models go into a multi-agent system. The team compared eight selection strategies, based on size, accuracy, answer diversity and error div
arXiv:2609.17443v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual question answering (VQA) performance, but processing large cluttered images is computationally expen
arXiv:2609.16637v1 Announce Type: new Abstract: Efficient perception is central to robotic systems operating under constrained computation, memory, and latency budgets. Knowledge transfer from larger
arXiv:2609.16724v1 Announce Type: new Abstract: Safe local planning requires forecasting surrounding-agent motion and evaluating candidate-specific risks, since identical agent motion can pose differe
arXiv:2609.15997v1 Announce Type: new Abstract: Improving safety at intersections requires identifying crash mechanisms and recommending appropriate countermeasures. However, this process traditionall
arXiv:2512.01782v4 Announce Type: replace-cross Abstract: Randomized Smoothing (RS) is a prominent technique for certifying the robustness of neural networks against adversarial perturbations. With RS
arXiv:2609.16070v1 Announce Type: cross Abstract: Generative recommendation reformulates item prediction as semantic identifier generation, yet episodic content introduces a fundamentally different se
arXiv:2607.27245v2 Announce Type: replace-cross Abstract: Modern policing faces a 'visibility paradox' where law enforcement agencies possess petabytes of Body-Worn Camera (BWC) footage that remains l
arXiv:2609.17439v1 Announce Type: cross Abstract: Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity
arXiv:2609.16528v1 Announce Type: new Abstract: Building accurate decision-support tools for next-generation air traffic control requires robust trajectory prediction models. We present a flow-matchin
arXiv:2609.16415v1 Announce Type: cross Abstract: Pedestrian-count forecasting supports pedestrian-oriented Intelligent Transportation Systems (ITS), including crowd monitoring, pedestrian-traffic sta
arXiv:2609.17115v1 Announce Type: cross Abstract: Vision-language-action (VLA) systems already bring together two valuable resources for robot learning: rich visual representations and demonstrations
arXiv:2512.15020v3 Announce Type: replace Abstract: Vision-based imitation learning has enabled impressive robotic manipulation skills, but action imitation alone provides limited supervision of the g
arXiv:2603.08283v2 Announce Type: replace Abstract: Complex constraints often make real-world optimization computationally prohibitive at the scale and speed required for operational decision-making.
arXiv:2609.16684v1 Announce Type: new Abstract: Learning manipulation from human video requires high-fidelity hand-motion reconstruction in metric units. Today's metric hand labels come from studio ri
arXiv:2609.17306v1 Announce Type: cross Abstract: Multi-agent Systems (MAS) combine multiple model outputs to solve complex reasoning tasks. However, despite rapid growth of available open-source mode
arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost
arXiv:2609.16995v1 Announce Type: new Abstract: Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such i
arXiv:2609.16564v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) pipelines may omit a source's material relationship to the query. We study a pre-generation triage layer that treat
arXiv:2609.17021v1 Announce Type: new Abstract: Autonomous wheel-loader control requires joint reasoning over task semantics, egocentric vision, proprioception, and 3D scene geometry. We present sensV
arXiv:2609.16804v1 Announce Type: cross Abstract: Time-series foundation models have demonstrated strong cross-domain transfer, yet their common architectural assumptions remain poorly aligned with we
arXiv:2609.16748v1 Announce Type: new Abstract: Text summarization requires models to condense content while preserving key qualities such as consistency and coherence. Large language models (LLMs) ha
arXiv:2609.17198v1 Announce Type: new Abstract: Autonomous nano-UAV navigation requires accurate ego-motion estimation under stringent size, weight, power, and computing (SWaP-C) constraints, where vi
arXiv:2609.16232v1 Announce Type: new Abstract: Geospatial artificial intelligence (GeoAI) powered by large language models (LLMs) is expanding the capacity to query, generate, and interpret spatial i
I've been working on something for this community (and other self-hosted communities) for almost 5 months now. Personally, I would grade it as probably the closest open source equivalent of Manus and
https://reddit.com/link/1wi2zuc/video/rs1a4sx92xph1/player Hey everyone, I’ve been experimenting with local LLMs on Intel hardware, and I wanted a hyper-optimized, standalone CLI tool that didn't rely
arXiv:2609.14413v1 Announce Type: cross Abstract: Large language model (LLM)-based database migration is often treated as direct code transformation, although enterprise Oracle systems contain heterog
arXiv:2609.13878v1 Announce Type: new Abstract: Spatio-temporal traffic data are central to intelligent transportation systems, yet their heterogeneity poses significant challenges for large-scale mod
arXiv:2609.14105v1 Announce Type: new Abstract: Heat Kernel Textures (HKTex) represent surface appearance with intrinsic anisotropic kernels, but evaluate them using 50 global Laplace-Beltrami eigende
Today, we are announcing the availability of Agent Substrate on Google Kubernetes Engine (GKE). Agent Substrate is an open-source, secure-by-default agent execution runtime engineered to run millions
arXiv:2609.13624v1 Announce Type: cross Abstract: Large Language Models (LLMs) are powerful zero-shot learners but remain prone to misalignment with human preferences, often producing biased, toxic, o
arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type