Search: “research”

SyPS: Measuring Sycophancy Prompt Sensitivity in Large Language Models

arXiv:2608.23837v1 Announce Type: new Abstract: Large language models (LLMs) are known to exhibit social sycophancy, often validating or agreeing with users in socially sensitive contexts. Existing ev

Task-Adaptive Rubrics for GUI Reward Modeling

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DGX agent

arXiv:2608.24174v1 Announce Type: new Abstract: Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajecto

researcharxiv-cs-ai

26 Aug 2026

The Loss Floor of Denoising Score Matching: Fisher Geometry from Schrodinger Bridges

arXiv:2608.23916v1 Announce Type: new Abstract: Denoising score matching trains diffusion models by regressing onto a conditional score, although generation ultimately requires the marginal score. The

The Sharp Tail of Uniform Stability

arXiv:2608.24098v1 Announce Type: new Abstract: Uniform stability controls how much one training example can change the loss at any test point. A new logarithmic-free upper bound shows that a gamma-un

Three-Stream Temporal-Shift Attention Network Based on Self-Knowledge Distillation for Micro-Expression Recognition

arXiv:2406.17538v4 Announce Type: replace Abstract: Micro-expressions are subtle facial movements that occur spontaneously when people try to conceal real emotions. Micro-expression recognition is cru

Tight Majorizations and Convergence Rates of Nuclear Norm Minimization IRLS

arXiv:2608.23765v1 Announce Type: new Abstract: Iteratively reweighted least squares (IRLS) methods constitute a natural approach to nuclear norm minimization, but their convergence rates and the role

Tlow: Flow-based Item Tokenizer for Recommendation

arXiv:2608.24176v1 Announce Type: cross Abstract: Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundame

TLXML: Task-Level Explanation of Meta-Learning via Influence Functions

arXiv:2501.14271v4 Announce Type: replace Abstract: Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially r

Topology enables learning-based hydrodynamic prediction of the global river system

arXiv:2602.22293v2 Announce Type: replace Abstract: Accurate river prediction is essential for water, food and energy security, yet remains challenging across entire river networks. Machine learning h

Towards Reproducibility in Predictive Process Mining: SPICE -- A Deep Learning Library

arXiv:2512.16715v3 Announce Type: replace-cross Abstract: In recent years, Predictive Process Mining (PPM) techniques based on artificial neural networks have evolved as a method for monitoring the fu

Transformer Accelerator (TFA): A Macro-Op INT8 Hardware Chip for Transformer Inference and Machine Translation

arXiv:2608.23582v1 Announce Type: cross Abstract: We present the Transformer Accelerator (TFA), a synthesizable, parameterizable INT8 memory-to-memory engine for transformer inference. One time-multip

Unlocking the power of partnership: How humans and machines can work together to improve face recognition

arXiv:2510.02570v2 Announce Type: replace Abstract: Human review of consequential decisions by face recognition algorithms creates a collaborative human-machine system. We establish the circumstances

Velocity-coupled Representation Refinement for Satellite Orbit Prediction

arXiv:2608.23728v1 Announce Type: new Abstract: Satellite orbit prediction, which aims to forecast future orbital trajectories from historical observations, is important for collision warning and safe

VisCache: Visual KV Cache Pruning for Efficient Vision Large Language Model Inference

arXiv:2608.24063v1 Announce Type: cross Abstract: While Vision Large Language Models (VLLMs) have achieved remarkable success in multimodal reasoning, their long-context inference remains prohibitivel

Vision Language Model Fusion for Explainable Face Recognition

arXiv:2608.24430v1 Announce Type: new Abstract: Responsible deployment of face verification systems requires more than accurate decisions: systems should also provide interpretable and auditable evide

Weakly Supervised Seafloor Segmentation for Seagrass Habitat Mapping in Side-Scan Sonar Imagery

arXiv:2608.24756v1 Announce Type: new Abstract: Seagrass meadows are crucial blue-carbon habitats, and mapping their extent is a prerequisite for coastal management and carbon inventory. Optical satel

What Does Prompt Learning Change? -A Natural-Language Concept Analysis of Vision-Language Models

arXiv:2608.24142v1 Announce Type: new Abstract: Prompt learning adapts vision-language models such as CLIP by optimizing continuous prompt vectors, but the learned prompts are difficult to interpret i

What FID Hides: Detecting, Ranking, and Diagnosing Deviations in Generative Evaluation

arXiv:2608.24881v1 Announce Type: cross Abstract: Generative models are commonly ranked by Frechet Inception Distance (FID) and Kernel Inception Distance (KID), yet FID's first-two-moment summary can

When Do Supervised UQ Ensembles Improve LLM Hallucination Detection? A Robustness Study

arXiv:2608.24492v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) methods are widely used for hallucination detection in large language models (LLMs) in closed-book settings where grou

When Does Self-Supervised Pretraining Help Tabular Models? A Study of Label Scarcity and Missing Data

arXiv:2608.24381v1 Announce Type: new Abstract: Self-supervised learning (SSL) has emerged as a promising approach for tabular data, yet its efficacy under extreme label scarcity and test-time missing

When Less Is More: An Empirical Study of Minimal Responses in Counseling Dialogues and the Behavior of LLMs

arXiv:2608.24080v1 Announce Type: cross Abstract: In psychological counseling, effective support is not always delivered through long, information-rich responses. Minimal responses, such as backchanne

XP-JEPA: Cross-Predictive Physics Grounding for Forecastable Latent Dynamics

arXiv:2608.24044v1 Announce Type: new Abstract: Latent world models plan by predicting how candidate actions transform learned representations. In self-predictive models, however, the encoder and pred

3D Point Cloud from Close-Range Photogrammetry for Defect Characterisation of Rubberised Concrete

arXiv:2608.21468v1 Announce Type: new Abstract: While three-dimensional (3D) point clouds are widely used in civil engineering, mainstream LiDAR systems such as Terrestrial Laser Scanning (TLS) are ph

A Data-Driven Approach to State Construction in Markov Models

arXiv:2608.21480v1 Announce Type: cross Abstract: A Markov chain is a widely used stochastic process modelling random events over time. These models are built on subsets of the entire dataset, referre

A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform

arXiv:1706.02795v1 Announce Type: cross Abstract: Kiva is an online non-profit crowdsouring microfinance platform that raises funds for the poor in the third world. The borrowers on Kiva are small bus

A Human-in-the-Loop Bayesian Optimization Framework for Constraint-Aware Bioprocess Development

arXiv:2606.19230v2 Announce Type: replace Abstract: This work presents an extension to Pareto Front Guided Sampling (PFGS), a Human-in-the-Loop (HitL) Bayesian Optimization (BO) framework in which Gau

A Multi-Domain and Multi-Task Generative Framework with Explicit Task and Domain Conditioning for Cross-Domain Event Extraction

arXiv:2608.23235v1 Announce Type: new Abstract: Event extraction aims to identify event triggers, classify event types, and extract arguments to construct structured event representations. Despite str

A Multidimensional Data-Driven Hybrid Transformer Framework for Non-invasive Continuous Blood Pressure Prediction

arXiv:2608.23276v1 Announce Type: new Abstract: Objective. To develop and evaluate a cuffless continuous blood pressure (BP) estimator using temporal physiological and demographic features. We propose

A New Type of Adversarial Examples

arXiv:2510.19347v2 Announce Type: replace-cross Abstract: Most machine learning models are vulnerable to adversarial examples, which poses security concerns on these models. Adversarial examples are c

A Simulator-Grounded Framework For Constructing Verifiable Muscle-Grounded QA From 3D Tongue Meshes

arXiv:2608.23137v1 Announce Type: new Abstract: Existing articulatory corpora based on real-time MRI and electromagnetic articulography capture tongue shape and motion but do not provide traceable lab

Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search

arXiv:2608.23503v1 Announce Type: new Abstract: Text-based person anomaly search requires distinguishing individuals based on fine-grained, context-dependent behaviors rather than mere appearance. Exi

Activation-Weighted Seeded Residual Coding for Low-Bit LLM Weight Repair

arXiv:2608.23144v1 Announce Type: cross Abstract: Low-bit weight quantization saves storage but leaves errors that degrade language-model quality. We introduce Activation-Weighted Seeded Residual Codi

Adapter-Based Few-Shot Continual Learning for Malicious Packet Recognition

arXiv:2608.23536v1 Announce Type: cross Abstract: The continual evolution of malware variants necessitates detection systems that can adapt to new threats without retraining from scratch. However, con

Adapting Dense Vision-Language Relationships for Multi-label Classification with Partial Label

arXiv:2608.22313v1 Announce Type: new Abstract: Learning multi-label image classification with incomplete annotations is a challenging task that has been widely studied for its superior trade-off betw

Adaptive Test-Time Compute Allocation for Block Diffusion Language Models in Complex Reasoning

arXiv:2602.09555v3 Announce Type: replace Abstract: Recent advances in block diffusion language models have demonstrated competitive performance and strong scalability on reasoning tasks. However, the

AdaR: A Framework for Equipping LLMs with Adaptive Reasoning

arXiv:2510.04617v3 Announce Type: replace Abstract: Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness an

AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies

arXiv:2501.16760v2 Announce Type: replace Abstract: Automated interpretation of seismic images using deep learning methods is challenging because of the limited availability of training data. Few-shot

ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability

arXiv:2608.23297v1 Announce Type: cross Abstract: Data assimilation (DA) is an essential tool for prediction and understanding in the geosciences. DA combines simulation programs representing scientif

ADMIL: Attention-Distilled Multiple Instance Learning for Selective Foundation Model Inference in Pathology

arXiv:2608.22066v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) using pathology foundation model embeddings is effective for slide-level tasks, but exhaustive infe

Advanced LLM-Enhanced Intent-Based 5G Network Management using Dynamic Semantic Routes

arXiv:2608.22644v1 Announce Type: cross Abstract: As the use of Artificial Intelligence (AI) and Large Language Models (LLMs) is becoming common in everyday applications, their ability to interpret na

Adversarial Robustness of Phishing Email Detection: A Comparative Study of TF-IDF + Logistic Regression and Fine-Tuned DistilBERT

arXiv:2607.18429v2 Announce Type: replace-cross Abstract: Phishing emails remain one of the most persistent cybersecurity threats, and machine-learning classifiers are widely used to detect them. Most

AI emotional support is better only when chosen, but shifts preferences even when it is not

arXiv:2608.23196v1 Announce Type: new Abstract: People increasingly face a novel decision when seeking emotional support: human or AI. In existing studies, AI's empathic messages are rated as well as

AI Learning and Conceptual Transfer in the Game of Hidden Rules

arXiv:2608.21372v1 Announce Type: new Abstract: This report summarizes the work conducted on the Game of Hidden Rules (GOHR), focusing on reinforcement learning agents trained to infer hidden rules fr

All four leading LLMs talk more than they listen to personality-verified synthetic help-seekers

arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b

An Interpretable Deep Learning Framework for Material Perception and Classification from Multisensory Tactile Data

arXiv:2608.21894v1 Announce Type: new Abstract: Human tactile perception relies on complex multisensory cues. Yet the relationship between tactile signals and perceptual representations remains poorly

researcharxiv-cs-ro

AquaFlow: A Monocular Gaussian Splatting SLAM for Underwater Streaming Reconstruction

arXiv:2608.22906v1 Announce Type: new Abstract: Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality

ARCHER: Amortized cross-specimen pose estimation for cryo-electron microscopy

arXiv:2608.22029v1 Announce Type: new Abstract: Single-particle cryo-electron microscopy (cryo-EM) pose estimation is traditionally solved anew for each dataset, where iterative refinement is done fro

As-Rigid-As-Possible Regularization for Implicit Surfaces

arXiv:2608.15933v1 Announce Type: cross Abstract: Implicit surface representations have regained popularity because of their use in machine learning. A common component in optimization is regularizati