Search: “models”

arXiv:2608.14820v1 Announce Type: cross Abstract: Handover (HO) management in vehicular networks requires fast and reliable decision-making under highly dynamic conditions. While machine learning (ML)

arXiv:2608.16622v1 Announce Type: cross Abstract: Multimodal harmful meme detection is typically formulated as image--text harmfulness classification. A model may correctly predict harmfulness while m

arXiv:2608.15008v1 Announce Type: new Abstract: Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely th

arXiv:2608.16689v1 Announce Type: cross Abstract: Instance-wise feature selection is a valuable tool for interpreting labeled data and the predictions of black-box models. In contrast to global featur

arXiv:2608.16222v1 Announce Type: cross Abstract: Humanoid intelligence requires learning over an extremely diverse space of whole-body motions and physically grounded interactions. However, existing

Im running a Ryzen 7 5700x, a 3080ti (12GB) with 64GB of RAM. I’m still new to Local AI, and I’ve tried it in the past but none of the previous generations of AI have been good enough for my specific

If you’re building an “agent over your PDFs” in 2026, one of the most underrated things you can do is to provide exact grounding back to the source document for any agentic answers. Specifically, show

arXiv:2608.16344v1 Announce Type: new Abstract: Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and eval

arXiv:2608.14744v1 Announce Type: new Abstract: Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation.

arXiv:2608.16424v1 Announce Type: new Abstract: Generative modeling has shown increasing promise for predicting cellular perturbation effects under chemical compound treatments. Existing approaches ei

arXiv:2608.16763v1 Announce Type: new Abstract: Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency,

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

This took one prompt to build, and another follow up prompt to fix two issues (player got stuck with the bomb and broken enemies path-finding), this is only html, css and js, no external assets, all d

arXiv:2608.15299v1 Announce Type: cross Abstract: Sparsely-activated Mixture-of-Experts (MoE) Transformers universally fix the same number of routed experts across all layers, a convention that ignore

arXiv:2608.16514v1 Announce Type: cross Abstract: Human visual search is serial: the fovea must land on a candidate to confirm it, and those landings form a scanpath. Whether multimodal large language

arXiv:2602.12407v3 Announce Type: replace-cross Abstract: Background: Robot-assisted minimally invasive surgery (RMIS) research increasingly relies on multimodal data, yet access to proprietary robot

arXiv:2608.15187v1 Announce Type: new Abstract: Scientific machine learning for partial differential equations commonly targets solution fields, as in physics-informed neural networks, or solution map

arXiv:2608.15830v1 Announce Type: new Abstract: Real-time tiny target perception in high-resolution imagery is critical for embodied Search-and-Rescue (SAR) missions. However, strict Size, Weight, and

arXiv:2608.15045v1 Announce Type: new Abstract: We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability.

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:2608.14767v1 Announce Type: cross Abstract: Automated vehicles must explain their decisions in ways that passengers can understand, monitor, and trust. Existing language-annotated driving datase

arXiv:2608.15573v1 Announce Type: new Abstract: Reliable long-horizon planning remains a key challenge in end-to-end autonomous driving. By accounting for future motion evolution and potential consequ

arXiv:2608.14710v1 Announce Type: cross Abstract: Predicting spatial gene expression from hematoxylin and eosin (H&E)-stained images offers a cost-effective alternative to spatial transcriptomics (ST)

arXiv:2512.03444v2 Announce Type: replace Abstract: Deep learning methods have significantly enhanced motion planning for robotic manipulators by leveraging prior experiences within planning datasets.

arXiv:2608.16717v1 Announce Type: new Abstract: Video generation is rapidly evolving from single-shot clips to multi-shot narratives, where the human character serves as the core narrative anchor. How

arXiv:2608.15285v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) is a natural way to adapt pretrained vision-language-action (VLA) policies, but most adapter designs apply temp

arXiv:2608.14658v1 Announce Type: cross Abstract: We introduce pico-type, a byte-level multi-head content classifier with approximately 1.5 million parameters that simultaneously predicts seven conten

arXiv:2608.14566v1 Announce Type: new Abstract: Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whet

arXiv:2608.16289v1 Announce Type: new Abstract: Automated e-commerce poster design requires both high-quality poster generation and flexible editing of existing designs. However, most existing methods

arXiv:2508.08517v2 Announce Type: replace-cross Abstract: Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to

arXiv:2608.14652v1 Announce Type: cross Abstract: The development of 0.1^{irc} global weather forecasting models based on machine learning (ML) is constrained by the limited availability of high-resol

arXiv:2608.16813v1 Announce Type: new Abstract: Agents now write knowledge graphs, but knowledge-graph stores still carry defaults set when humans curated them: accept writes now and clean later, keep

arXiv:2608.16011v1 Announce Type: new Abstract: We introduce ReRef-3D, a benchmark for language-guided placement in 3D scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning

arXiv:2608.15694v1 Announce Type: cross Abstract: Conditional image-to-image generators are single-shot: they map input features to an output in one forward pass and treat it as final, with no opportu

arXiv:2608.15863v1 Announce Type: cross Abstract: Operating household appliances requires long-horizon planning that is state-dependent and robust to disturbances, yet existing large models fall short

arXiv:2608.14647v1 Announce Type: cross Abstract: Dirty-history rollouts make multi-turn on-policy self-distillation (OPSD) brittle: once a student emits an erroneous intermediate reply, later turns a

arXiv:2608.15632v1 Announce Type: cross Abstract: Neural representations have become a central tool for studying the internal mechanisms of modern AI models, yet their complex high-dimensional structu

arXiv:2608.14725v1 Announce Type: new Abstract: We present a novel causal approach to interpretability for computer vision models that dynamically masks the input image prior to classification. The in

arXiv:2608.16008v1 Announce Type: new Abstract: Text-driven human motion editing aims to modify existing motion sequences according to natural language instructions while maintaining the structural co

arXiv:2608.15452v1 Announce Type: new Abstract: Current flow matching models learn to transport the source i.i.d. Gaussian noise into the target distribution of natural images, yet this source distrib

arXiv:2601.06404v2 Announce Type: replace Abstract: Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incom

Strong enough to keep up with the frontier, light enough to run on your own laptop. Come see what it can do! ⚡ It's official: Qwen3.8-27B just scored 52 on the @ArtificialAnlys Intelligence Index. We

arXiv:2608.16050v1 Announce Type: cross Abstract: Spreadsheets are a primary medium for publishing tabular data, yet automatically extracting structured content from them remains difficult due to hete

arXiv:2608.15897v1 Announce Type: new Abstract: Robot sensor designs, particularly tactile sensors, are highly diverse and evolve rapidly. Modeling each sensor in simulation demands substantial domain

arXiv:2608.15763v1 Announce Type: new Abstract: AI-powered digital-avatar streamers in live e-commerce must answer product questions, engage viewers, and execute changing business strategies in real t

arXiv:2608.15394v1 Announce Type: new Abstract: Human perception of time is subjective. Well-documented temporal illusions show that the brain relies on context and relational cues for judging duratio