Search: “models”

LiveVVT: High-Fidelity Video Virtual Try-On in Real Time

arXiv:2608.26714v1 Announce Type: cross Abstract: Diffusion-based Video Virtual Try-On (VVT) achieves high visual fidelity through bidirectional spatio-temporal modeling, but complete-clip dependence

local-aiarxiv-cs-ai

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LLaVAFlow: Preserving Latent Alignment Flow for Parameter-Efficient Multimodal Fine-Tuning

DGX agent

arXiv:2608.26820v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) exhibit strong generalization, visual instruction tuning for downstream tasks inevitably causes catastrop

model-releasesarxiv-cs-cv

28 Aug 2026

LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade

arXiv:2509.07274v4 Announce Type: replace Abstract: Migration has been a core topic in German political debate, from postwar expellee displacement to labor migration and recent refugee movements. Larg

Multi-Dataset Inverse Problem Solving with Distributed Generative AI

arXiv:2608.26283v1 Announce Type: cross Abstract: Extracting a shared set of unknown, not directly measurable quantities from multiple, heterogeneous datasets is a common challenge across scientific d

Multi2AV-Safety: Benchmarking Safety in Multimodal-to-Audio-Video Generation

arXiv:2608.26535v1 Announce Type: new Abstract: Audio-video generation is rapidly moving from prompt-driven synthesis toward multimodal conditioning, where text, images, audio, and video can jointly s

On Scope Classification and Current Knowledge-Editing Benchmarks: A Negative Result, with INLAY as a Gradient-Free Case Study

arXiv:2608.26292v1 Announce Type: cross Abstract: Every memory-based knowledge editor in the SERAC lineage depends on a scope decision: given a query, does a stored edit apply? We report that current

PACE: A Unified Condense-and-Extract Paradigm for Fast VLM Inference

arXiv:2608.27206v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) demonstrate exceptional visual reasoning capabilities, yet their inference costs escalate rapidly with the proliferation

researcharxiv-cs-ai

Parameter Efficient Continual Learning for Sparse Event-Based Transformers

arXiv:2608.26720v1 Announce Type: new Abstract: Robotic and edge intelligence systems operate in dynamic environments where data arrives continuously, requiring models to adapt while preserving previo

Privacy Without Regret: Differentially Private Inference-Time Alignment

arXiv:2608.26324v1 Announce Type: new Abstract: Best-of-N (BoN) sampling is the simplest and most widely deployed inference-time alignment strategy, but it suffers from two distinct problems: reward h

Profit based evaluation of machine learning for nitrogen recommendations in winter wheat

arXiv:2608.27205v1 Announce Type: new Abstract: Nitrogen rates for winter wheat are set before the season, under unknown prices and weather. The standard UK advice does not respond to prices, yet rece

QuantumBoostNet: A Hybrid Classical-Quantum Architecture for Enhanced Accuracy in Cardiac Ultrasound View Identification

arXiv:2608.27302v1 Announce Type: new Abstract: Accurate identification of the correct view or angle in cardiac ultrasound (echocardiogram) is a critical component of cardiologic imaging. This step is

Reward-Informed Sparse Autoencoders and the Solution-Completeness Confound

arXiv:2608.26136v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) decompose language-model activations into sparse, interpretable features, and an appealing way to aim them at reasoning is to

Safety

Self-Generated Text Recognition: Quality Heuristics, Cross-Task Transfer, and Downstream Bias in LLM Evaluation

arXiv:2608.26159v1 Announce Type: cross Abstract: Self-Generated Text Recognition (SGTR)--the ability of an LLM to identify its own outputs--poses risks to AI safeguards that rely on LLMs as evaluator

safetyarxiv-cs-ai

Safety

SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning

arXiv:2608.26550v1 Announce Type: new Abstract: Reinforcement learning-based knowledge distillation has the potential to transfer complex reasoning from teacher to student models, yet it currently fac

safetyarxiv-cs-cl

Spreading the load: How Salesforce met Multi-AZ HA with SageMaker Inference Components

model-releasesaws-ml-blog

Learn how Salesforce used Amazon SageMaker AI Inference Component placement (the SchedulingConfig parameter) to distribute model copies across multiple Availability Zones, meeting their Multi-AZ high

When Text Misleads: Inconsistent-Aware Reasoning for Audio-Grounded Dialogue

arXiv:2608.27176v1 Announce Type: cross Abstract: Understanding spoken dialogue requires joint reasoning over lexical content and paralinguistic acoustic signals such as emotion and conversational int

Adaptive Regularization for Random Features: A Neighboring Early-Stopping Rule with Oracle-Rate Guarantees

arXiv:2608.25513v1 Announce Type: cross Abstract: Random feature methods provide a scalable approximation to kernel ridge regression (KRR), but the regularization parameter that yields the oracle lear

AFDBench: A Reasoning-First AI Scientist for NationalWeather Service Forecast Discussions

arXiv:2608.24954v1 Announce Type: new Abstract: Large language models (LLMs) hallucinate numerical values when generating high-stakes meteorological text, posing risks for weather communication. We pr

Applications

Are LLM-Enhanced GNNs Privacy-Safe?

arXiv:2608.25727v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced graph neural networks (GNNs) by enriching node representations with semantic information, giving ris

applicationsarxiv-cs-lg

Control-Oriented Learning for Dynamic Tracking and Stability Analysis of Soft Pneumatic Actuators

arXiv:2608.25171v1 Announce Type: new Abstract: Soft pneumatic actuators offer inherent compliance and safe interaction but remain difficult to model and control because of their highly nonlinear, dis

local-aiarxiv-cs-ro

CrossMambaTuning: Synergistic Spatial and Cross-Layer Adaptation for Machine Vision Compression

arXiv:2608.25568v1 Announce Type: new Abstract: To reduce deployment cost and retraining overhead, adapting pretrained learned image compression (LIC) models to downstream machine vision tasks has att

Emyx: Fast and efficient all-atom protein generation

arXiv:2606.19377v2 Announce Type: replace Abstract: Computational enzyme design requires generating proteins that scaffold catalytic residues and ligands, a task that demands both geometric accuracy a

Flower Hub: A Reproducible Benchmarking Platform for Federated Learning in Simulation and Deployment

arXiv:2608.25114v1 Announce Type: new Abstract: Federated learning (FL) has emerged as a key approach for training models across decentralized data, yet benchmarking in FL remains difficult to reprodu

Generalized Riesz Regression: A Unified Framework for Debiased Machine Learning with Riesz Representer Fitting under Bregman Divergence

arXiv:2601.07752v4 Announce Type: replace-cross Abstract: Estimating the Riesz representer is central to debiased machine learning, yet the generator and representer model determine which regression d

researcharxiv-cs-lg

Group-Shared Low-Rank Approximation for Mobile-Efficient Pointwise Convolutions in Large-Kernel CNNs

arXiv:2608.26069v1 Announce Type: new Abstract: Large-kernel Convolutional Neural Networks (CNNs) deliver remarkable performance in vision tasks by significantly expanding receptive fields, yet their

How Robust Are Automated Fact-Checking Systems? A Cross-Benchmark Evaluation

arXiv:2608.25934v1 Announce Type: cross Abstract: Automated fact-checking (AFC) systems retrieve evidence and predict claim veracity, yet evaluations omit simple baselines, systems are developed for a

MIMONet: Multi-scale Input and Multi-scale Output Network for Salient Object Detection

arXiv:2608.25733v1 Announce Type: new Abstract: The existing methods for saliency detection task focus on the application of multi-level features, aiming to take advantage of the respective strengths

Not All Attention Heads Contribute to Critical Visual Token Selection: Head-Aware Pruning Matters More

arXiv:2608.25332v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have exhibited impressive performance across diverse visual scenarios. However, this success comes at the cost of explosiv

researcharxiv-cs-cv

OmniPhys: A Unified Multimodal Benchmark for Physics Understanding and Generation from Chinese Educational Corpora

arXiv:2608.25398v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong abilities in solving diverse visual and textual reasoning tasks. However, their develo

Rare Diseases, Common Dilemmas: LLMs Prioritize Equal Resource Distribution over Patient Benefit in Decision-Making

arXiv:2608.25236v1 Announce Type: cross Abstract: Clinical decision-making often involves prioritizing ethical values, such as beneficence, non-maleficence, respecting a patient's autonomy, and justic

Reflection Steering: Disentangling Reflection from Reasoning in Activation Space for Token-Efficient Inference

arXiv:2608.25542v1 Announce Type: cross Abstract: Large reasoning models often produce reasoning traces with verification, revision, and backtracking. When reflection merely re-checks established resu

Synergising Local Geo-Environmental Characteristics with Spatial Context for Enhancing Landslide Susceptibility Mapping

arXiv:2608.24956v1 Announce Type: new Abstract: Data-driven methods are widely used in landslide susceptibility mapping (LSM) because they can effectively model the complex relationships between lands

local-aiarxiv-cs-cv

What's this Apodex thing? (AMA prep)

model-releasesr-localllama

A sticky popped up 'Hey, AMA today'. At first I thought I missed something, but I didn't see a single mention of it here so far, aside from having never heard of it. So, as the posting was devoid of i

ACE: A Self-Correcting Agentic Canvas Editor for Multi-Slide Presentation Automation

arXiv:2608.24103v1 Announce Type: new Abstract: Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two practical problems block reliable deployment:

Agents

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

arXiv:2608.23858v1 Announce Type: cross Abstract: The Agent Payments Protocol (AP2), introduced by Google, enables large language model (LLM)-driven shopping agents to authorize and execute payments o

agentsarxiv-cs-ai

BREAKING: GLM-5.3 Flash by @Zai_org debuts at 6th overall on Design Arena with a preliminary Elo of 1343. This places the MIT-licensed, nati…

model-releaseszhipu-ai--x

BREAKING: GLM-5.3 Flash by @Zai_org debuts at 6th overall on Design Arena with a preliminary Elo of 1343. This places the MIT-licensed, natively multimodal model in the same performance band as GLM-5.

Cross-Generation Optimization of YOLOv26, YOLOv11, and YOLOv8 for Fine-Grained Small-Object Detection and Instance Segmentation in Complex Orchards

arXiv:2608.23636v1 Announce Type: new Abstract: Small-object detection and instance segmentation remain challenging in orchard environments because of green-on-green similarity, occlusion, and limited

Applications

Enhancing Bayesian Optimization and Active Learning Through Kernel Diversity

arXiv:2608.24721v1 Announce Type: cross Abstract: Hyperparameter selection remains a key challenge in Bayesian optimization (BO) and Bayesian active learning (AL), as model misspecification can lead t

applicationsarxiv-cs-ai

exttt{findr}: Transparent and Fair Credit Risk Decisions through Semi-Structured Regressions

arXiv:2608.24582v1 Announce Type: cross Abstract: Credit risk models increasingly need to combine predictive accuracy with transparent explanations and auditable fairness constraints. Logistic regress

local-aiarxiv-cs-ai

FARCA: Fact-Aligned Reliability-Aware Credit Assignment for Reinforcement Learning with Factual Supervision

arXiv:2608.24350v1 Announce Type: cross Abstract: To reduce the hallucination risk caused by outcome-driven rewards in large language models trained through reinforcement learning with verifiable rewa

local-aiarxiv-cs-ai

From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs

arXiv:2506.13182v3 Announce Type: replace-cross Abstract: [...] Since then, various APR approaches, especially those leveraging the power of large language models (LLMs), have been rapidly developed t

'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection

arXiv:2608.24191v1 Announce Type: cross Abstract: Urdu, the world's tenth most spoken language with 246 million speakers, remains almost entirely absent from mainstream LLM safety evaluation and nine

HMGCLIP: Heterogeneous Multi-Granularity Contrastive Learning for E-commerce Representation Learning

arXiv:2608.24467v1 Announce Type: new Abstract: Although recent Multimodal Large Language Models (MLLMs) have advanced general product understanding, they implicitly encode product information into gl

IDeaL: Data-Free Multi-Teacher Distillation via Improved Dead Leaves

arXiv:2608.24759v1 Announce Type: new Abstract: Multi-teacher distillation has emerged as a way to combine complementary teacher models into a single student model that exhibits the strengths of all i

researcharxiv-cs-cv

Safety

Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents

arXiv:2608.24087v1 Announce Type: cross Abstract: Current LLM agent systems decide delegation before reasoning begins (a router picks a model) or after a response is complete (a verifier scores it and

safetyarxiv-cs-ai

More GPUs or a Smaller Cache? Tensor Parallelism versus KV Compression for Memory-Bound LLM Serving

arXiv:2608.23962v1 Announce Type: new Abstract: When an LLM serving deployment runs out of KVcache room, there are two well-established ways out. Tensor parallelism shards the weights and the KV cache

RAGSentinel: Certifiable Geometric Consensus for Robust Retrieval-Augmented Generation

arXiv:2608.23965v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models by grounding responses in external documents, but it also expose

REFINE: A Multi-Agent LLM Approach for Evidence-Guided Code Refactoring

arXiv:2608.23611v1 Announce Type: cross Abstract: Large Language Models (LLMs) offer new opportunities for automated code refactoring. However, generated changes must reduce targeted quality problems