Knowledge catalogue
Anyone else play with vllm-mlx? There was an interesting paper that came out that compared this version of vllm that was originally designed for multi modal inference performance gains, but ended up s
arXiv:2508.15754v2 Announce Type: replace-cross Abstract: Tool use is often assumed to monotonically improve reasoning, where external evidence is expected to help when relevant and be ignored when ir
arXiv:2609.09166v1 Announce Type: new Abstract: This paper investigates collaborative speculative decoding (CoSD), a distributed large language model (LLM) inference framework in which an on-device sm
arXiv:2609.07675v1 Announce Type: cross Abstract: Transaction-local controls answer whether one financial request may proceed, but market behavior can be distributed across messages, agents, assets, a
arXiv:2609.06507v1 Announce Type: new Abstract: Accurate vehicle license plate detection is essential for applications such as intelligent transportation systems, toll collection, parking management,
arXiv:2508.04175v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly
arXiv:2609.06984v1 Announce Type: new Abstract: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with increased risks of stroke and heart failure. The growing availabil
arXiv:2609.06380v1 Announce Type: new Abstract: Developing microanastomosis skill requires repeated practice with timely, action-specific feedback, yet expert review of lengthy microscope videos does
Another banger paper from Google. If you build memory for long-horizon agents, this one is worth your time. (bookmark it) Really nice to see how knowledge graphs are being explored in creative ways fo
arXiv:2609.07012v1 Announce Type: cross Abstract: Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform jitter produces spatially varying motion b
arXiv:2609.05937v1 Announce Type: new Abstract: Vision Transformers (ViTs) have shown immense potential in medical image analysis. However, standard pre-training via global image classification suffer
arXiv:2609.07597v1 Announce Type: new Abstract: Muon can be interpreted as optimizing a linear local objective over a spectral-norm ball. This gives a matrix-sign update that preserves the singular di
Tool: .blend URL Viewer I'm continuing to have a lot of fun with GPT-6 Astra and Blender (see my TIL). As a big fan of the Imperial Fabergé Easter eggs, I've always thought it would be fun to make som
arXiv:2609.07362v1 Announce Type: cross Abstract: Converting in-service reinforced-concrete (RC) building blueprints into simulation-ready models---structured frame representations that support determ
arXiv:2609.05881v1 Announce Type: cross Abstract: Developers increasingly run large language models locally by pulling quantized GGUF artifacts from public registries, yet nothing in the distribution
arXiv:2609.06623v1 Announce Type: cross Abstract: Can exploratory UAV waypoint sequences be generated from multimodal onboard observations and a fixed-dimensional recurrent internal state without main
arXiv:2609.07004v1 Announce Type: new Abstract: Accurate segmentation of pulmonary lesions is essential for effective clinical diagnosis and treatment strategies. Existing segmentation approaches ofte
arXiv:2609.06093v1 Announce Type: new Abstract: Connectomes, graph-level maps of neurons and their synaptic connections, provide a structural basis for understanding how brain circuits support functio
arXiv:2609.07314v1 Announce Type: cross Abstract: Rotary position embedding (RoPE) uses each token's integer position to determine the rotation applied inside attention. This works well for local toke
arXiv:2609.05988v1 Announce Type: new Abstract: Recurrent reasoning models (RRMs) can solve structured problems, achieving easy-to-hard generalization through iterative computation in hidden space. Th
arXiv:2609.08331v1 Announce Type: new Abstract: Video Large Language Models (VideoLLMs) are increasingly deployed in safety-critical applications such as content moderation and video analytics. To pro
im new to using ai so i may be missing something. I set up ollama but dont want any of my data to go to any of the model providers, for certain models i appear to need an api key to download the model
arXiv:2609.06370v1 Announce Type: new Abstract: Predicting 3D occupancy from multi-view images requires preserving geometric detail during 2D-to-3D lifting while reasoning over sparse, volumetric scen
arXiv:2603.26483v2 Announce Type: replace Abstract: Medical edge-AI systems must operate under a difficult tension: delivering reliable diagnostic inference while running on devices with limited batte
arXiv:2505.20961v2 Announce Type: replace-cross Abstract: Sound source localization (SSL) is a critical technology for determining the position of sound sources in complex environments. However, exist
arXiv:2609.08391v1 Announce Type: new Abstract: Remote sensing multimodal large language models (RS-MLLMs) have advanced scene understanding and visual question answering over satellite imagery, yet l
arXiv:2609.08607v1 Announce Type: new Abstract: We present GOLF, the first-place solution to the SHOW3D Interaction Field Estimation Challenge at HANDS@ECCV 2026. Given synchronized egocentric stereo
arXiv:2603.25255v2 Announce Type: replace Abstract: Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidenc
I’ve been experimenting with explaining AI/LLM concepts in a way that doesn’t assume too much technical background. This video is about KV Cache and why longer context windows require more memory duri
arXiv:2609.07874v1 Announce Type: new Abstract: Multimodal large language models often capture visual-linguistic correlations but struggle to predict how local visual interventions propagate and affec
arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem
arXiv:2508.17708v2 Announce Type: replace Abstract: X-ray micro-computed tomography (micro-CT) provides non-destructive three-dimensional (3D) imaging of porous material microstructures. In situ exper
arXiv:2609.06686v1 Announce Type: cross Abstract: We present an unsupervised search for anomalous dijet events in proton--proton collision data using neural spline flow density estimation. A normalizi
arXiv:2609.08408v1 Announce Type: new Abstract: Focusing on spatially localized, control-relevant visual cues has been shown to improve data efficiency in visuomotor policies by reducing the need to m
arXiv:2609.07029v1 Announce Type: new Abstract: Localizing a font into new languages is a highly intricate task requiring precise design adaptation of glyphs, color/texture, and spacing/kerning, from
arXiv:2609.05955v1 Announce Type: new Abstract: Tabular foundation models have become powerful graph learners. Systems such as G2T-FM and GraphPFN encode each node as a feature row and make prediction
arXiv:2609.07116v1 Announce Type: new Abstract: Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their re
arXiv:2609.08041v1 Announce Type: new Abstract: Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexist
arXiv:2609.05841v1 Announce Type: new Abstract: Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations,
arXiv:2609.06874v1 Announce Type: cross Abstract: High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and fo
arXiv:2609.07504v1 Announce Type: new Abstract: Standard Convolutional Neural Networks (CNNs) exhibit severe performance degradation due to a strong inductive texture bias that prioritizes local, high
arXiv:2609.06514v1 Announce Type: new Abstract: Adaptive frequency hopping against predictive jamming must address both model uncertainty and policy exposure: the context-loss relationship may vary ac
arXiv:2609.05941v1 Announce Type: new Abstract: Optimization-based simultaneous localization and mapping (SLAM) makes it possible to reduce accumulated navigation errors of sensing platforms by return
I was curious about how AIs talk to each other and how a conversation changes as it goes on, so I built AI Arena Lite. It connects to Ollama and lets you assign models to different agent roles, follow
arXiv:2609.08594v1 Announce Type: new Abstract: This paper proposes a level-set-based physics-driven neural network solver (LSPDNN) for 3-D electromagnetic inverse scattering. To mitigate boundary blu
arXiv:2609.06288v1 Announce Type: new Abstract: Training-free image editing steers diffusion or flow-matching generative models at inference time by modifying prompt-conditioned denoising velocities.
arXiv:2609.05498v1 Announce Type: new Abstract: This technical report studies the local weak observability of a planar bicycle-model vehicle when vehicle pose, planar LiDAR extrinsic calibration, and
arXiv:2609.07108v1 Announce Type: new Abstract: Speculative decoding accelerates rollout generation, which dominates the cost of reinforcement learning (RL) post-training. Online co-training can furth
arXiv:2609.06942v1 Announce Type: new Abstract: Medium-range precipitation forecasts are impaired by persistent systematic biases, lead-time-dependent error accumulation, and coarse spatial resolution
arXiv:2609.08215v1 Announce Type: new Abstract: Video generation models have recently attracted substantial attention for their ability to generate visually compelling videos, yet ensuring physically
arXiv:2609.07532v1 Announce Type: new Abstract: Learning physically plausible dynamics from visual observations is essential for interactive world models and embodied agents. However, modeling real-wo
arXiv:2609.06436v1 Announce Type: new Abstract: High-resolution 3D asset generation is vital in various 3D applications. Existing state-of-the-art diffusion-based models remain constrained by fixed re
arXiv:2609.06869v1 Announce Type: new Abstract: Three-dimensional bioheat simulation aims to predict transient temperature distributions in biological tissue and is commonly modeled using the Pennes b
arXiv:2609.07328v1 Announce Type: new Abstract: Local pedestrian-vehicle forecasting spans heterogeneous physical scales: pedestrians combine root locomotion with articulated motion, whereas vehicles
https://github.com/paulknysh/raggy A lightweight CLI tool for Retrieval-Augmented Generation (RAG) over local documents built with Ollama. Hybrid database (vector + BM25 index) and embedding generatio
arXiv:2609.07312v1 Announce Type: new Abstract: This paper proposes a robust decentralized personalized federated learning method R-DPFL, that enables clients to reduce the impact of Byzantine attacks
arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a
arXiv:2609.08867v1 Announce Type: new Abstract: Reasoning segmentation converts an implicit linguistic conclusion into a precise mask, requiring both semantic identification and spatial grounding. Exi
arXiv:2609.08496v1 Announce Type: new Abstract: Sign language video generation demands precise hand and facial articulation, yet modern video diffusion models, trained predominantly on spoken-language
arXiv:2609.07608v1 Announce Type: new Abstract: Bridging the simulation-to-reality gap in roadside LiDAR requires addressing several coupled discrepancies, including scene geometry, sampling density,