Search: “models”

arXiv:2510.18034v2 Announce Type: replace-cross Abstract: Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emer

arXiv:2511.20779v2 Announce Type: replace Abstract: Globally interpretable models are a promising approach for trustworthy AI in safety-critical domains. Alongside global explanations, detailed local

arXiv:2603.17812v2 Announce Type: replace-cross Abstract: Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previo

arXiv:2601.08950v3 Announce Type: replace Abstract: Despite their growing adoption in education, LLMs remain misaligned with the core principle of effective tutoring: the dialogic construction of know

arXiv:2604.07518v1 Announce Type: new Abstract: Vision-Language Models often struggle with complex visual reasoning due to the visual information loss in textual CoT. Existing methods either add the c

Ollama Cloud offers Free, Pro ($20/month), and Max ($100/month) subscription tiers for cloud-hosted inference, but token generation speed depends on model size, architecture, and hardware optimiza...

arXiv:2604.04344v2 Announce Type: replace Abstract: We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produc

arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a vector val

arXiv:2511.15496v2 Announce Type: replace Abstract: Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. M

A 2-stage upscaling workflow using FLUX.2 Klein in ComfyUI combines the model's image-editing capabilities with a secondary upscaler (such as SeedVR2) to produce high-resolution outputs — for examp...

arXiv:2604.06403v1 Announce Type: cross Abstract: The paper presents an approach for the recognition of toxic habits named entities in Spanish clinical texts. The approach was developed for the ToxHab

arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

arXiv:2604.06215v1 Announce Type: cross Abstract: The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical

arXiv:2604.08046v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current res

arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s

@IeloEmanuele is on a roll! you can now use claude code's advisor strategy with @LangChain agents because langchain/deepagents are provider agnostic, you can use different providers for your advisor a

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing so much in deepagents) we always wanted to run llms in a loop

arXiv:2402.08267v3 Announce Type: replace Abstract: Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is

arXiv:2604.07034v1 Announce Type: cross Abstract: We present KITE, a training-free, keyframe-anchored, layout-grounded front-end that converts long robot-execution videos into compact, interpretable t

arXiv:2604.06438v1 Announce Type: cross Abstract: Forecasters often choose retraining schedules by convention rather than by an explicit decision rule. This paper gives that decision a posterior-space

arXiv:2604.07146v2 Announce Type: replace Abstract: Knowledge-based visual question answering (KB-VQA) requires vision-language models to understand images and use external knowledge, especially for r

arXiv:2604.07966v1 Announce Type: new Abstract: Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as

LiteParse is the best document parsing library for coding agents. It's free, fast, integrates natively with the LLM's native visual understanding capabilities, and comes with support for 50+ formats a

arXiv:2604.07822v1 Announce Type: new Abstract: We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models

arXiv:2604.07143v1 Announce Type: new Abstract: We introduce Lumbermark, a robust divisive clustering algorithm capable of detecting clusters of varying sizes, densities, and shapes. Lumbermark iterat

arXiv:2604.02445v2 Announce Type: replace Abstract: Matrix Profile (MP) methods are an interpretable and scalable family of distance-based methods for time-series anomaly detection, but strong benchma

arXiv:2604.07747v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve low-k reasoning accuracy while narrowing solution coverage on challenging math que

arXiv:2603.20654v4 Announce Type: replace-cross Abstract: Classical Amdahl's Law conceptualized the limit of speedup for an era of fixed serial-parallel decomposition and homogeneous replication. Mode

arXiv:2604.07741v1 Announce Type: new Abstract: Audio-visual deepfake detection typically employs a complementary multi-modal model to check the forgery traces in the video. These methods primarily ex

arXiv:2411.19121v2 Announce Type: replace-cross Abstract: While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sam

arXiv:2603.11633v2 Announce Type: replace Abstract: Recent unified 3D generation models have made remarkable progress in producing high-quality 3D assets from a single image. Notably, layout-aware app

In 2025, CivitAI underwent several significant platform changes. In April–May 2025, CivitAI tightened rules around extreme/illegal content and real-person likenesses. After its payment processor...

arXiv:2602.16005v2 Announce Type: replace-cross Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challen

arXiv:2604.07788v1 Announce Type: cross Abstract: We introduce PeReGrINE, a benchmark and evaluation framework for personalized review generation grounded in graph-structured user--item evidence. PeRe

arXiv:2603.23286v3 Announce Type: replace Abstract: Physical knot classification is a fine-grained task in which the intended cue is rope crossing structure, but high accuracy may still come from appe

arXiv:2511.19474v4 Announce Type: replace-cross Abstract: Automatically detecting abnormal events in videos is crucial for modern autonomous systems, yet existing Video Anomaly Detection (VAD) benchma

arXiv:2604.06279v1 Announce Type: cross Abstract: Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leadin

QueryData launches in preview today. It is a tool for translating natural language into database queries with near-100% accuracy. With QueryData, you can build agentic experiences across AlloyDB, Clou

The rapid evolution of AI is redefining industries, while also exposing organizations to new risks. At Google Cloud, we believe that modern cloud defense should have AI protection built in and accessi

arXiv:2604.07165v1 Announce Type: new Abstract: Reinforcement learning for Large Language Model agents is often hindered by sparse rewards in multi-step reasoning tasks. Existing approaches like Group

arXiv:2604.07595v1 Announce Type: cross Abstract: Language model agents reason from scratch on every query: each time an agent retrieves evidence and deliberates, the chain of thought is discarded and

arXiv:2503.02537v4 Announce Type: replace Abstract: Diffusion models have achieved remarkable progress across various visual generation tasks. However, their performance significantly declines when ge

arXiv:2512.01925v2 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have been driven by their emergent reasoning capabilities, particularly through long chain

arXiv:2604.07599v1 Announce Type: new Abstract: SANDO is a safe trajectory planner for 3D dynamic unknown environments, where obstacle locations and motions are unknown a priori and a collision-free p

arXiv:2604.03134v2 Announce Type: replace Abstract: Few-Shot Medical Image Segmentation (FSMIS) aims to segment novel object classes in medical images using only minimal annotated examples, addressing

arXiv:2604.03128v2 Announce Type: replace Abstract: On-policy distillation (OPD) has become a popular training paradigm in the LLM community. This paradigm selects a larger model as the teacher to pro