Search: “models”

Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning

arXiv:2608.27715v1 Announce Type: new Abstract: Federated learning systems are increasingly deployed to facilitate collaborative model training across a heterogeneous client population. Existing pract

local-aiarxiv-cs-lg

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Model Releases

CoCoBench: A Cooperative Coordination Benchmark for Embodied Multi-Agent Task Planning

DGX agent

arXiv:2608.28266v1 Announce Type: new Abstract: Agent systems powered by multimodal large language models (MLLMs) have advanced rapidly in recent years, yet existing embodied-agent benchmarks still la

model-releasesarxiv-cs-ro

31 Aug 2026

Cyc3D: Evaluating Cyclic Structural Stability and Asset Usability in Image-to-3D Generation

arXiv:2608.28080v1 Announce Type: new Abstract: Image-conditioned 3D generation has advanced rapidly, yet existing evaluation protocols largely judge rendered-view plausibility and semantic alignment,

Applications

Destroy Me: Automatic Artifact Generation for Histopathology Images

arXiv:2608.27516v1 Announce Type: cross Abstract: Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor

applicationsarxiv-cs-cv

GRACE:Gradient-guided Coreset Selection for LLM Unlearning

arXiv:2608.28361v1 Announce Type: cross Abstract: Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests m

researcharxiv-cs-lg

Learning to Difference: Adaptive Reversible Differencing (AdaRDiff) for Time Series Forecasting

arXiv:2608.28134v1 Announce Type: new Abstract: Reliable long-horizon time series forecasting is an important yet difficult problem. Trends and seasonality introduce complex temporal structure that ch

Locate Anything in Videos: Rethinking Efficient Generative Spatio-Temporal Video Grounding

arXiv:2608.28192v1 Announce Type: new Abstract: Spatio-temporal video grounding (STVG) requires models to identify when a referred event occurs and localize the target entity throughout that interval.

local-aiarxiv-cs-cv

OmniFusion: Simultaneous Multilingual Multimodal Translations via Modular Fusion

arXiv:2512.00234v3 Announce Type: replace Abstract: There has been significant progress in open-source text-only translation large language models (LLMs) with better language coverage and quality. How

researcharxiv-cs-cl

PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems

arXiv:2608.28378v1 Announce Type: new Abstract: Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally comp

RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing

arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,

local-aiarxiv-cs-lg

Sliding-window beats linear attention

arXiv:2608.28444v1 Announce Type: new Abstract: Due to the nature of quadratic attention, Large Language Models (LLMs) consume a lot of memory and energy. Every new token costs more than the previous

researcharxiv-cs-cl

When Robots Mishear Us: Mapping the Safety Risks of Voice-Controlled Embodied AI

arXiv:2608.28518v1 Announce Type: cross Abstract: We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that

safetyarxiv-cs-cl

Active Curriculum Refinement for Reinforcement Learning

arXiv:2608.26469v1 Announce Type: new Abstract: In many reinforcement learning (RL) domains, environments are connected by prerequisite relations, such as difficulty-increasing edits or parameter incr

AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air

arXiv:2507.11515v2 Announce Type: replace-cross Abstract: Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computationa

safetyarxiv-cs-ai

Benchmarking_Fast_Domain_Adaptation_for_Unsupervised_Speech_Units

arXiv:2608.26992v1 Announce Type: new Abstract: Representation learning has attracted great atten- tion and managed to reach good performances as a pretraining method for downstream tasks or as a firs

Cascaded Batch Prompting

arXiv:2608.27038v1 Announce Type: new Abstract: Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredicta

researcharxiv-cs-cl

FaithSieve: Fine-Grained Evaluation of Math Proofs with Faithful Formal Evidence

arXiv:2608.26310v1 Announce Type: new Abstract: Large language models can now generate complex, multi-step mathematical proofs, but reliably determining their correctness and localizing early logical

Importance Scoring of Transformer Attention Heads in Learning Tabular Data

arXiv:2608.27241v1 Announce Type: new Abstract: Computationally demanding and opaque deep learning models can be better understood and optimized by analyzing how they transform data. While deep transf

researcharxiv-cs-lg

Learning the ARTS of Search for Automated Discovery

arXiv:2606.21891v2 Announce Type: replace Abstract: Scientific discovery can be formulated as an iterative search process over the space of hypotheses and experiments. Contemporary methods navigate th

Learning Woody Clearing With Loss Alignment for Zero-Shot Regrowth and Woody Segmentation

arXiv:2608.26489v1 Announce Type: new Abstract: Detecting woody clearing is vital for managing biodiversity. Deep learning models can detect change in woody vegetation from bitemporal remote sensing i

safetyarxiv-cs-cv

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

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

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

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

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

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

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