research

LanGuSTE: Language-Guided Coarse-to-Fine Patch Selection for Efficient Whole Slide Image Analysis

arXiv:2508.14537v2 Announce Type: replace Abstract: Whole slide images (WSIs) in computational pathology pose a major computational challenge due to their gigapixel scale, often requiring tens to hund

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Last But Not Least: Boundary Attention CalibratiON for Multimodal KV Cache Compression

DGX agent

arXiv:2606.14782v3 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) achieve strong vision-language reasoning but incur large KV caches and high decoding latency with lon

researcharxiv-cs-cl

25 Aug 2026

Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations

arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented

Learning Sample-wise Rank-aware Interpolation Weights for Composed Visual Data Retrieval

arXiv:2608.22500v1 Announce Type: new Abstract: At the heart of composed visual data retrieval is the fusion of a reference visual input and a textual modification into a single query. While current s

Learning Spherical Occupancy Profiles for Multi-View 3D Reconstruction and Generation

arXiv:2608.23206v1 Announce Type: new Abstract: We study spherical occupancy profiles-the ray-wise occupancy probability profiles P(r) = T(r) o(r) distilled from multi-view 3D Gaussian reconstructions

Learning to Select and Rank from Choice-Based Feedback: A Simple Nested Approach

arXiv:2307.09295v3 Announce Type: replace Abstract: We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially di

Learning with Boolean threshold functions

arXiv:2602.17493v2 Announce Type: replace-cross Abstract: We develop a method for training neural networks on Boolean data in which the values at all nodes are strictly pm 1, and the resulting models

Learning with Local Search MCMC Layers

arXiv:2505.14240v3 Announce Type: replace Abstract: Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing appr

Lexical Perturbations Disrupt LLM Reasoning: An Empirical Study of Attention Diversion

arXiv:2608.22140v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve strong reasoning performance, but their robustness to realistic lexical corruption remains poorly understood. We

Lies We Can Trust: Quantifying Action Uncertainty with Inaccurate Stochastic Dynamics through Conformalized Nonholonomic Lie groups

arXiv:2512.10294v2 Announce Type: replace Abstract: We propose Conformal Lie-group Action Prediction Sets (CLAPS), a symmetry-aware conformal prediction-based algorithm that constructs, for a given ac

researcharxiv-cs-ro

Lightweight Multi-scale Hierarchical Anomaly Detection and Localization for Geospatial Big Data Applications at the Edge

arXiv:2608.22648v1 Announce Type: cross Abstract: As an increasing number of critical applications, including environmental, emergency, meteorological, and agricultural, rely on real-time anomaly dete

LLM-Based Adversarial Persuasion Attacks on Fact-Checking Systems

arXiv:2601.16890v2 Announce Type: replace-cross Abstract: Automated fact-checking (AFC) systems are susceptible to adversarial attacks, enabling false claims to evade detection. Existing adversarial f

LLM-Based Selection of Incongruent Verbal and Nonverbal Behavior for Virtual Humans

arXiv:2608.22731v1 Announce Type: new Abstract: Nonverbal behavior generation systems for virtual agents often take an utterance as input and generate nonverbal behaviors that emphasize or illustrate

LLM Evaluation on Unseen Questions: Contextual Multidimensional IRT Model

arXiv:2608.22295v1 Announce Type: cross Abstract: Evaluation of large language models (LLMs) increasingly requires predicting how a model will perform on new questions or tasks before collecting large

Long-term User Engagement Optimization through Model-agnostic Downstream Rewards Learning

arXiv:2607.14192v3 Announce Type: replace Abstract: As recommender systems mature in the past few years, their optimization objectives have evolved from a primary focusing on short-term behavioral sig

Lookahead-then-Verify: Reliable Constrained Decoding for Diffusion LLMs under Context-Free Grammars

arXiv:2602.00612v3 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) have demonstrated promising generative capabilities and are increasingly used to produce formal languages de

Machine Learning Assisted Inverse Design of Pixelated mmWave Patch Antennas

arXiv:2608.23469v1 Announce Type: cross Abstract: A machine learning-assisted framework for the inverse design of pixelated millimetre-wave patch antennas targeting the 22--30 GHz band is presented. T

MADR: MPC-guided Adversarial DeepReach

arXiv:2510.18845v2 Announce Type: replace Abstract: Hamilton-Jacobi (HJ) Reachability offers a framework for generating safe value functions and policies in the face of adversarial disturbance, but is

researcharxiv-cs-ro

Magnitude Homology Is the Associated Graded of the Length Filtration

arXiv:2608.21479v1 Announce Type: cross Abstract: Magnitude homology is graded by length and knows nothing of persistence. Its persistent refinement knows nothing of where its bars begin and end. We s

Mapping the Concept Landscape: Structural Perception of Global Distributions for Transparent Data Pruning

arXiv:2608.22858v1 Announce Type: cross Abstract: Existing data pruning methods predominantly rely on high-dimensional feature embeddings to measure sample importance. However, these compressed vector

Maximum-distance nonnegative matrix factorization for unmixing highly mixed grain-size distribution data: A generalization of AnalySize

arXiv:2608.22681v1 Announce Type: new Abstract: Nonnegative matrix factorization (NMF) decomposes a nonnegative matrix into the product of two nonnegative matrices. This property makes NMF well suited

MDFI: A Multi-Domain Features Integration for Compressed Video Quality Enhancement

arXiv:2608.21495v1 Announce Type: cross Abstract: The latest video coding standard, H.266/VVC, has demonstrated significant improvements in compression efficiency compared to H.265/HEVC. Despite its a

Measuring Gender Representation in Animated Films

arXiv:2608.21429v1 Announce Type: new Abstract: Animated films--often developed with an audience of children in mind--are an important vector for enculturation, and empirical work that has examined th

Measuring Stability and Failure Behavior in Language Models Under Structured Perturbations

arXiv:2608.22138v1 Announce Type: new Abstract: Language models are usually judged by a single accuracy score, which does not reveal how their performance degrades as inputs are perturbed. We present

Mechanistic Interpretability of Chain-of-Thought Reasoning via Sequential Activation Patching

arXiv:2608.22332v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable problem-solving capabilities when guided by Chain-of-Thought (CoT) prompting, yet the internal mecha

Mining Artifacts in Mycelium SEM Micrographs

arXiv:2103.07573v2 Announce Type: replace-cross Abstract: Mycelium is a promising biomaterial based on fungal mycelium, a highly porous, nanofibrous structure. Scanning electron micrographs are used t

Mirror descent algorithms with logarithmic barriers

arXiv:2608.22834v1 Announce Type: cross Abstract: This work derives convergence guarantees for mirror descent and proximal mirror descent algorithms when a logarithmic barrier is used as a distance-ge

Mitigating Explanation Leakage in Financial Fraud Detection Systems

arXiv:2608.22607v1 Announce Type: new Abstract: Financial fraud detection relies heavily on centralized machine learning models. This creates serious data privacy risks. Federated Learning (FL) decent

MLLM-Assisted Audio VOS: A 3rd Place Report for the MeViS-Audio Track, 8th LSVOS Challenge

arXiv:2608.23234v1 Announce Type: new Abstract: In this technical report, we present a training-free framework for audio-guided video object segmentation, which integrates Multimodal Large Language Mo

MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design

arXiv:2511.18980v2 Announce Type: replace-cross Abstract: Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains f

Modalities Should Talk to Each Other: Dual-Stream Multimodal Learning for Long-Horizon Influenza Forecasting

arXiv:2608.23373v1 Announce Type: new Abstract: Forecasting long-range influenza-like illness (ILI) matters for public health readiness. Publicly available surveillance datasets typically pair numeric

Model of Models: When Does Emitting a Specialist Beat Attending, Adapting, or Tuning?

arXiv:2608.21386v1 Announce Type: cross Abstract: Given a task described by a few examples, how should a model be specialized to it? Four mechanisms are available -- zero-shot, in-context attention, t

Modeling Claim Dependency Structure for Patent Litigation Prediction with Graph Attention Networks

arXiv:2608.21924v1 Announce Type: new Abstract: Patent litigation imposes substantial costs on firms and distorts R&D incentives, making early risk identification a practically important task. While p

ModTrack: Sensor-Agnostic Multi-View Tracking via Identity-Informed PHD Filtering with Covariance Propagation

arXiv:2603.15812v3 Announce Type: replace Abstract: Multi-View Multi-Object Tracking (MV-MOT) aims to localize and maintain consistent identities of objects observed by multiple sensors. This task is

Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules

arXiv:2608.22642v1 Announce Type: cross Abstract: Despite recent advances in molecular foundation models, several limitations remain, such as chemically invalid augmentations, modality collapse, and i

More accurate behavioral predictions with hybrid Bayesian-connectionist models

arXiv:2608.22154v1 Announce Type: new Abstract: Researchers must often choose between Bayesian or neural network models of behavior, two paradigms with complementary strengths and weaknesses. An ideal

Most of the LLM routing gap is task type

arXiv:2608.23023v1 Announce Type: new Abstract: An LLM router picks which model should answer each query. The appeal is that models fail on different questions. Whatever single model is best overall s

Motion-Aware Reasoning from Speech to Mask Tracks: Runner-up Solution for the MeViS-Audio Track of the 8th LSVOS Challenge 2026

arXiv:2608.22337v1 Announce Type: cross Abstract: Speech-guided referring video object segmentation aims to recover the mask tracks of objects specified by a spoken motion description. Here, speech ca

MotionDLO: Hybrid Event- and Frame-Based Tracking of Deformable Linear Objects

arXiv:2608.22398v1 Announce Type: cross Abstract: Reliably tracking moving deformable linear objects (DLOs) while simultaneously ensuring robustness, accuracy, and temporally consistent state estimati

Multi-Winner Voting with Argumentative Ballots

arXiv:2608.23247v1 Announce Type: cross Abstract: We introduce multi-winner voting with argumentative ballots (MVArg) and investigate theoretical properties. As our conceptual contribution, we general

Multimodal Injury Risk and Performance Prediction in Tennis Using Weighted Ensemble Learning

arXiv:2608.21530v1 Announce Type: new Abstract: Machine learning has had a positive impact on the sports industry, with one of its most promising applications being the prediction of athlete performan

Multimodal pseudo-CT synthesis for PET attenuation correction using separate modality encoding and topogram conditioning

arXiv:2608.21481v1 Announce Type: cross Abstract: We participated in the BIC-MAC Challenge with a multimodal 3D patch-based U-Net for pseudo-CT generation from NAC-PET, MRI, and 2D topograms. By using

MusPyExpress: Extending MusPy with Enhanced Expression Text Support

arXiv:2608.21678v1 Announce Type: cross Abstract: Current work in modeling symbolic music primarily relies on representations extracted from MIDI-like data. While such formats allow for modeling symbo

Neighbor-embedded Graph Neural Network-based Crowd Delivery Traffic Management in Smart City

arXiv:2608.22555v1 Announce Type: cross Abstract: The significant upsurge in vehicle traffic presents a considerable challenge in the pursuit of smart mobilization and transportation (SMT) worldwide.

NemoSplat: Feed-Forward 4D Gaussian Splatting for Media-Aware Underwater Reconstruction

arXiv:2608.22888v1 Announce Type: new Abstract: Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpre

Neural Network Field Theory at Finite Width

arXiv:2608.21588v1 Announce Type: cross Abstract: Under mild assumptions, any quantum mechanical (QM) model or quantum field theory (QFT) admits a representation in terms of an ensemble of neural netw

Neural Operator based Multi-Field Reconstruction of Inner Solar Boundary State

arXiv:2608.22782v1 Announce Type: cross Abstract: The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic pro

Neural-Symbolic Reasoning over Knowledge Graphs: A Survey from a Query Perspective

arXiv:2412.10390v2 Announce Type: replace Abstract: Knowledge graph reasoning is pivotal in various domains such as data mining, artificial intelligence, the Web, and social sciences. These knowledge