Knowledge catalogue
arXiv:2608.15517v1 Announce Type: new Abstract: Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence
arXiv:2608.15107v1 Announce Type: new Abstract: Federated learning (FL) is a practical framework that can train models on distributed user data while guaranteeing data privacy; however, due to heterog
arXiv:2608.16733v1 Announce Type: cross Abstract: Physical design algorithms operate within tightly coupled, multi-stage optimization flows, where stage-local gains may vanish or induce downstream deg
arXiv:2608.16328v1 Announce Type: new Abstract: Instruction-based general video editing seeks to unify diverse editing operations within a single, intuitive interface. Existing approaches often rely o
arXiv:2608.15647v1 Announce Type: cross Abstract: Semantic segmentation of very-high-resolution (VHR) remote sensing imagery increasingly benefits from strong pretrained hierarchical encoders, yet exp
arXiv:2511.21317v2 Announce Type: replace Abstract: The Visual Geometry Grounded Transformer (VGGT) marks a significant leap forward in 3D scene reconstruction, as it is the first model that directly
arXiv:2608.16607v1 Announce Type: new Abstract: Whole-slide image (WSI) analysis remains computationally challenging due to the extremely large spatial resolution of slides and the sparse distribution
I was checking out benchmarks of this model and apparantly better than Qwen3.5 9b reasoning across the bench on artificial analysis. I have used the 9b model for variety of stuff and it has been amazi
arXiv:2608.15693v1 Announce Type: new Abstract: Running large AI models on resource-constrained edge devices requires model compression to reduce model size and computation. What compresses well, howe
arXiv:2608.16185v1 Announce Type: cross Abstract: LLM agents increasingly answer questions over dynamic raw-document collections, where files may change before preprocessing, and relevant evidence (sp
arXiv:2608.14625v1 Announce Type: cross Abstract: Academic peer review is under mounting strain: NeurIPS 2025 received 21,575 submissions, ICLR 2025 received 11,603, and ICML 2025 received 12,107. Thi
I have a lot of content in my personal Obsidian vault and would feel much more comfortable using LLMs with an offline model. I've experimented with Ollama and various small 3b/8b local models (given c
arXiv:2608.16429v1 Announce Type: new Abstract: Foundational models for tabular data have made significant progress in recent years, with TabICLv2 reporting state-of-the-art performance on several tab
arXiv:2608.15156v1 Announce Type: cross Abstract: World models may predict the future without making clear which parts of their hidden state actually drive those predictions. We ask whether a small, d
arXiv:2411.15041v2 Announce Type: replace Abstract: Advanced Multimodal Large Language Models (MLLMs) struggle with recent Knowledge-based Visual Question Answering (VQA) tasks, such as INFOSEEK and E
arXiv:2608.16201v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) aims to predict sentiment polarity and intensity from heterogeneous inputs such as text, audio, and vision. While la
The AI wants to run a higher risk action. Nyx AI stops it here. Nyx AI deliberately invokes a native Windows confirmation before certain higher risk actions can continue. The model cannot approve this
arXiv:2608.16070v1 Announce Type: cross Abstract: Reliable global ocean forecasting is critical for climate monitoring, marine navigation, and extreme event early warning. Physics-based ocean forecast
arXiv:2608.14677v1 Announce Type: cross Abstract: Most mobile image-generation applications are thin clients over cloud services, leaving outputs hard to audit. We present an Android latent-diffusion
arXiv:2608.15267v1 Announce Type: new Abstract: Semantic change detection (SCD) is a bitemporal dense-prediction task that jointly identifies changed regions and their semantic states before and after
arXiv:2608.14557v1 Announce Type: cross Abstract: Low Earth Orbit (LEO) computing is emerging for low-latency, globally distributed AI services, enabled by advances in satellite constellations and reu
arXiv:2608.14774v1 Announce Type: new Abstract: Modern sequence models heavily rely on massive memory footprints and large-batch stochastic optimization, barriers that restrict sample efficiency and c
arXiv:2608.15026v1 Announce Type: new Abstract: Post-training of vision-language-action (VLA) models typically relies on expert demonstrations and policy interaction trajectories. However, in long-hor
arXiv:2608.16477v1 Announce Type: new Abstract: AI-RAN brings large language model (LLM) serving close to mobile users, but cellular handover can separate an active request from its inference state: t
arXiv:2608.15115v1 Announce Type: new Abstract: Adversarial examples generated on a surrogate deep neural network (DNN) can often successfully fool other black-box DNN models. This cross-model transfe
arXiv:2602.08261v2 Announce Type: replace Abstract: Auto-bidding systems strive to maximize marketing value while maintaining high compliance with efficiency constraints, such as Target Cost-Per-Actio
arXiv:2608.16167v1 Announce Type: cross Abstract: High-precision radio map construction is essential for emerging 6G Integrated Sensing and Communication (ISAC) applications, including digital twins a
arXiv:2509.12757v2 Announce Type: replace Abstract: Cross-view object geo-localization (CVOGL) aims to determine the location of a specific object in high-resolution satellite imagery given a query im
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:2608.15946v1 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:2608.14682v1 Announce Type: new Abstract: Real-world time series inherently intertwine global periodic structures with localized non-stationary variations. Existing approaches process these hete
arXiv:2608.15075v1 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:2606.19888v2 Announce Type: replace-cross Abstract: Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, mu
arXiv:2608.15958v1 Announce Type: new Abstract: Deciding whether a Sokoban puzzle is solvable is PSPACE-complete (Culberson, 1997): solutions can be exponentially long and there is no short certificat
arXiv:2608.14922v1 Announce Type: cross Abstract: Mechanistic interpretability has recently expanded to Vision Transformers (ViTs), with Sparse Autoencoders (SAEs) increasingly used as post-hoc tools
arXiv:2608.15687v1 Announce Type: new Abstract: Sycophancy, the tendency of a language model to change its answer to match a user's stated belief, is a common alignment failure. Existing activation st
arXiv:2608.16765v1 Announce Type: cross Abstract: Despite recent advances in unified multimodal models for multi-reference image generation, existing benchmarks remain organized around predefined task
arXiv:2608.16410v1 Announce Type: new Abstract: Combined algorithm selection and hyperparameter optimization (CASH) searches a conditional space in which the selected model determines which hyperparam
arXiv:2608.16696v1 Announce Type: cross Abstract: Physical AI systems such as autonomous vehicles and robots rely on timely exchange of high-dimensional sensory signals under tight bandwidth, latency,
Hi everyone, I use AI agents to code and manage my personal files heavily. However, I am worried that the agents may accidentally delete some important files on my machine, outside of the defined scop
arXiv:2608.14665v1 Announce Type: new Abstract: The temperature that maximizes pass@k is often low for a small sampling budget and higher for a large budget. This pattern has been reported from Codex
arXiv:2608.15639v1 Announce Type: cross Abstract: extit{Split Federated Learning} (SFL) enables distributed model training by splitting networks between the server and clients. However, under client h
arXiv:2608.14811v1 Announce Type: new Abstract: Teams that adopt cycle-consistent adversarial networks for unpaired image-to-image translation meet the same obstacles: adversarial training oscillates
arXiv:2608.14854v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general video understanding, their capability in fine-grained and motion-centric tasks remains l
arXiv:2510.25692v4 Announce Type: replace-cross Abstract: As machine learning (ML) increasingly underpins critical applications, credible, comparable, and repeatable experimental results become more i
arXiv:2608.13574v1 Announce Type: new Abstract: LLM agents increasingly operate as execution systems that invoke tools, modify local state, use persistent memory, and interact with external protocols.
arXiv:2603.11461v3 Announce Type: replace Abstract: With increasing demand for mass customization, traditional manufacturing robots that rely on rule-based operations lack the flexibility to accommoda
arXiv:2608.14051v1 Announce Type: new Abstract: Deep learning models trained on datasets with spurious correlations can achieve high average accuracy whilst relying on shortcut features that do not ge
arXiv:2608.14027v1 Announce Type: new Abstract: Benefiting from high temporal resolution and dynamic range, event-based local feature methods have attracted increasing attention. However, event sparsi
arXiv:2608.14428v1 Announce Type: new Abstract: 3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable p
arXiv:2602.21956v2 Announce Type: replace Abstract: Text Image Machine Translation (TIMT) aims to translate text embedded in images in the source-language into target-language, requiring synergistic i
arXiv:2608.14032v1 Announce Type: cross Abstract: Existing multimodal RAG methods often flatten structured documents into isolated text and image units, weakening the source organization and local tex
arXiv:2608.13678v1 Announce Type: cross Abstract: A central goal of robot learning is to enable robots to execute rich instructions specified at runtime. Large-scale language-conditioned policies have
arXiv:2608.14394v1 Announce Type: new Abstract: Perception is a fundamental component of autonomous driving systems. While LiDAR-based methods have achieved remarkable progress in object detection, th
Join us for a fun night this Thursday (August 20th) in San Francisco! RSVP link below! 👇 This Thursday, August 20th, we’re bringing together four leaders at the forefront of open models, coding agents
arXiv:2608.13863v1 Announce Type: new Abstract: Deep neural network (DNN) inference on mobile devices often incurs high latency and energy consumption due to limited computing and memory resources. To
arXiv:2608.14543v1 Announce Type: new Abstract: High-resolution image restoration from degraded inputs is challenging because it must preserve global structural consistency while recovering fine-grain
arXiv:2608.13571v1 Announce Type: cross Abstract: When a language model fails to answer a query on the first attempt, an agentic system retries, consuming additional tokens each time. This retry overh
I’m trying to compare Ollama Pro with OpenCode Go, specifically in terms of how much real-world usage each plan provides. Ollama Pro costs 20/month, while OpenCode Go costs approximately 10/month. Bas
arXiv:2608.14408v1 Announce Type: cross Abstract: We study online statistical inference for functionals of the return distribution under a fixed policy. The return distribution is estimated by nonpara