Knowledge catalogue
arXiv:2607.09557v2 Announce Type: replace Abstract: Fine grain control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Traditio
arXiv:2609.19670v1 Announce Type: new Abstract: Direct forecasting has become a standard paradigm for multivariate time-series forecasting because it predicts the full future horizon in a single pass.
arXiv:2609.20586v1 Announce Type: cross Abstract: Referring scene understanding for embodied robots requires grounding object- and relation-centric language queries from a designated viewpoint. While
arXiv:2609.19818v1 Announce Type: cross Abstract: Generalizing to unseen attacks remains challenging for audio deepfake detectors, and collecting training data covering all potential attacks is imprac
arXiv:2609.19512v1 Announce Type: cross Abstract: Robots can recall prior failures without knowing whether recalled evidence remains valid, conflicts with current observations, or is sufficient to gui
arXiv:2609.20045v1 Announce Type: cross Abstract: A memory can answer a current query correctly while discarding distinctions required by a later update. We investigate this failure with a paired-hist
arXiv:2609.20461v1 Announce Type: cross Abstract: Studying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are
arXiv:2603.29429v2 Announce Type: replace Abstract: AI is increasingly used for mental health and well-being support, creating an urgent need for safer engagement, while design, evaluation, and govern
arXiv:2609.20260v1 Announce Type: cross Abstract: We comment on the optimally-transported generalized method of moments (OTGMM) estimator proposed by Schennach & Starck (2026a) and give counterexample
arXiv:2609.19189v1 Announce Type: cross Abstract: Design verification remains one of the most resource-intensive stages of hardware development, often consuming up to 70% of the total design effort. W
arXiv:2609.20441v1 Announce Type: new Abstract: Geospatial foundation models can provide strong flood-segmentation performance, but their size limits deployment on memory-constrained edge hardware. We
arXiv:2609.20139v1 Announce Type: cross Abstract: Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the question affects VLMs in two opposite ways. Verbose
arXiv:2602.10711v2 Announce Type: replace-cross Abstract: Asset retrieval (finding similar assets in a financial universe) is central to quantitative investment decision-making. Existing approaches de
arXiv:2609.20592v1 Announce Type: new Abstract: Crystal structure refinement is a fundamental inverse problem in materials characterization, where structural parameters are optimized to reproduce expe
So I know that Ollama is built on top of llama.cpp, I decided to run a model on both and applied settings on llama.cpp like flash attention and q8/q4 kv cache. On Ollama (using the Python package) I w
arXiv:2609.20691v1 Announce Type: new Abstract: Mapping and monitoring aquatic environments can benefit from hybrid aerial-amphibious drones able to combine flight and water-surface navigation within
arXiv:2609.19996v1 Announce Type: new Abstract: With the widespread use of online navigation and ride-hailing services, achieving optimal route planning for diverse user preferences has recently attra
Three cybersecurity researchers used Claude to breach OpenAI Group PBC’s GitHub repository. Sources told the Wall Street Journal today that the repository contains “OpenAI’s algorithmic secrets.” The
arXiv:2609.19880v1 Announce Type: new Abstract: The KV cache has become a major bottleneck in deploying LLMs, as its memory footprint grows linearly with sequence length and batch size, imposing subst
arXiv:2609.20051v1 Announce Type: new Abstract: Step distillation reduces the cost of video generation, but reusing a LoRA trained for a longer trajectory can alter its functional effect or degrade ta
Hi there, I'm Yuesong, a researcher at Video Rebirth. We open-sourced HyperFlow, an 8-step LoRA for MiniMax-H3. The core idea: data-free flow self-distillation. Diffusers' default sampler does 49 mode
arXiv:2609.19617v1 Announce Type: cross Abstract: Business analytics education requires diverse datasets to support different learning objectives, student backgrounds, and analytical tasks. Real-world
arXiv:2609.19726v1 Announce Type: new Abstract: The existing singularity-free guiding vector field (SF-GVF) with an additional virtual coordinate can eliminate singular points (i.e., points where the
arXiv:2609.20467v1 Announce Type: cross Abstract: The categorization of cognitive and resting states derived from electroencephalography (EEG) signals is crucial for comprehending fluctuations in brai
arXiv:2609.19416v1 Announce Type: cross Abstract: We study machine-learning detection of controlled beyond-General-Relativity (beyond-GR) deviations in gravitational-wave signals, using both synthetic
arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a f
arXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost
I just released a new dataset https://huggingface.co/datasets/LocalLLaMA/deepswe-mini it is meant to be more efficent when testing and benchmarking local models on DeepSwe https://deepswe.datacurve.ai
arXiv:2609.19801v1 Announce Type: new Abstract: Executable environments enable LLM agents to learn from the consequences of their actions. For embodied agents, those consequences extend beyond whether
arXiv:2609.19900v1 Announce Type: cross Abstract: Static malware detection for Windows Portable Executable files demands a careful balance between detection effectiveness, computational efficiency, an
arXiv:2609.19607v1 Announce Type: cross Abstract: Coding-agent benchmarks are built for broad and comprehensive comparisons, not frequent development decisions. Individual runs vary, full suites are e
arXiv:2609.19428v1 Announce Type: cross Abstract: This paper proposes a structured approach to learning linear operators for control systems from data. We address both structural and learning-theoreti
Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving containe
arXiv:2609.19367v1 Announce Type: new Abstract: Ensuring intrinsic safety in physical human robot interaction (pHRI) is a critical requirement for social and service robots. While Series Elastic Actua
arXiv:2609.20104v1 Announce Type: new Abstract: We describe the architecture, training methodology and inference speedups of Granite 5.0 Turbo CTC, a 470 million parameter encoder-only model with an e
arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling. However, it remains unclear how to prevent deski
arXiv:2609.20336v1 Announce Type: cross Abstract: Deceptive online job advertisements have emerged as a primary pathway into forced labour, yet systematic detection methods remain underdeveloped due t
arXiv:2609.19531v1 Announce Type: cross Abstract: We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for mul
arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots
arXiv:2609.20304v1 Announce Type: new Abstract: A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the pol
arXiv:2609.19805v1 Announce Type: new Abstract: Grapheme-to-phoneme (G2P) conversion turns raw text into its phonemic form and is an essential part of both text-to-speech (TTS) and automatic speech re
arXiv:2609.19913v1 Announce Type: new Abstract: The study of opinion dynamics in social networks is one of the key challenges in computational social science with direct relevance to understanding pol
arXiv:2609.19927v1 Announce Type: new Abstract: Optical motion capture delivers high-fidelity human motion, but its reliance on strict marker layouts and clean trajectories severely limits its real-wo
arXiv:2609.20248v1 Announce Type: new Abstract: Deploying a deep object detector in a new setting is limited less by architecture than by the cost of annotating data from that setting. Active learning
arXiv:2509.12390v3 Announce Type: replace Abstract: This paper addresses collaborative formation control for multi-agent systems with limited resources. We consider a team of robots tasked with achiev
arXiv:2609.19912v1 Announce Type: new Abstract: Teams of mobile robots rely on continuous communication with their neighbors for coordination, yet most distributed model predictive control (DMPC) sche
arXiv:2609.20501v1 Announce Type: new Abstract: Federated learning trains a shared model from private client data. In practice, data-generating distributions may differ, and the true mixture across cl
arXiv:2609.19196v1 Announce Type: new Abstract: Collecting data for manipulation with high-DOF hands is challenging, as interfaces must capture rich hand motion while rendering the contact interaction
arXiv:2609.19387v1 Announce Type: new Abstract: Agents are increasingly asked to design hardware, and increasingly reported to succeed. Such reports establish that a design improved; they cannot estab
arXiv:2609.20574v1 Announce Type: new Abstract: Answer grounding in document visual question answering remains an open challenge: most benchmarks lack grounding annotations or provide limited-quality
arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored acti
arXiv:2609.20751v1 Announce Type: new Abstract: Adapting a pretrained autoregressive (AR) model is a cost-efficient route to a diffusion language model (DLM). While nearly all such adaptations start f
arXiv:2609.20035v1 Announce Type: new Abstract: This paper presents dynamics-relaxed model predictive control (DR-MPC), a novel MPC formulation for legged locomotion, and a tailored interior-point met
arXiv:2603.07998v2 Announce Type: replace-cross Abstract: Aerodynamic promptness quantifies how rotor-speed variations generate multirotor wrench variations, but its Euclidean formulation assigns the
Note not my work, but something i found and wanted to share so hopefully more people can push this along even further. https://github.com/nasone32/llama.cpp-RDNA3-7900xtx-opt I basically run 2 x 7900
arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and ho
arXiv:2609.20008v1 Announce Type: cross Abstract: Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost. This is particularly
arXiv:2609.19336v1 Announce Type: new Abstract: This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in
arXiv:2409.18457v2 Announce Type: replace Abstract: This paper addresses a special Perspective-n-Point (PnP) problem: estimating the optimal pose to align 3D and 2D shapes in real-time without corresp
arXiv:2609.20001v1 Announce Type: new Abstract: Automated video interview assessment integrates verbal content, acoustic delivery, and visual behavior, yet numerical predictions alone provide limited