Knowledge catalogue
arXiv:2609.26729v1 Announce Type: new Abstract: In this paper, we proposed GAD-MambaUNet, a lightweight medical image segmentation network that combines efficient local modeling, direction--group stat
arXiv:2609.26499v1 Announce Type: new Abstract: Today, progress in open-weight language models enables systems capable of writing, executing and debugging code while still running on a single workstat
arXiv:2609.26620v1 Announce Type: new Abstract: Photographic composition aims to provide visual guidance for improving the framing, viewpoint, and spatial arrangement of an image. Early methods primar
arXiv:2609.25692v1 Announce Type: new Abstract: Graph domain adaptation (GDA) transfers knowledge from a labeled source graph to an unlabeled target graph under shifts in both node attributes and grap
arXiv:2609.22702v1 Announce Type: new Abstract: Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. Producing them at h
arXiv:2609.26231v1 Announce Type: new Abstract: Continuous and subtle GNSS spoofing poses a serious threat to autonomous vehicles because forged positions may remain locally plausible while gradually
SWE‑Serve evaluates AI coding agents on 53 inference‑engineering tasks derived from SGLang pull requests across six functional domains. Among 19 tasks that launch a live server, patches that pass loca
arXiv:2609.23360v1 Announce Type: cross Abstract: Engineering predictions require physical mechanisms to be translated consistently into equations, discretization, code, and validation, yet errors can
arXiv:2609.25927v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning
I keep seeing Jev presented as some new class of decision model, but most of what’s being advertised is just normal classifier behavior with modern zero-shot capabilities. It outputs probabilities ove
arXiv:2609.25802v1 Announce Type: cross Abstract: We introduce latest exact match attention (LEMA), an attention variant for transformers where queries and keys are binarized and each query attends on
arXiv:2609.22410v1 Announce Type: new Abstract: Inferring 3D cellular properties from 2D microscopy is difficult when a reference instrument reports only population statistics rather than labels for i
arXiv:2609.26325v1 Announce Type: cross Abstract: Camera-based 3D object detection and online vectorized HD mapping provide compact scene representations for autonomous driving, but both depend on acc
arXiv:2609.25051v1 Announce Type: new Abstract: Dual-source encrypted points of interest (DSEP), POIs from two encrypted coordinate systems, suffer from intertwined location and attribute uncertaintie
arXiv:2609.26667v1 Announce Type: new Abstract: Collaboration topology shapes both the performance and execution cost of LLM-based multi-agent systems. Because tasks differ in complexity and required
In light of recent events and media coverage, ai is in the spotlight and people are afraid. How I respond to those fears: If you are afraid of ai then you should also be afraid of all medical research
Looking for the best way to restore/refine quality of an AI-generated 720p video to 2K I’m looking for advice on the best ComfyUI workflow for improving the quality of an AI-generated video. My workfl
arXiv:2609.25049v1 Announce Type: new Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior stud
arXiv:2609.25815v1 Announce Type: new Abstract: Visual attribution methods typically explain predictions using pixels, superpixels, or regular patches. These representations can localize important reg
arXiv:2609.25907v1 Announce Type: new Abstract: Visual localization (VL) is a fundamental technology for vision applications such as virtual reality. Recently, a novel VL paradigm, Camera Ray Regressi
I’m looking for advice as I’ve just started out the local llm journey. I’d like to try out coding. I downloaded LM Studio and Qwen3.8-27B-Q4, but I wonder if there are more optimal options for my hard
arXiv:2609.25014v1 Announce Type: cross Abstract: Organizations fine-tune small language models on private data and then compress them to 4 bits for resource-efficient deployment. We show that the com
Is it just me or ollama serve command doesn't work at all. It uses a different directory than the systemd process, so it can't find any model or anything if you installed it using systemd ollama. Luck
arXiv:2603.17043v2 Announce Type: replace Abstract: Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy im
arXiv:2609.22987v1 Announce Type: new Abstract: Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing m
arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl
arXiv:2609.24876v1 Announce Type: new Abstract: In multi-agent social settings, model reliability varies across relationships. Beyond inferring what others will do, an agent must calibrate how confide
arXiv:2609.26219v1 Announce Type: cross Abstract: Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered c
arXiv:2609.25388v1 Announce Type: cross Abstract: A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal pr
arXiv:2609.23860v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) commonly reuse visual encoders pretrained with CLIP, although the features of these ViTs are ultimately consume
arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele
arXiv:2609.25898v1 Announce Type: new Abstract: Aerial-ground cooperation requires real-time UAV--UGV relative-state information. Instead of maintaining global estimates for both robots, direct contro
Hey everyone, I made a simple script called MOMOS to run Ollama and small LLMs directly on your Android phone using Termux. It automatically handles PRoot-Distro (Debian), installs Ollama, and lets yo
arXiv:2609.24130v1 Announce Type: new Abstract: LLM agents can change their own future behavior, raising a basic control question of which self-generated changes should be allowed to persist. We formu
arXiv:2609.26780v1 Announce Type: new Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish
arXiv:2609.26143v1 Announce Type: cross Abstract: Recommender systems on Web platforms tend to over-serve popular items and neglect the long tail. Item-side knowledge graphs (KGs), often available as
arXiv:2609.24243v1 Announce Type: new Abstract: Reinforcement learning (RL) improves reasoning in vision-language models (VLMs) but can induce chain-of-thought (CoT) obfuscation: an operational, non-i
Illinois folks (like myself), write your governor, please. And if you live elsewhere, please pay attention to your local/state politics. https://wgntv.com/politics-3/pritzker-establishes-ai-cabinet-to
arXiv:2609.26389v1 Announce Type: new Abstract: Real-world time series evolve continuously, with meaningful changes potentially emerging at any moment. However, existing time-series language models (T
arXiv:2609.25498v1 Announce Type: cross Abstract: Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessi
arXiv:2603.22667v2 Announce Type: replace Abstract: Autonomous exploration by unmanned surface vehicles (USVs) in near-shore waters requires reliable localisation and consistent mapping over extended
arXiv:2609.23444v1 Announce Type: cross Abstract: Engineering change order (ECO) is an important step in repairing timing and electrical violations during the late stages of chip design. Existing Agen
Hey everyone, I’m new to running AI models locally and I’d like some advice. My laptop specs are: HP OMEN 15 CPU: Intel i5-8300H RAM: 16 GB GPU: NVIDIA GTX 1050 Ti 4 GB VRAM OS: Windows I’m planning t
Hey everyone, I'm getting into running LLMs locally with Ollama and would like some recommendations on which models I should realistically run with my hardware. My PC specs GPU: RTX 5060 Ti 16GB VRAM
arXiv:2609.26487v1 Announce Type: new Abstract: Recursive models can continue updating their latent states beyond their nominal inference budget, so an incorrect output at that budget does not show wh
Ollama has introduced a new option allowing users to add usage credits for paid cloud models without requiring an Ollama subscription, enabling a pay‑as‑you‑go billing approach. The feature can be acc
arXiv:2609.22654v1 Announce Type: cross Abstract: Federated learning (FL) has emerged as a leading privacy-preserving framework for collaborative machine learning across decentralized environments. Wh
I know that there are some bots active on this sub but wow these comments really look AI generated. Is it just me or are those really bot comments? https://preview.redd.it/20st4vivq3rh1.png?width=955&
arXiv:2609.23582v1 Announce Type: new Abstract: Maintenance work orders must often be processed offline on embedded hardware, yet downstream software requires predictable structured output. We present
arXiv:2609.23896v1 Announce Type: new Abstract: Control barrier functions (CBFs) have become one of the most popular tools for encoding and enforcing state constraints in safety-critical robotics. Sta
arXiv:2609.22939v1 Announce Type: cross Abstract: Long-context models read a novel the way a person reads a printout: one token after another, in narrative order, with the whole history competing for
arXiv:2609.22162v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generation i
arXiv:2609.22260v1 Announce Type: cross Abstract: A large audio language model (LALM) attaches a speech front end to a text language model (LM) that is already safety-aligned. When such a model refuse
arXiv:2609.22247v1 Announce Type: new Abstract: Search agents are usually trained under a single harness. But once an agent is deployed in a real application, its harness is frequently updated (e.g.,
arXiv:2609.24494v1 Announce Type: new Abstract: Accurate monocular depth estimation serves as a core enabler for single camera scene understanding. However, existing self-supervised monocular depth es
arXiv:2609.22175v1 Announce Type: cross Abstract: World models trained via pixel reconstruction can struggle in visually complex environments, where irrelevant information dominates the objective and
arXiv:2609.24651v1 Announce Type: new Abstract: Diffusion and flow models, as promising generative paradigms for speech enhancement, face a training--inference mismatch: training uses analytical path
arXiv:2609.24749v1 Announce Type: cross Abstract: Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will
arXiv:2609.24359v1 Announce Type: new Abstract: Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while
arXiv:2609.24627v1 Announce Type: new Abstract: Multi-organ segmentation using deep learning requires large amounts of annotated patient data; however, institutions often lack sufficiently large and d