Search: “models”

arXiv:2604.08565v1 Announce Type: cross Abstract: At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer's compute budget, motivating sparse alternatives to

arXiv:2604.09164v1 Announce Type: new Abstract: Temporal human action detection aims to identify and localize action segments within untrimmed videos, serving as a pivotal task in video understanding.

arXiv:2604.09130v1 Announce Type: cross Abstract: As SE(3)-equivariant graph neural networks mature as a core tool for 3D atomistic modeling, improving their efficiency, expressivity, and physical con

arXiv:2412.12686v3 Announce Type: replace Abstract: Current large language models (LLMs) often exhibit imbalances in multilingual capabilities and cultural adaptability, largely attributed to their En

arXiv:2604.06832v2 Announce Type: replace Abstract: Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference

arXiv:2410.15001v5 Announce Type: replace Abstract: Scalability of Graph Neural Networks (GNNs) remains a significant challenge. To tackle this, methods like coarsening, condensation, and computation

arXiv:2601.18150v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence

arXiv:2604.09175v1 Announce Type: cross Abstract: We develop a theory of generalization and scaling for Mixture-of-Experts (MoE) Transformers that cleanly separates active per-input capacity from rout

This r/StableDiffusion thread addresses user difficulties running ACE-Step 1.5 XL in ComfyUI — an AI music generation model that was released on April 2, 2026, featuring a 4B-parameter DiT decoder for

arXiv:2604.09016v1 Announce Type: cross Abstract: This study addresses the challenge of creating datasets for cybercrime analysis while complying with the requirements of regulations such as the Gener

This Reddit thread on r/ollama likely discusses where and how to use Ollama's cloud offering, which allows models to run without a powerful local GPU by automatically offloading computation to Ollama'

arXiv:2604.09512v1 Announce Type: new Abstract: Transformers have emerged as the dominant neural-network architecture, achieving state-of-the-art performance in language processing and computer vision

arXiv:2410.08559v5 Announce Type: replace-cross Abstract: Electrocardiogram (ECG) captures the heart's electrical signals, offering valuable information for diagnosing cardiac conditions. However, the

arXiv:2509.24164v2 Announce Type: replace Abstract: We investigate the mechanistic underpinnings of in-context learning (ICL) in large language models by reconciling two dominant perspectives: the com

arXiv:2604.09352v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is crucial for autonomous lunar rover navigation using electro-optical cameras. However, deploying terrestrial MDE netw

arXiv:2604.09124v1 Announce Type: cross Abstract: Deploying DNNs on System-on-Chips (SoC) with multiple heterogeneous acceleration engines is challenging, and the majority of deployment frameworks can

arXiv:2604.08788v1 Announce Type: new Abstract: Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless

arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to

arXiv:2604.08947v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly prevalent in text simplification, systematically evaluating their outputs across diverse prompting

A new speed-focused LoRA for the Wan 2.2 video generation model, released by the LightX2V project on April 26, 2024, shared on the r/StableDiffusion community. The LightX2V distilled LoRA dramatically

arXiv:2604.09058v1 Announce Type: cross Abstract: Long-horizon spatiotemporal prediction remains a challenging problem due to cumulative errors, noise amplification, and the lack of physical consisten

arXiv:2604.08986v1 Announce Type: cross Abstract: Persona prompting has been widely adopted to steer large language models (LLMs) behavior and improve their instruction performance by assigning specif

arXiv:2604.09499v1 Announce Type: new Abstract: Autonomous racing without prebuilt maps is a grand challenge for embedded robotics that requires kinodynamic planning from instantaneous sensor data at

arXiv:2604.08810v1 Announce Type: new Abstract: Graph neural networks (GNNs) are increasingly applied to physical design tasks such as congestion prediction and wirelength estimation, yet progress is

arXiv:2604.08628v1 Announce Type: cross Abstract: Unauthorized disclosure of confidential documents demands robust, low-leakage classification. In real work environments, there is a lot of inflow and

arXiv:2604.08905v1 Announce Type: new Abstract: Reinforcement learning (RL) is effective in enhancing the accuracy of large language models in complex reasoning tasks. Existing RL policy optimization

arXiv:2509.24169v2 Announce Type: replace Abstract: Large Language Models (LLMs) can perform new tasks from in-context demonstrations, a phenomenon known as in-context learning (ICL). Recent work sugg

arXiv:2604.09047v1 Announce Type: new Abstract: Dental implant abutments serve as the geometric and biomechanical interface between the implant fixture and the prosthetic crown, yet their design relie

arXiv:2604.09439v1 Announce Type: cross Abstract: In this paper, we propose a sequential recommendation model that integrates Time-aware personalization, Multi-interest personalization, and Explanatio

arXiv:2604.09008v1 Announce Type: cross Abstract: The widespread use of English as a Second or Foreign Language (ESFL) has sparked a paradigm shift: ESFL is not seen merely as a deviation from standar

arXiv:2603.08146v3 Announce Type: replace Abstract: Existing frameworks for gradient-based training of spiking neural networks face a trade-off: discrete-time methods using surrogate gradients support

This Reddit post from r/StableDiffusion announces the release of 'Distilled v1.1,' an updated version of a knowledge-distilled Stable Diffusion model, likely building on prior distillation work that p

This r/StableDiffusion post demonstrates running AceStep 1.5 XL Turbo alongside LTX Video 2.3 on a laptop equipped with an 8GB NVIDIA RTX 5060 GPU — a notable feat given that the XL (4B) model require

This Reddit thread from r/StableDiffusion discusses the compatibility of compact LLMs — Qwen3.5 4B and Gemma 4 E4B — as text encoder/LLM components within Z-Image and Z-Image Turbo image generation wo

Deepagents is an open-source project by LangChain that implements deep research-style agentic workflows, enabling AI agents to perform iterative, multi-step research and reasoning tasks. The repositor

From this perspective, Gemini is also worse than the original Bard. Sydney was the original sin of LLMs anthropormism, but also got the idea that AIs can sometimes be better with personalities right.

This Reddit thread discusses how to configure Ollama for use with Claude Code locally, covering two key setup steps. By default, Ollama uses a context window of only 4,096 tokens — insufficient for Cl

Lorsque vous avez le besoin de lever des dizaines de milliards de dollars, l'importance de créer un contexte de stupéfaction est déterminent. Les soi-disantes failles de sécurité détectées par Mythos,

This Reddit post from r/StableDiffusion showcases a community-created ComfyUI workflow for the LTX-2.3 model — a DiT-based audio-video foundation model capable of generating synchronized video and aud

memory is core to how you get enhanced output. it is key to defensibility across AI products: 1. increase personalization and therefore lock-in 2. benefit from distribution through multiplayer-AI inte

Harrison Chase discusses the concept of 'memory lock-in' in AI agent frameworks, arguing that the switching cost doesn't occur at the point of adoption but rather accumulates over time as agents build

Memory features in AI platforms represent a strategic mechanism for increasing user retention and platform lock-in, as personalized context and learned preferences become increasingly difficult to mig

This Reddit thread from r/StableDiffusion addresses a common image quality issue where Tensor Art — a cloud-based Stable Diffusion platform — produces outputs with heavy, unwanted color tints. The dis

A lot of our education on writing well focuses on logic, clarity, and argument. AI will force us to think more about style. The boredom that comes from everything on the internet reading Claude-y now,

If you don't own the memory, you don't own the agent: - memory is what makes your agent get smarter over time - without it, anyone with the same tools can copy your agent overnight - with it, you buil

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