Search: “models”

Chemically Meaningful Textualization Enables Explainable Validation of Metal-Organic Frameworks by Large Language Models

arXiv:2608.11283v1 Announce Type: cross Abstract: Computation-ready metal-organic framework (MOF) databases are essential for high-throughput screening, yet many reported crystal structures remain che

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Local Ai

Class Activation Mapping in Explainable Computer Vision: A Method-Centered Review of CNN, Transformer, and Foundation-Model-Era Visual Explanations

DGX agent

arXiv:2608.12299v1 Announce Type: cross Abstract: Class activation mapping (CAM) is one of the most widely used visual explanation families in explainable artificial intelligence. Its purpose is intui

local-aiarxiv-cs-ai

13 Aug 2026

CYBER SLAYER — a 1995-style action trailer made with MiniMax H3, Wan 2.2 and ComfyUI

model-releasesr-stablediffusion

Hey all! This started as a way to mark my 15th anniversary working in video game cinematics. I thought it would be fun to make a completely ridiculous, fictionalized version of how I got into the indu

Tutorials

Fine-Tuning Generative Models for Extreme Events via CVaR-Penalized Wasserstein Gradient Flows

arXiv:2608.11544v1 Announce Type: cross Abstract: We propose CVaR-penalized Generative Particle Algorithm (CVaR-GPA), a robust, tail-agnostic algorithm for fine-tuning generative models to learn heavy

tutorialsarxiv-cs-lg

Governing Agentic AI in FinTech

model-releasesarxiv-cs-ai

arXiv:2608.11344v1 Announce Type: cross Abstract: Financial institutions are delegating consequential decisions to agentic AI systems that decompose goals, coordinate models and tools, and act with li

Grounding Large Language Models as Generalizable Policies in Network Control

arXiv:2512.11839v2 Announce Type: replace Abstract: Designing generalizable control policies that operate reliably under changing conditions is essential for robust network services in modern digital

safetyarxiv-cs-lg

Keep the Future, Drop the Rollout: RIFT for World Action Models

arXiv:2608.11521v1 Announce Type: cross Abstract: World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether acti

Latent variable models for simultaneous EOV identification and removal in population-based SHM

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

Self-Evolving Embodied Agents via Skill-Harness Evolution

model-releasesarxiv-cs-cl

arXiv:2608.11350v1 Announce Type: new Abstract: Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills,

Agents

Chain of Spatial Thoughts: Modality-Agnostic Spatial Grounding for Vision Language Models

arXiv:2608.10278v1 Announce Type: new Abstract: Spatial understanding is fundamental to embodied intelligence, underpinning applications such as robotic manipulation, embodied navigation, and autonomo

agentsarxiv-cs-cv

Covert Visual Prompt Injection against Commercial Multimodal Large Language Models

arXiv:2603.29418v2 Announce Type: replace-cross Abstract: Although multimodal large language models (MLLMs) are increasingly deployed in real-world applications, their instruction-following behavior l

Diffract: Spectral View of LLM Domain Adaptation

arXiv:2608.10850v1 Announce Type: new Abstract: We study continual pre-training (CPT) as a mechanism for adapting general-purpose large language models to specialized domains: mathematics, instruction

Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language Models

arXiv:2608.10525v1 Announce Type: cross Abstract: Historical context integration presents a fundamental challenge for Vision-Language Models (VLMs) in sequential decision-making tasks. Current VLMs pr

How Robust Are LLMs to Vietnamese Dialects?

model-releasesarxiv-cs-cl

arXiv:2608.10414v1 Announce Type: new Abstract: Large Language Models (LLMs) are typically evaluated on standard written Vietnamese, yet everyday communication frequently involves regional dialects th

Optimized Sequential Testing for Binary Ensemble Classifiers

arXiv:2606.15237v1 Announce Type: cross Abstract: Ensemble classifiers are predictive models that combine the results of simpler base models, often by majority vote. A classic example is random forest

Self-Geometry: GT-Free and Plug-and-Play Test-Time Adaptation for Geometrically Consistent 3D Vision Foundation Models

arXiv:2608.10708v1 Announce Type: new Abstract: Recent Vision Foundation Models (VFMs) predict depth, camera pose, and pointmap in a single forward pass without per-scene optimization, achieving stron

researcharxiv-cs-cv

TEASR: Training-Efficient Any-Step Diffusion Transformer for Real-World Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2606.16188v2 Announce Type: replace Abstract: Diffusion models excel in Real-World Image Super-Resolution (Real-ISR) due to their powerful generative priors but suffer from slow iterative sampli

Tutorials

Twitch says it intends to use videos streamed on its platform to help train Amazon's generative AI models and tells creators how to opt out (Amanda Silberling/TechCrunch)

Amanda Silberling / TechCrunch: Twitch says it intends to use videos streamed on its platform to help train Amazon's generative AI models and tells creators how to opt out — The streaming platform Twi

tutorialstechmeme

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: …

model-releasesclem-delangue--x

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B

Local Ai

Bootstrapping Vision-Language Model for Hysteroscopic Surgical Scene Segmentation

arXiv:2608.09302v1 Announce Type: new Abstract: Hysteroscopic surgical scene segmentation plays a pivotal role in understanding the hysteroscopic intraoperative environment as well as computer-assiste

local-aiarxiv-cs-cv

Agents

Bounding Hallucinations: Merlin-Arthur Protocols for Mutual-Information Bounds in Language Models

arXiv:2512.11614v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) relies on retrieved context to guide large language models (LLM), yet treats the retrieval as a heuristic

agentsarxiv-cs-ai

Causal State-Space Model for Causal Inference: Estimating Longitudinal Individual Treatment Effects

arXiv:2608.08288v1 Announce Type: new Abstract: Estimating counterfactual outcomes over time from longitudinal observational data is central to clinical decision support. Existing methods rely on doma

researcharxiv-cs-lg

CDGC-Net: 3D Medical Image Segmentation with Cooperative Dual-Scale Self-Attention and Grouped Channel Modeling

arXiv:2608.08575v1 Announce Type: cross Abstract: Accurate 3D medical image segmentation requires the integration of long-range anatomical context with fine boundary detail. Existing methods often mod

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models

arXiv:2608.08999v1 Announce Type: cross Abstract: The proliferation of AI-generated images produced by Latent Diffusion Models (LDMs) has raised critical concerns regarding copyright infringement and

DeepSeek V4 Flash 0731 at 27+ t/s decode on Strix Halo — Vulkan + DSpark full guide

model-releasesr-localllama

Been benchmarking DSv4 Flash 0731 on a Flow Z13 (Ryzen AI MAX+ 395, Radeon 8060S / gfx1151, 128GB LPDDR5X) for the past week. Figured I'd share what actually works and what doesn't — there are a lot o

Hardware

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching

arXiv:2608.09444v1 Announce Type: cross Abstract: A main promise of looped language models (LMs) is depth-adaptive inference. By iterating a block of shared layers a variable number of times, the mode

hardwarearxiv-cs-cl

Tutorials

Did the Grid Erase the Event? EndoClock for Auditing Medical World-Model Pipelines

arXiv:2608.09266v1 Announce Type: new Abstract: Medical world models commonly learn from multimodal recordings synchronized onto a fixed-rate grid. This preprocessing resamples each native stream onto

tutorialsarxiv-cs-cv

Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models

arXiv:2601.03115v2 Announce Type: replace Abstract: Emotion is a central dimension of spoken communication, yet, we still lack a mechanistic account of how modern large audio-language models (LALMs) e

safetyarxiv-cs-cl

From Inaudible Inputs to Model Failures: Low-Frequency Safety Risks in LALMs

arXiv:2608.09158v1 Announce Type: cross Abstract: Large audio-language models (LALMs) have demonstrated strong capabilities in understanding diverse audio inputs. This diversity includes low-frequency

Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models

arXiv:2608.08010v1 Announce Type: cross Abstract: Time series forecasting (TSF) plays an important role in a wide range of real-world applications. Recently, time series foundation models (TSFMs), pre

How Do Large Language Models Judge Social Attraction? Evidence from Theory-Grounded Persona Ratings Across Multiple LLMs and Humans

arXiv:2608.09717v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to perform subjective evaluations traditionally made by humans, yet their validity as social judges

How ONESTRUCTION built the Ishigaki-IDS foundation model with AWS GenAIIC

ONESTRUCTION, with technical advisory from the AWS Generative AI Innovation Center, built Ishigaki-IDS, a foundation model specialized for construction and BIM workflows. This architectural case study

applicationsaws-ml-blog

Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction

arXiv:2608.08825v1 Announce Type: cross Abstract: Foundation models for time series forecasting demonstrate impressive zero-shot generalization but often underperform on specialized domains such as hi

Hardware

IBM and Together AI sign a $240M, multi-year deal to build an AI inference cluster on IBM Cloud, using Nvidia's HGX B300 systems, to support open-source models (Anhata Rooprai/Reuters)

Anhata Rooprai / Reuters: IBM and Together AI sign a 240M, multi-year deal to build an AI inference cluster on IBM Cloud, using Nvidia's HGX B300 systems, to support open-source models — IBM (IBM.N) a

hardwaretechmeme

Intelligence Foundation Model: A New Perspective to Approach Artificial General Intelligence

arXiv:2511.10119v4 Announce Type: replace Abstract: We propose a new perspective for approaching artificial general intelligence (AGI) through an intelligence foundation model (IFM). Unlike existing f

KVDiagnosis: A Diagnostic Benchmark for KV-Cache Compression in Long-Context Language Models

model-releasesarxiv-cs-ai

arXiv:2608.09412v1 Announce Type: new Abstract: KV-cache compression reduces long-context memory, but aggregate task scores reveal neither which correct executions fail nor why. We present KVDiagnosis

LF{}^{2}AR: Accounting for Layerwise Dynamics to Improve Multimodal Adaptation of Language Models

arXiv:2503.06211v3 Announce Type: replace-cross Abstract: Text-pretrained language models (LMs) encode rich world knowledge, but adapting them to process and generate perceptual modalities such as aud

Multi-Branch Policy Optimization for Multimodal Large Language Models

arXiv:2608.07581v1 Announce Type: cross Abstract: Group-based reinforcement learning methods for multimodal large language models typically rely on trajectory-level credit assignment that applies a si

Multimodal Model Diffing for Feature Discovery and Control

arXiv:2608.09928v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to

NeuroBreak: Unveil Internal Jailbreak Mechanisms in Large Language Models

arXiv:2509.03985v2 Announce Type: replace-cross Abstract: In deployment and application, large language models (LLMs) typically undergo safety alignment to prevent illegal and unethical outputs. Howev

Nonlinear Model Predictive Control of a Robotic Soft Esophagus

arXiv:2608.09602v1 Announce Type: new Abstract: Strictures caused by esophageal cancer can narrow down the esophageal lumen, leading to dysphagia. Palliation of dysphagia has driven the development of

researcharxiv-cs-ro

OATS: Online Data Augmentation for Time Series Foundation Models

arXiv:2601.19040v2 Announce Type: replace Abstract: Time Series Foundation Models (TSFMs) are a powerful paradigm for time series analysis and are often enhanced by synthetic data augmentation to impr

researcharxiv-cs-lg

Open-World Semantic Segmentation with Sensitivity Modeling

arXiv:2608.08308v1 Announce Type: cross Abstract: Modern vision systems must operate in 'open-world' settings, where models must recognize known categories and detect unseen or anomalous content. Conv

Pragmatic Attack Surface: Vulnerabilities of Implicit Context in Large Language Models

arXiv:2608.09551v1 Announce Type: new Abstract: In the era of large language models (LLMs), attackers often manipulate natural language to elicit unsafe or harmful outputs, creating a new natural lang

safetyarxiv-cs-cl

Predicting blood clot growth from sparse post-onset measurements with latent neural differential equations

arXiv:2608.08165v1 Announce Type: new Abstract: Computational models of blood clotting improve understanding of thrombus formation, but their clinical application remains limited because many model in

PRISM-Delta: Differential Subspace Steering for Prompt Highlighting in Large Language Models

arXiv:2603.10705v2 Announce Type: replace Abstract: Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing

researcharxiv-cs-cl

Quality-Diversity Stress Tests for Process Reward Models:What Archive Coverage Can and Cannot Certify

arXiv:2608.08008v1 Announce Type: new Abstract: Process reward models (PRMs) score intermediate reasoning steps and are widely used for search, ranking, and training, but optimization can exploit thes

researcharxiv-cs-lg

RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance

arXiv:2608.09853v1 Announce Type: cross Abstract: General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning value-related capabilities from

safetyarxiv-cs-cv