Search: “evaluation”

3DGAA: Realistic and Robust 3D Gaussian-based Adversarial Attack for Autonomous Driving

arXiv:2507.09993v4 Announce Type: replace Abstract: Camera-based perception in connected and autonomous vehicles remains exposed to physical adversarial attacks. Prior attacks often either optimize im

safetyarxiv-cs-cv

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AdaVDR: Adaptive Tool Use and Reflection for Video Deep Research

DGX agent

arXiv:2608.25559v1 Announce Type: new Abstract: Video deep research answers complex questions by jointly understanding video content and retrieving external knowledge from the open Web. However, diver

model-releasesarxiv-cs-cv

27 Aug 2026

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

AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models

arXiv:2510.15987v3 Announce Type: replace Abstract: How do inference time and latent computations enable large language models (LLMs) to solve multi-step reasoning problems? We introduce AlgoTrace, a

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

Beam Search, Self-Consistency, and the Limits of Inference-Time Scaling for Grammar-Constrained Text-to-SQL in Small Language Models

arXiv:2608.25761v1 Announce Type: new Abstract: One common trade-off in the use of large language models involves reducing the size of the model while increasing the amount of computation at inference

CoRE: Weakly Supervised Coarse-to-Fine Risk Evidence Learning in Driving Videos

model-releasesarxiv-cs-cv

arXiv:2608.25344v1 Announce Type: new Abstract: Perceived risk in driving evolves over time and may be supported by specific scene entities, yet supervision is typically limited to coarse video-level

Cross-Dataset Stability of Expert-Informed Skill Prompting and Fine-Tuning for Chinese Metaphor Identification

arXiv:2608.25579v1 Announce Type: new Abstract: Metaphor-identification performance can change markedly across datasets that differ in text distribution and annotation policy. We examine whether a fix

Detection != Reliable Control: Decodable Empathy Directions Yield at Most Partial Shifts in Automated Empathy Scores

arXiv:2608.24901v1 Announce Type: new Abstract: A decodable 'empathy' direction is routinely read as a causal lever, conflating decodability, automated-metric control, and human-perceived change. We t

Does Fine-Tuning Undo Activation Steering? Behavioural Recovery Without Weight-Edit Reversal

arXiv:2608.24988v1 Announce Type: new Abstract: Activation steering can be embedded directly into a language model's weights, shaping behaviour without inference-time intervention and offering a way t

EgoArgus: Benchmarking VLMs as Situational Assistants for Modality-Grounded User Supports

arXiv:2608.25561v1 Announce Type: new Abstract: VLMs are increasingly positioned as daily assistants that perceive first-person environments, follow user dialogue, and decide how to help. Existing ego

Emergent Abilities in Large Language Models: A Survey

arXiv:2503.05788v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are leading a new technological revolution as one of the most promising research streams toward artificial genera

Evidence-Grounded Mapping of Multimodal Human Sensing Psychological Transdiagnostic Dimensions

arXiv:2608.24903v1 Announce Type: cross Abstract: Mobile and wearable sensing enables longitudinal observation of behavior, yet translating these signals into meaningful mental health constructs remai

Fine-Tuning Whisper for Automatic Speech Recognition in Baniwa: A Preliminary Study

arXiv:2608.26060v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technologies have achieved remarkable performance in recent years through the use of large multilingual foundation mo

Applications

FlashNormal: Detailed Surface Normal Estimation from Flash and No-Flash Images

arXiv:2608.25360v1 Announce Type: new Abstract: High-quality surface normal estimation is preferred for detailed surface shape recovery and image editing. Existing single image-based methods, though b

applicationsarxiv-cs-cv

FlowMoDL: Model-Based Deep Learning with Conjugate-Gradient Data Consistency for Highly Accelerated 4D Flow MRI Reconstruction

arXiv:2608.25828v1 Announce Type: new Abstract: We present FlowMoDL, an unrolled neural network for highly accelerated 4D flow MRI reconstruction that directly optimizes for both anatomical magnitude

researcharxiv-cs-cv

Fusing Perceptual Vision Experts with Multimodal Large Language Models for Explainable Plant Disease Diagnosis: From Benchmark Imagery to Real-World Robotic Field Validation

model-releasesarxiv-cs-cv

arXiv:2608.24934v1 Announce Type: new Abstract: Accurate field plant disease diagnosis requires reliable fusion of uncertain and conflicting perceptual evidence. We present the Hybrid Hierarchical Mul

Gaussian Splatting Underwater: A Controlled Cross-Regime Study

model-releasesarxiv-cs-cv

arXiv:2608.25483v1 Announce Type: new Abstract: The underwater environment is challenging for 3D reconstruction, because particles suspended in the water scatter and diffuse light, turbidity varies, a

Generative Modeling: A Review

arXiv:2501.05458v3 Announce Type: replace-cross Abstract: We organize the generative-modeling literature around three classes of generators, corresponding to three distinct inferential tasks: estimati

Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality

arXiv:2608.25807v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) replace fixed activations in deep architectures with learnable univariate edge functions, making the choice of edge pa

GRIP: Granular Reward-Guided Parameter Interpolation for Efficient Reasoning

arXiv:2608.25583v1 Announce Type: new Abstract: Reasoning-oriented large language models often achieve strong problem-solving performance by generating long chains of thought, but this behavior substa

Hyperbolic Latent Geometry for Tree-Structured Prototype Networks: A Local-vs-Global Trade-off

arXiv:2608.25199v1 Announce Type: new Abstract: We study a tree-structured regularizer over class-prototype layouts in a hierarchical-classification model and ask whether the choice of latent manifold

researcharxiv-cs-lg

Applications

Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models

arXiv:2601.03542v2 Announce Type: replace Abstract: Large language models (LLMs) perform well on multi-hop reasoning, yet how they internally compose multiple facts remains unclear. Recent work propos

applicationsarxiv-cs-cl

Less Contouring, More Accuracy: Lesion-Guided ROI Deep Learning for Ovarian Ultrasound Classification

arXiv:2608.25965v1 Announce Type: new Abstract: Ovarian lesion classification using transvaginal ultrasound remains challenging due to overlapping imaging characteristics and the dependence on expert

researcharxiv-cs-cv

Loss Landscape Geometry of Partial Differential Equation Emulators: Or, Symmetry Learning via Gradient Alignment

arXiv:2601.20172v2 Announce Type: replace Abstract: We study how neural emulators of partial differential equation solution operators internalize physical symmetries by introducing an influence-based

MetaSieve: Faster Relational Deep Learning through SQL-Based Metapath Selection

arXiv:2608.25903v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) is an effective approach to machine learning over multi-table relational databases. In RDL, a database is modeled as a

Neural-Bayesian Structure Learning for Discrete Choice Modeling

arXiv:2608.25258v1 Announce Type: new Abstract: Conventional discrete choice and machine learning models are estimated primarily from observational data and typically treat explanatory covariates as p

safetyarxiv-cs-lg

Local Ai

OpenCVL: An Open, Diverse, and Large-Scale Dataset for Fine-Grained Cross-View Localization

arXiv:2608.25274v1 Announce Type: new Abstract: Fine-grained Cross-View Localization (CVL) estimates the precise position and orientation of a ground-level image by aligning it with geo-referenced aer

local-aiarxiv-cs-cv

OpenSanctions Pairs: Large-Scale Entity Matching with LLMs

arXiv:2603.11051v2 Announce Type: replace-cross Abstract: We release OpenSanctions Pairs, the first large-scale public benchmark for entity matching on sanctions and OSINT data. The dataset includes 7

OpenVeinNet: Robust Open-Set Finger Vein Verification with Dynamic Snake Convolution and Graph Learning

arXiv:2608.25515v1 Announce Type: new Abstract: Finger vein verification is a promising biometric modality for secure authentication because vascular patterns are internal, difficult to observe extern

researcharxiv-cs-cv

Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models

arXiv:2608.25662v1 Announce Type: new Abstract: In 2026, we held the fourth iteration of the SHROOM Shared Task series: SHROOM-Visions (extbf{S}hared-task on extbf{H}allucinations and extbf{R}elated e

PA-CoT: Profile-Adaptive Chain-of-Thought for Personalized Nutritional Consulting

arXiv:2608.24907v1 Announce Type: cross Abstract: In health and nutrition consulting, widely used prompting methods pass the user profile as an unstructured block without a dedicated analysis step, le

Prefix-Denoising Consistency: Test-Time Verification for Diffusion Language Models

arXiv:2608.25311v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) have recently become increasingly competitive with autoregressive (AR) models, and even outperform them on certain task

PRISM: Projection-Integrated Sampling-Based MPC with Bayesian Cost Tuning for Bimanual Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.25666v1 Announce Type: new Abstract: Bimanual manipulation in cluttered, contact-rich environments remains challenging because it requires coordinated motion generation, interaction-aware p

Provable Privacy Attacks on Trained Shallow Neural Networks

arXiv:2410.07632v3 Announce Type: replace Abstract: We study what provable privacy attacks can be shown for trained 2-layer ReLU neural networks, focusing on two types of attacks: membership inference

safetyarxiv-cs-lg

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

Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion

arXiv:2509.21054v2 Announce Type: replace-cross Abstract: Understanding persuasion is critical for the safety and reliability of multi-agent systems built on large language models (LLMs). This paper s

Same-Player Verification for Account Consistency in Counter-Strike 2

arXiv:2608.24893v1 Announce Type: cross Abstract: In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavi

researcharxiv-cs-lg

SAMpLE: A SystemC-AMS Machine LEarning-based Framework for Virtual Prototyping

arXiv:2608.25910v1 Announce Type: new Abstract: Machine Learning (ML) is increasingly used in virtual prototypes of embedded systems to model behaviors that are difficult to capture analytically. Howe

Hardware

Scalable Multi-GPU Simulation of 3D Multicellular Growth with RNN-Based Workload Balancing

arXiv:2608.25890v1 Announce Type: cross Abstract: Detailed multicellular growth simulations based on subcellular element models (SEMs) can capture complex tissue development, but their element-level i

hardwarearxiv-cs-lg

Semantic Variability of Replies Across LLMs: Implications for Designing Conversation-Based Assessment

arXiv:2608.24920v1 Announce Type: new Abstract: This study examines whether LLM-generated replies remain semantically consistent when the underlying LLM changes. Using messages from real collaborative

SNAP-KG: Streaming Node Assignment via Projection for Knowledge Graph Entity Integration

arXiv:2608.25149v1 Announce Type: new Abstract: Knowledge graph (KG) construction pipelines must continuously integrate newly arriving entities into a growing graph. Unlike inserting triples between e

The Imperfective Paradox Is Not Necessarily in Large Language Models: A Benchmark Failure Before a Model Failure

arXiv:2608.25005v1 Announce Type: new Abstract: The imperfective paradox provides a useful test of compositional semantic analysis. Recent work constructs an NLI benchmark and reports that models freq

Training Alignment Auditors via Reinforcement Learning

arXiv:2608.25460v1 Announce Type: cross Abstract: Alignment auditing of frontier models increasingly relies on LLM auditors to surface undesirable behaviors at scale, but current automated auditors ca

safetyarxiv-cs-lg

Unsupervised Post-Training of Foundation Models: A Survey

arXiv:2608.24982v1 Announce Type: new Abstract: Foundation-model post-training usually relies on human labels, preference data, stronger teachers, or executable verifiers. We study Unsupervised Post-T

When Does Context Routing Help? A Systematic Study of Multi-Modal Fusion in Time Series Forecasting

arXiv:2608.25128v1 Announce Type: new Abstract: Multi-modal time series forecasting methods integrate auxiliary context into temporal predictions through increasingly sophisticated fusion mechanisms.

When Personality Meets Quantization: A Layer-wise MBTI Analysis of Quantized LLMs

arXiv:2608.25977v1 Announce Type: new Abstract: Personality is increasingly important in large language models (LLMs), as it shapes users' trust, engagement, and emotional experiences. While the Myers

A Dual-Dimensional LLM Framework for Automated Item Incidental Content Similarity Analysis in Large-Scale Assessments