research

Xetrieval: Mechanistically Explaining Dense Retrieval

arXiv:2605.29507v1 Announce Type: new Abstract: Explaining why dense retrievers assign high relevance scores remains challenging because retrieval decisions are made through opaque high-dimensional em

29 May 2026

.@ylecun’s definition of what is a world model.

Yann LeCun, a pioneering AI researcher, provides his definition of what constitutes a world model in this X post. A world model is an AI system's internal representation of how the physical world work

researchyann-lecun--x

29 May 2026

A Conflict-Aware Penalty and Statistical Loss Framework for Balancing Modalities and Enhancing Stability in Multimodal Sentiment Analysis

arXiv:2605.28575v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) fuses text, acoustic, and visual streams to infer sentiment. Because pre-trained text encoders are far more expressi

A Digital Twin Framework for Virtual Visuo-Haptic Teleoperation of Complex-Shaped Optical Microrobots

arXiv:2605.28448v1 Announce Type: new Abstract: Optical tweezers (OT) provide piconewton-scale manipulation for delicate biomedical tasks, where visuo-haptic feedback can improve operator awareness by

researcharxiv-cs-ro

A Fixed-Budget, Cluster-Aware Standard for LLM-as-a-Judge Evaluation: A Multi-Hop RAG Stress Test

arXiv:2605.27789v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems are often compared by asking a large language model (LLM) judge which answer is better. For multi-hop RAG,

A Methodology to Assess Power Modeling in Energy-Aware Federated Learning on Heterogeneous Mobile Devices

arXiv:2605.27601v1 Announce Type: cross Abstract: Estimating CPU power on heterogeneous ARM-based commodity devices is challenging due to limited access to CPU's voltage domains. As a result, state-of

A Multiscale Kinetic Framework for Image Segmentation: From Particle Systems to Continuum Models

arXiv:2605.28619v1 Announce Type: new Abstract: In this work, we present a multiscale kinetic framework for consensus-based image segmentation. By interpreting an image as a system of interacting part

A New Era of Innovation: Google Research at I/O 2026

Google Research at I/O 2026 showcased new Gemini AI models including Gemini Omni, which can create content from any input starting with video, and Gemini 3.5 Flash, combining frontier intelligence wit

researchgoogle-research

A new semantically annotated corpus with syntactic-semantic and cross-lingual senses

arXiv:2605.28494v1 Announce Type: new Abstract: We describe a new sense-tagged corpus for word sense disambiguation. The corpus is constituted of instances of 20 French polysemous verbs. Each verb ins

A novel ordinal multi-view aggregation scheme for oak defoliation

arXiv:2605.28151v1 Announce Type: new Abstract: Forest decline driven by climate and biotic stressors threatens ecosystem functioning, making accurate monitoring of tree health essential. In this work

A Patient-Specific Pulmonary Arterial Tree Digital Twin to Extract Pulmonary Embolism Biomarkers

arXiv:2605.28217v1 Announce Type: new Abstract: Pulmonary embolism, the obstruction of a pulmonary artery by a blood clot, is one of the leading causes of acute cardiovascular syndrome. In clinical pr

A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning

arXiv:2605.27884v1 Announce Type: new Abstract: City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction re

A Surveillance Evasion Game with Continuous Sensor Redeployment via Bilevel Optimization

arXiv:2605.27917v1 Announce Type: new Abstract: Uncrewed Aerial Systems (UASs) have become a growing threat to the security of critical infrastructure, exploiting spatiotemporal gaps in sensor perimet

researcharxiv-cs-ro

A Survey on Event-based Optical Marker Systems

arXiv:2504.20736v2 Announce Type: replace-cross Abstract: The advent of event-based cameras, with their low latency, high dynamic range, and reduced power consumption, marked a turning point in machin

A Systematic Evaluation of Retrieval-Augmented Generation and Language Models for Space Operations

arXiv:2605.27444v1 Announce Type: cross Abstract: The rapid expansion of space activities has led to an unprecedented accumulation of technical documentation, operational guidelines, and scientific li

A tree interpretation of arc standard dependency derivation

arXiv:2603.27459v2 Announce Type: replace Abstract: Arc-standard derivations over projective dependency trees can be interpreted as the incremental construction of lexicalized ordered trees with conti

ABot-OCR Technical Report

arXiv:2605.27978v1 Announce Type: new Abstract: We introduce ABot-OCR, an end-to-end vision-language model that transcribes a page image directly into clean Markdown in a single forward pass. By doing

Accelerating Diffusion Sampling via Exploiting Local Transition Coherence

arXiv:2503.09675v3 Announce Type: replace Abstract: Text-based diffusion models have made significant breakthroughs in generating high-quality images and videos from textual descriptions. However, the

Accelerating Natural Gradient Descent for PINNs with Randomized Numerical Linear Algebra

arXiv:2505.11638v4 Announce Type: replace-cross Abstract: Natural Gradient Descent (NGD) has emerged as a promising optimization algorithm for training neural network-based solvers for partial differe

Accelerating Reinforcement Learning Training Using Simulation Surrogate Models

arXiv:2605.27556v1 Announce Type: cross Abstract: High-fidelity simulation models are widely used to analyze complex stochastic systems, but their high computational cost motivates the development of

AdaMerge: Salience-Aware Adaptive Token Merging for Training-Free Acceleration of Vision Transformers

arXiv:2605.27465v1 Announce Type: cross Abstract: The quadratic cost of self-attention in Vision Transformers (ViTs) constitutes a fundamental bottleneck for practical deployment, motivating a vibrant

Adapting, Fast and Slow: On Few-Shot Transportability of Compositions

arXiv:2512.22777v2 Announce Type: replace-cross Abstract: Generalization across domains requires stable structure that links the source and target distributions. Building on causal transportability th

Adaptive Coarse-to-Fine Subgoal Refinement for Long-Horizon Offline Goal-Conditioned Reinforcement Learning

arXiv:2605.28127v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) is challenging in long-horizon tasks, where distant state--goal pairs provide weak supervision an

Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction

arXiv:2605.28397v1 Announce Type: new Abstract: Predicting conversion from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is critical for early intervention. Current deep learning paradig

Adjusted Shuffling SARAH: Advancing Complexity Analysis via Dynamic Gradient Weighting

arXiv:2506.12444v2 Announce Type: replace-cross Abstract: In this paper, we propose Adjusted Shuffling SARAH, a novel algorithm that integrates shuffling strategies into the recursive SARAH framework

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients

arXiv:2605.27412v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have emerged with promising energy-efficient property, yet a substantial performance gap persists compared to Artificia

Alterbute: Editing Intrinsic Attributes of Objects in Images

arXiv:2601.10714v2 Announce Type: replace Abstract: We introduce Alterbute, a diffusion-based method for editing an object's intrinsic attributes in an image. We allow changing color, texture, materia

An analytic theory of convolutional neural network inverse problems solvers

arXiv:2601.10334v2 Announce Type: replace Abstract: Supervised convolutional neural networks (CNNs) are widely used to solve imaging inverse problems, achieving state-of-the-art performance in numerou

An Empirical Audit of k-NAF Budget Accounting for Anchored Decoding

arXiv:2605.28001v1 Announce Type: new Abstract: We empirically audit the k-NAF budget-accounting mechanism in Anchored Decoding using (i) a fixed, class-stratified workload (approximately 8,500 random

An Empirical Study on Variance-based MC Dropout Uncertainty-Error Correlation in 2D Brain Tumor Segmentation

arXiv:2510.15541v2 Announce Type: replace-cross Abstract: Accurate brain tumor segmentation from MRI is vital for diagnosis and treatment planning. Although Monte Carlo (MC) Dropout is widely used to

Anomaly as Non-Conformity via Training-Free Graph Laplacian Energy Minimization

arXiv:2605.28428v1 Announce Type: cross Abstract: Detecting subtle visual anomalies in images remains challenging, particularly when only normal samples are available a priori. Such unsupervised anoma

Applications of temporal graph learning for predicting the dynamics of biological systems

arXiv:2605.28659v1 Announce Type: new Abstract: Biological foundation models have shown strong performance in single-cell representation learning by applying transformer architectures directly to gene

Are We Truly Innovating? A Qualitative and Quantitative Study of Originality in AI Research Papers

arXiv:2602.06054v3 Announce Type: replace Abstract: Assessing originality in AI research is arguably the most consequential yet least reliable step in peer review. Reviewer judgments of originality re

Asking Is Not Enough: Protocol Sensitivity in LLM Confidence Calibration

arXiv:2605.27752v1 Announce Type: new Abstract: LLM confidence calibration is often evaluated by comparing two signals: token-probability scores and verbalized confidence. These signals are sometimes

Atomic Skills are the Prerequisite: When Reinforcement Learning Synthesizes Compositional Reasoning, and When It Only Amplifies

arXiv:2512.01970v3 Announce Type: replace Abstract: Does Reinforcement Learning (RL) merely amplify existing skills, or synthesize novel skills? We investigate this question through the lens of Comple

Attention Projection Mixing with Exogenous Anchors

arXiv:2601.08131v4 Announce Type: replace Abstract: Cross-layer reuse of early attention projections can improve optimization and data efficiency, but it creates a structural conflict: the first layer

Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective

arXiv:2605.27476v1 Announce Type: cross Abstract: We characterize the pre-softmax attention matrix mathbf{QK^op} in transformers as an associative memory matrix encoding pairwise associations between

Better heads do not guarantee better binarized constituency parsing

arXiv:2605.28131v1 Announce Type: new Abstract: We revisit punctuation-aware tree binarization for constituency parsing and ask whether dependency-induced headedness improves binary parser supervision

Beyond Chunk-Local Extraction: Cross-Chunk Graph Augmentation for GraphRAG

arXiv:2605.28004v1 Announce Type: new Abstract: GraphRAG extends retrieval-augmented generation by organizing corpora as explicit knowledge graphs, enabling graph-based retrieval for complex question

Beyond Input Understanding: Diagnosing Multilingual Mathematical Reasoning with Directed Acyclic Trace Graphs

arXiv:2605.27715v1 Announce Type: new Abstract: Large reasoning models (LRMs) achieve strong mathematical reasoning performance in English, but remain much less reliable in many low- and medium-resour

Beyond pass@k: Redundancy-Aware RLVR for Multi-Sample Code Generation

arXiv:2605.28022v1 Announce Type: new Abstract: LLMs for code generation are commonly evaluated in repeated-sampling settings using Pass@k, where multiple candidate programs are executed against unit

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models

arXiv:2605.28051v1 Announce Type: new Abstract: Visual token pruning reduces the computational cost of Vision-Language Models (VLMs) by removing redundant visual tokens. Existing methods typically rel

Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data

arXiv:2603.10961v2 Announce Type: replace Abstract: Wearable accelerometers enable large-scale health monitoring, yet learning robust human-activity representations has been constrained by scarce labe

BIRDNet: Mining and Encoding Boolean Implication Knowledge Graphs as Interpretable Deep Neural Networks

arXiv:2605.28739v1 Announce Type: cross Abstract: Tabular data in knowledge-rich domains often carries a latent prior in the form of Boolean implication relationships (BIRs) between pairs of features.

BIRDS: Characterizing and Understanding Biodiversity Impact of Large Language Model Serving

arXiv:2605.27480v1 Announce Type: cross Abstract: Large language model (LLM) serving creates environmental impacts beyond carbon and water, including ecosystem damage through biodiversity-related path

Bound-Constrained Sparse Representation for Electrical Impedance Tomography

arXiv:2605.28392v1 Announce Type: new Abstract: This study proposes a bound-constrained sparse representation (BC-SR) framework for electrical impedance tomography (EIT), aimed at improving conductivi

Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Models

arXiv:2605.28488v1 Announce Type: cross Abstract: We study inference in stochastic block models (SBMs) through the lens of optimal transport (OT). We first establish that maximum likelihood variationa

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective

arXiv:2605.27962v1 Announce Type: new Abstract: This paper describes our approach for the 8th UG2+ Workshop (CVPR 2026) Track~2, which targets semantic segmentation of outdoor scenes degraded by five