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SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer

arXiv:2605.14894v1 Announce Type: new Abstract: Recent breakthroughs in video diffusion models have significantly accelerated the development of video editing techniques. However, existing methods oft

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Seed3D 2.0: Advancing High-Fidelity Simulation-Ready 3D Content Generation

DGX agent

arXiv:2605.13862v1 Announce Type: cross Abstract: We present Seed3D 2.0, an advanced 3D content generation system built on Seed3D 1.0, with substantial improvements across generation fidelity, simulat

local-aiarxiv-cs-cv

15 May 2026

Self-Pruned Key-Value Attention: Learning When to Write by Predicting Future Utility

arXiv:2605.14037v1 Announce Type: cross Abstract: Under modern test-time compute and agentic paradigms, language models process ever-longer sequences. Efficient text generation with transformer archit

local-aiarxiv-cs-cl

Small, Private Language Models as Teammates for Educational Assessment Design

arXiv:2605.15015v1 Announce Type: new Abstract: Generative AI increasingly supports educational design tasks, e.g., through Large Language Models (LLMs), demonstrating the capability to design assessm

SteerSeg: Attention Steering for Reasoning Video Segmentation

arXiv:2605.14908v1 Announce Type: new Abstract: Video reasoning segmentation requires localizing objects across video frames from natural language expressions, often involving spatial reasoning and im

Towards Fine-Grained and Verifiable Concept Bottleneck Models

arXiv:2605.14210v1 Announce Type: cross Abstract: Concept Bottleneck Models (CBMs) offer interpretable alternatives to black-box predictors by introducing human-relatable concepts before the final out

Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought

arXiv:2605.14866v1 Announce Type: cross Abstract: As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with

Towards Real-Time Autonomous Navigation: Transformer-Based Catheter Tip Tracking in Fluoroscopy

arXiv:2605.14253v1 Announce Type: new Abstract: Purpose: Mechanical thrombectomy (MT) improves stroke outcomes, but is limited by a lack of local treatment access. Widespread distribution of reinforce

Training-Free Inference for High-Resolution Sinogram Completion

arXiv:2506.08809v5 Announce Type: replace Abstract: High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While

TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models

arXiv:2602.04657v3 Announce Type: replace Abstract: Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most ex

Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization

arXiv:2605.14373v1 Announce Type: cross Abstract: Zeroth-Order (ZO) optimization is pivotal for scenarios where backpropagation is unavailable, such as memory-constrained on-device learning and black-

Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces

arXiv:2605.14358v1 Announce Type: new Abstract: Language models often generate long chain-of-thought traces, but it remains unclear how much of this reasoning is necessary for preserving the final pre

v0.25.0-rc0: ci: speed up release builds (#15982)

This release candidate introduces CI/CD optimizations to accelerate the release build process for Ollama, as indicated by pull request #15982. The improvements focus on reducing build times during the

local-aiollama-releases

Venus-DeFakerOne: Unified Fake Image Detection & Localization

arXiv:2605.14091v1 Announce Type: new Abstract: In recent years, the rapid evolution of generative AI has fundamentally reshaped the paradigm of image forgery, breaking the traditional boundaries betw

Watch your neighbors: Training statistically accurate chaotic systems with local phase space information

arXiv:2605.14405v1 Announce Type: new Abstract: Chaotic systems pose fundamental challenges for data-driven dynamics discovery, as small modeling errors lead to exponentially growing trajectory discre

local-aiarxiv-cs-lg

Widening the Gap: Exploiting LLM Quantization via Outlier Injection

arXiv:2605.15152v1 Announce Type: cross Abstract: LLM quantization has become essential for memory-efficient deployment. Recent work has shown that quantization schemes can pose critical security risk

You Only Landmark Once: Lightweight U-Net Face Super Resolution with YOLO-World Landmark Heatmaps

arXiv:2605.14166v1 Announce Type: new Abstract: Face image super-resolution aims to recover high-resolution facial images from severely degraded inputs. Under extreme upscaling factors, fine facial de

3D RL-DWA: A Hybrid Reinforcement Learning and Dynamic Window Approach for Goal-Directed Local Navigation in Multi-DoF Robots

arXiv:2605.12689v1 Announce Type: new Abstract: In this paper, we present a novel hybrid approach that combines Reinforcement Learning (RL) with Dynamic Window Approach (DWA) for adaptive 3D local nav

local-aiarxiv-cs-ro

AdaFocus: Adaptive Relevance-Diversity Sampling with Zero-Cache Look-back for Efficient Long Video Understanding

arXiv:2605.12954v1 Announce Type: cross Abstract: Long video understanding is heavily bottlenecked by a rigid one-shot paradigm: existing methods either densely encode videos at prohibitive memory and

Adaptive Kernel Density Estimation with Pre-training

arXiv:2605.13092v1 Announce Type: cross Abstract: Density estimation in high-dimensional settings is an important and challenging statistical problem.Traditional methods based on kernel smoothing are

local-aiarxiv-cs-lg

Agentic Interpretation: Lattice-Structured Evidence for LLM-Based Program Analysis

arXiv:2605.12694v1 Announce Type: cross Abstract: Large language models can consult information that fixed static analyzers cannot, such as documentation, current security advisories, version-specific

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

arXiv:2502.15761v3 Announce Type: replace-cross Abstract: The deployment of large language models (LLMs) on extended reality (XR) devices has great potential to advance the field of human-AI interacti

An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

arXiv:2605.13221v1 Announce Type: new Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms

anima pv2 vs anima pv3 vs anima-base v1

local-air-stablediffusion

Anima is a 2 billion parameter text-to-image model focused on anime concepts, characters, and styles, with capability for non-photorealistic content. Preview versions are intermediate model checkpoint

are there memory limit settings that can be changed?

Ollama offers several memory management settings, including the ability to reduce context length (context window) to decrease VRAM usage, which can save 0.2-0.4GB for 7-8B models when reduced from 8K

local-air-ollama

b9140

The search did not return specific information about the b9140 release. Based on the context, b9140 is a specific build number from the llama.cpp project releases. llama.cpp is an LLM inference implem

b9142

Release b9142 is an intermediate build of llama.cpp, a C/C++ library for running large language model inference on consumer hardware. llama.cpp performs inference on various large language models and

b9143

The search results show releases near b9143 (specifically b9134 was the most recent) but do not contain specific details about b9143 itself. Based on the available information: llama.cpp is a C/C++ im

b9144

llama.cpp is an open source software library that performs inference on various large language models such as Llama. Build b9144 is an intermediate release version of the llama.cpp project from the gg

b9145

The search results show recent llama.cpp releases but don't contain specific details about the b9145 build. Based on the pattern of changes in recent releases, b9145 likely includes updates to SYCL/Le

b9148

Release b9148 of llama.cpp adds a non-backtracking tokenizer handler for Qwen3.5 to handle Unicode regex patterns for letters and combining marks, addressing stack overflow issues on long inputs. The

b9150

b9150 is a llama.cpp release that adds a custom Unicode regex handler for Qwen3.5's tokenizer to prevent stack overflows on long inputs. The release includes test vocabularies and updated test configu

b9151

Release b9151 of llama.cpp includes enhancements to Unicode regex handling for Qwen3.5's tokenizer, adding a custom non-backtracking handler to prevent stack overflows on long inputs. The release also

b9156

B9156 is a llama.cpp release that adds enhanced Unicode regex handling for Qwen3.5 tokenization, implementing a non-backtracking handler to prevent stack overflows on long inputs . The release include

b9158

B9158 is a llama.cpp release that adds a custom Unicode regex handler for Qwen3.5 tokenization to prevent stack overflows on long inputs. The release includes test vocabulary files and expected output

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements t…

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements to caching for faster inference overall. Turn on Developer Mod

local-ailm-studio--x

Beyond Individual Mimicry: Constructing Human-Like Social network with Graph-Augmented LLM Agents

arXiv:2605.12512v1 Announce Type: cross Abstract: Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade soci

BlockVLA: Accelerating Autoregressive VLA via Block Diffusion Finetuning

arXiv:2605.13382v1 Announce Type: new Abstract: While autoregressive (AR) Vision-Language-Action (VLA) models have demonstrated formidable reasoning capabilities in robotic tasks, their sequential dec

local-aiarxiv-cs-ro

CANTANTE: Optimizing Agentic Systems via Contrastive Credit Attribution

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

ChannelKAN: Multi-Scale Dual-Domain Channel Prediction via Hybrid CNN-KAN Architecture

arXiv:2605.12553v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for improving the reliability and spectral efficiency of massive MIMO-OFDM systems in

CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy

arXiv:2605.13038v1 Announce Type: cross Abstract: Geometric estimation including depth estimation and scene reconstruction is a crucial technique for colonoscopy which can provide surgeons with 3D spa

Comfyui error Missing Models (1)AttributeError: module 'tensorflow' has no attribute 'Tensor'

local-air-stablediffusion

This error in ComfyUI occurs when the einops library encounters a broken TensorFlow installation while performing multi-backend type checks, even though ComfyUI itself is PyTorch-based. The primary so

Comparing tokens per second of common models

This Reddit post likely compares inference performance metrics across popular language models running on Ollama, measuring tokens per second as a key performance indicator. The post would help users a

local-air-ollama

Contextual Bandits for Resource-Constrained Devices using Probabilistic Learning

arXiv:2605.13346v1 Announce Type: new Abstract: Contextual bandits (CB) are online sequential decision-making problems under partial feedback that underpin many adaptive services. There is a growing d

local-aiarxiv-cs-lg

Discovery of Hidden Miscalibration Regimes

arXiv:2605.13484v1 Announce Type: cross Abstract: Calibration is commonly evaluated by comparing model confidence with its empirical correctness, implicitly treating reliability as a function of the c

Does Engram Do Memory Retrieval in Autoregressive Image Generation?

arXiv:2605.13179v1 Announce Type: new Abstract: The Engram module -- a hash-keyed, O(1) associative memory injected into Transformer layers -- was recently shown to improve large language model pretra

Drag within Prior Distribution: Text-Conditioned Point-Based Image Editing within Distribution Constraints

arXiv:2605.13349v1 Announce Type: new Abstract: Diffusion-based point editing methods have gained significant traction in image editing tasks due to their ability to manipulate image semantics and fin

EDITS: Enhancing Dataset Distillation with Implicit Textual Semantics

arXiv:2509.13858v2 Announce Type: replace Abstract: Dataset distillation aims to synthesize a compact dataset from the original large-scale one, enabling highly efficient learning while preserving com