Search: “evaluation”

arXiv:2605.19101v1 Announce Type: cross Abstract: Training general-purpose Audio Large Language Models (ALLMs) across diverse datasets is essential for holistic audio understanding, yet it faces signi

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Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling

DGX agent

arXiv:2511.11688v3 Announce Type: replace-cross Abstract: Diffusion probabilistic models have set a new standard for generative fidelity but are hindered by a slow iterative sampling process. A powerf

local-aiarxiv-cs-cv

20 May 2026

How Faithful Is Trajectory-Based Data Attribution? Error Sources, Remedies, and Practical Guidelines

arXiv:2605.18814v1 Announce Type: new Abstract: Trajectory-based data attribution methods estimate the influence of training samples on model predictions by unrolling the training trajectory. They are

How Far Are We From True Auto-Research?

arXiv:2605.19156v1 Announce Type: new Abstract: Recent auto-research systems can produce complete papers, but feasibility is not the same as quality, and the field still lacks a systematic study of ho

Hybrid Training for Vision-Language-Action Models

arXiv:2510.00600v2 Announce Type: replace-cross Abstract: Using Large Language Models to produce intermediate thoughts, a.k.a. Chain-of-thought (CoT), before providing an answer has been a successful

agentsarxiv-cs-ai

HypergraphFormer: Learning Hypergraphs from LLMs for Editable Floor Plan Generation

arXiv:2605.18932v1 Announce Type: cross Abstract: In this work, we propose HypergraphFormer, a novel and efficient approach to floor plan generation based on learning hypergraph representations with a

Local Ai

iDiff: Interpretable Difference-aware Framework for Pairwise Image Quality Assessment

arXiv:2605.19522v1 Announce Type: new Abstract: Pairwise image quality assessment (IQA) in professional photography requires a model not only to identify the preferred image between two candidates, bu

local-aiarxiv-cs-cv

Improved visual-information-driven model for crowd simulation and its modular application

arXiv:2504.03758v4 Announce Type: replace-cross Abstract: Crowd movement simulation is crucial for pedestrian safety management and facility design. Data-driven models offer the potential to improve r

safetyarxiv-cs-cv

Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization

arXiv:2605.18772v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factual accuracy of large language model (LLM) outputs by grounding generation in external knowledge

agentsarxiv-cs-ai

Tutorials

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

tutorialsarxiv-cs-cv

Inference-Time Scaling in Diffusion Models through Iterative Partial Refinement

arXiv:2605.19317v1 Announce Type: cross Abstract: Inference-time scaling has emerged as a major approach for improving reasoning capabilities, and has been increasingly applied to diffusion models. Ho

Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies

arXiv:2605.19644v1 Announce Type: cross Abstract: Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and

applicationsarxiv-cs-lg

Introducing Agent Executor, Google’s distributed Agent Runtime

model-releasesgoogle-cloud-ai

As models and harnesses improve, agents are taking on increasingly complex tasks that can run for hours or even days. But as we push agents to do more, this has surfaced a new operational problem: lon

Jailbreaking on Text-to-Video Models via Scene Splitting Strategy

arXiv:2509.22292v2 Announce Type: replace-cross Abstract: Along with the rapid advancement of numerous Text-to-Video (T2V) models, growing concerns have emerged regarding their safety risks. While rec

safetyarxiv-cs-ai

Justifying bio-inspired robotics research: A taxonomy of strategies

arXiv:2605.19840v1 Announce Type: new Abstract: For most of human history, we have not thought systematically about how and why we incorporate aspects of the natural world into our designs. The lack o

researcharxiv-cs-ro

KVBuffer: IO-aware Serving for Linear Attention

arXiv:2605.19049v1 Announce Type: cross Abstract: Linear attention has recently gained significant attention for long-context inference due to its constant decoding cost with respect to context length

Landslide Detection and Mapping Using Deep Learning Across Multi-Source Satellite Data and Geographic Regions

arXiv:2507.01123v2 Announce Type: replace Abstract: Landslides pose severe threats to infrastructure, economies, and human lives, necessitating accurate detection and predictive mapping across diverse

researcharxiv-cs-cv

Tutorials

Latent Laplace Diffusion for Irregular Multivariate Time Series

arXiv:2605.19805v1 Announce Type: cross Abstract: Irregular multivariate time series impose a trade-off for long-horizon forecasting: discrete methods can distort temporal structure via re-gridding, w

tutorialsarxiv-cs-ai

Learn-by-Wire Training Control Governance: Bounded Autonomous Training Under Stress for Stability and Efficiency

arXiv:2605.19008v1 Announce Type: new Abstract: Modern language-model training is increasingly exposed to instability, degraded runs, and wasted compute, especially under aggressive learning-rate, sca

Learn2Decompose: Learning Problem Decomposition for Efficient Sequential Multi-object Manipulation Planning

arXiv:2408.06843v5 Announce Type: replace Abstract: We present an efficient task and motion replanning approach for sequential multi-object manipulation in dynamic environments. Conventional Task And

applicationsarxiv-cs-ro

Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions

arXiv:2605.19562v1 Announce Type: cross Abstract: This paper presents a learning-augmented trajectory planning framework for cooperative unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV)

Learning Efficient Guardrails for Compliance

arXiv:2510.03485v2 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed for long-horizon tasks, yet their ability to adhere to real-world policies remains critically undere

Learning ORDER-Aware Multimodal Representations for Composite Materials Design

arXiv:2602.02513v2 Announce Type: replace Abstract: Artificial intelligence has shown remarkable success in materials discovery and property prediction, particularly for crystalline and polymer system

safetyarxiv-cs-lg

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

arXiv:2602.04998v2 Announce Type: replace-cross Abstract: Low-Rank Adaptation (LoRA) is the prevailing approach for efficient large language model (LLM) fine-tuning. Building on this paradigm, recent

Less Back-and-Forth: A Comparative Study of Structured Prompting

arXiv:2605.20149v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used for open-ended tasks, but underspecified prompts can lead to low-quality answers and additional interacti

Library Drift: Diagnosing and Fixing a Silent Failure Mode in Self-Evolving LLM Skill Libraries

arXiv:2605.19576v1 Announce Type: new Abstract: Self-evolving skill libraries face a silent failure mode we term library drift: unbounded skill accumulation without outcome-driven lifecycle management

agentsarxiv-cs-ai

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries

model-releasesarxiv-cs-cl

arXiv:2509.22202v3 Announce Type: replace-cross Abstract: Large language models (LLMs) now play a central role in code generation, yet they continue to hallucinate, frequently inventing non-existent l

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators

arXiv:2605.19060v1 Announce Type: cross Abstract: High-resolution 3D medical image generation remains challenging because fully volumetric models are computationally expensive, while efficient 2D slic

Lightweight and Fast Backdoor Model Detection

arXiv:2605.18907v1 Announce Type: cross Abstract: Deep neural networks (DNN), despite their remarkable performance, are highly vulnerable to backdoor attacks. Existing defenses mainly rely on activati

LMM-Track4D: Eliciting 4D Dynamic Reasoning in LMMs via Trajectory-Grounded Dialogue

model-releasesarxiv-cs-cv

arXiv:2605.19390v1 Announce Type: new Abstract: Recent large multimodal models (LMMs) have become increasingly capable on image and video understanding, yet still struggle to sustain 4D continuous spa

Long-term Power Grid Planning via Answer Set Programming

arXiv:2605.20172v1 Announce Type: cross Abstract: The Power grid is a critical infrastructure underpinning all aspects of modern society and its services. Maintaining its effectiveness requires contin

applicationsarxiv-cs-ai

Lynx: Enabling Efficient MoE Inference through Dynamic Batch-Aware Expert Selection

arXiv:2411.08982v3 Announce Type: replace Abstract: Selective parameter activation provided by Mixture-of-Expert (MoE) models have made them a popular choice in modern foundational models. However, Mo

M3DocDep: Multi-modal, Multi-page, Multi-document Dependency Chunking with Large Vision-Language Models

arXiv:2605.18774v1 Announce Type: cross Abstract: In long, multi-page industrial documents, retrieval-augmented generation (RAG) depends heavily on whether chunk boundaries follow the document's true

Mask-to-Correct^+: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction

arXiv:2605.18776v1 Announce Type: cross Abstract: The rapid spread of misinformation on social media highlights the need for robust, automated fact correction frameworks. However, existing works rely

MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution

arXiv:2512.05958v2 Announce Type: replace-cross Abstract: Generative search engines based on large language models (LLMs) are replacing traditional search, fundamentally changing how information provi

MCNav: Memory-Aware Dynamic Cognitive Map for Zero-shot Goal-oriented Navigation

arXiv:2605.19594v1 Announce Type: new Abstract: Navigating to instance-level targets in complex environments is a challenging problem. Many existing zero-shot methods achieve strong performance by mod

researcharxiv-cs-ro

MedFM-Robust: Benchmarking Robustness of Medical Foundation Models

model-releasesarxiv-cs-cv

arXiv:2605.19027v1 Announce Type: new Abstract: Medical foundation models (MedFMs) have emerged as transformative tools in healthcare, demonstrating capabilities across diverse clinical applications.

MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent

arXiv:2605.19194v1 Announce Type: new Abstract: The Mixture-of-Agents (MoA) framework has shown promise in improving large language model (LLM) performance by aggregating outputs from multiple agents.

agentsarxiv-cs-cl

Motion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations

arXiv:2412.13111v2 Announce Type: replace Abstract: Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods of

researcharxiv-cs-cv

MTraining: Distributed Dynamic Sparse Attention for Efficient Ultra-Long Context Training

model-releasesarxiv-cs-cl

arXiv:2510.18830v2 Announce Type: replace Abstract: The adoption of long context windows has become a standard feature in Large Language Models (LLMs), as extended contexts significantly enhance their

Multi-axis Analysis of Image Manipulation Localization

model-releasesarxiv-cs-cv

arXiv:2605.20174v1 Announce Type: new Abstract: Advanced image editing software enables easy creation of highly convincing image manipulations, which has been made even more accessible in recent years

Multi-Session Ground Texture SLAM in Low-Dynamic Environments

arXiv:2605.19701v1 Announce Type: new Abstract: The simultaneous localization and mapping community has introduced a growing number of systems adapted for multi-session operations where the operationa

safetyarxiv-cs-ro

Multimodal system for skin cancer detection

arXiv:2601.14822v2 Announce Type: replace-cross Abstract: Melanoma detection is vital for early diagnosis and effective treatment. While deep learning models on dermoscopic images have shown promise,

applicationsarxiv-cs-ai

Not All Tokens Are Worth Caching: Learning Semantic-Aware Eviction for LLM Prefix Caches

arXiv:2605.18825v1 Announce Type: new Abstract: Prefix caching is a key optimization in Large Language Model (LLM) serving, reusing attention Key-Value (KV) states across requests with shared prompt p

Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR

arXiv:2605.20164v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has made post-training highly effective when correctness can be checked automatically. However, many impo

safetyarxiv-cs-ai

Local Ai

OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences

arXiv:2605.18930v1 Announce Type: cross Abstract: Memory-augmented large language model (LLM) agents use iterative reflection and self-evolution to solve complex tasks, but these mechanisms introduce

local-aiarxiv-cs-ai

Local Ai

On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosis

arXiv:2605.19201v1 Announce Type: cross Abstract: Deep learning models detect pneumonia from chest X-rays with high accuracy, but the performance declines under domain shifts caused by differences in

local-aiarxiv-cs-ai

Open-Set Domain Adaptation Under Background Distribution Shift: Challenges and A Provably Efficient Solution

arXiv:2512.01152v4 Announce Type: replace-cross Abstract: As we deploy machine learning systems in the real world, a core challenge is to maintain a model that is performant even as the data shifts. S

applicationsarxiv-cs-ai