Search: “research”

CLUIE: Clustering-Aware Recurrent Propagation with Local Structural Compensation for Underwater Image Enhancement

arXiv:2607.21467v1 Announce Type: new Abstract: Underwater image enhancement remains challenging due to wavelength-dependent light absorption, scattering, and backscattering, which jointly cause color

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Research

Code Monitor Red Teaming for Public-Test-Passing Code

DGX agent

arXiv:2607.20852v1 Announce Type: new Abstract: Visible tests are a common gate for LLM-generated code, but passing them does not certify specification correctness. We study a deployment-like monitori

researcharxiv-cs-ai

24 Jul 2026

Codec-Gauge: Learning Compression-Friendly Gauges for Transformer KV Caches

arXiv:2607.20538v1 Announce Type: cross Abstract: Long-context Transformer inference increasingly relies on KV-cache compression or quantization. Prior rotation and transform-coding results suggest th

Compiling to recurrent neurons

arXiv:2511.14953v2 Announce Type: replace-cross Abstract: Discrete structures are currently second-class in differentiable programming. Since functions over discrete structures lack overt derivatives,

Content Anonymization for Privacy in Long-form Audio

arXiv:2510.12780v3 Announce Type: replace-cross Abstract: Voice anonymization techniques have been found to successfully obscure a speaker's acoustic identity in short, isolated utterances in benchmar

researcharxiv-cs-cl

Context-weighted Discrete Flow Matching

arXiv:2607.21427v1 Announce Type: new Abstract: Discrete flow matching provides a flexible framework for generative modeling on discrete structures. However, the standard factorized training objective

CRAWO: Custom Resources for Adaptive Workload Orchestration

arXiv:2607.20490v1 Announce Type: new Abstract: Edge Intelligence has emerged as a key paradigm for enabling real-time applications in smart cities by shifting computation from centralized cloud data

Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning

arXiv:2607.20666v1 Announce Type: cross Abstract: The robustness of machine learning techniques across heterogeneous network domains remains an open challenge in optical networks. Models trained on da

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding

arXiv:2607.20467v1 Announce Type: new Abstract: While parallel decoding is central to the efficiency of Diffusion Large Language Models (dLLMs), current strategies are often hindered by overly conserv

Declarative Problem Solving in UAM Strategic Deconfliction

arXiv:2607.21197v1 Announce Type: cross Abstract: The growing demand for Urban Air Mobility (UAM) introduces significant challenges in airspace management, particularly within densely populated metrop

DecodeShare: Tracing the Shared Subspace of LLM Decode-Time Decisions

arXiv:2607.20469v1 Announce Type: new Abstract: Large language models (LLMs) handle many tasks with one set of parameters, but under KV-cached inference it is unclear what task-general structure, if a

Demographically-Informed Heat-Mortality Risk Curves via Risk Graph Neural Networks

arXiv:2607.21131v1 Announce Type: cross Abstract: Estimating heat-related mortality risk is a core task in environmental epidemiology, typically addressed with Distributed Lag Non-linear Models (DLNMs

Differentiable Logic Programming to Mitigate Reasoning Shortcuts in Neurosymbolic Systems

arXiv:2607.21185v1 Announce Type: new Abstract: Neurosymbolic (NeSy) systems integrate neural networks with logical reasoning to achieve both generalization and interpretability, but recent work has s

Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering

arXiv:2607.20487v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to answer questions about political information, including in election-adjacent information settings

Distributed Model-Based Diffusion For Scalable Multi-Robot Trajectory Optimization

arXiv:2607.20992v1 Announce Type: new Abstract: Trajectory optimization for multi-robot systems remains a critical challenge, particularly when navigating highly non-convex, non-linear, and non-differ

researcharxiv-cs-ro

Double-Scoring: Reliable Extraction of Strong Lottery Tickets

arXiv:2607.20555v1 Announce Type: new Abstract: The lottery ticket hypothesis proposes that large random neural networks contain sparse subnetworks that can match the performance of dense models after

DS@GT ARC at ImageCLEFmed GANs 2026: Geometric Filtering for Privacy-Preserving CT Slice Generation

arXiv:2607.20692v1 Announce Type: cross Abstract: We present a privacy-preserving framework for synthetic lung CT slice generation developed for the Image-CLEFmed GANs 2026 challenge. The approach com

Emergent Misalignment Recruits a Pre-existing Persona Subspace

arXiv:2607.21356v1 Announce Type: new Abstract: Fine-tuning an aligned language model on a narrow stream of bad advice can make it broadly misaligned on questions unrelated to the training data, a phe

Encoding Event-B Proof Rules in Prolog: An Interactive Sequent Prover for ProB

arXiv:2607.21191v1 Announce Type: cross Abstract: Event-B is a formal method rooted in predicate logic and set theory. We encoded over 600 proof rules in Prolog, enabling a systematic, comprehensible

Error Certificates for KV-Cache Eviction via Randomized Design

arXiv:2607.21475v1 Announce Type: cross Abstract: Deterministic KV-cache eviction keeps the top-k tokens under an importance score and deletes the rest. We prove that this design cannot know what it d

Evolutionarily Stable Stackelberg Equilibrium

arXiv:2603.18385v4 Announce Type: replace-cross Abstract: We present a new solution concept called evolutionarily stable Stackelberg equilibrium (SESS). We study the Stackelberg evolutionary game sett

Exact ReLU realization of affine one-dimensional refinement iterates via residual memory and offset frames

arXiv:2607.20586v1 Announce Type: new Abstract: We study vector-valued affine refinement operators of the form [ (Wgamma)(t)=sum_{jinZ} A_jgamma(Mt-j)+B(t), ] with finitely supported matrix mask and c

Expanding Flow Maps

arXiv:2607.21585v1 Announce Type: new Abstract: Flow-based generative models have enabled remarkable progress in fast and controllable generation across continuous and discrete state spaces, yet exist

Explanation-Based Runtime Verification for Trustworthy ML-driven Optical Networks

arXiv:2607.20675v1 Announce Type: new Abstract: Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, perform

External Clustering Validation by the Homogeneity-Parsimony Trade-off

arXiv:2607.20799v1 Announce Type: new Abstract: Scalar metrics are often used to evaluate clusterings against known classes, but they can obscure a fundamental trade-off: clusterings should be informa

FA-LAM: Focus-Aware Large Avatar Model for One-Shot 4D Animatable Gaussian Head

arXiv:2607.20922v1 Announce Type: new Abstract: We propose FA-LAM, a Focus-Aware Large Avatar Model for one-shot animatable Gaussian head creation, while simultaneously enabling static 3D and dynamic

Finite-Sample Coverage Audits for High-Recall Candidate Generation: Certification and Learning-Theoretic Design

arXiv:2607.21480v1 Announce Type: new Abstract: An initial high-recall stage in an empirical pipeline decides which items pass to later review, labelling, or modelling, and relevant items it misses ar

Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing

arXiv:2507.14268v2 Announce Type: replace Abstract: This paper reviews algorithmic and modeling approaches for fitting generalized power diagrams to three-dimensional image data, a key step in virtual

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts

arXiv:2607.20500v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly on well-specified reasoning tasks with a feasible answer. However, problems encountered in the open world

Foundation-model-guided radiogenomic discovery linking cancer genomes to cancer scans

arXiv:2607.20583v1 Announce Type: cross Abstract: The function of many genes is still unknown, and conventional driver-discovery methods, which rely on how frequently a gene is mutated, cannot assess

Free energy landscape of Dense Associative Memory

arXiv:2607.19195v2 Announce Type: replace-cross Abstract: Using large deviations theory, we solve and obtain a general expression for the free energy functional for a broad class of associative memori

From Atoms to Entropy: Optimal Noise Allocation for Diffusion Training in the Convex Regime

arXiv:2607.20540v1 Announce Type: cross Abstract: How should a diffusion model decide which noise levels to train on, and how much? Despite the importance of this choice, current noise schedules are b

From Errors to Rules: Iterative Prompt Optimization for Text Classification

arXiv:2607.20497v1 Announce Type: new Abstract: Prompt optimization for text classification spans diverse approaches, from demonstration selection to exploration-based search to error-driven diagnosis

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data

arXiv:2607.20970v1 Announce Type: new Abstract: Implicit neural representations (INRs) for time-varying volumetric data are typically trained using dense sampling over spatiotemporal coordinates, wher

FSB-Net: Frequency-Spatial Boundary Network for Brain Stroke Lesion Segmentation in Non-Contrast CT

arXiv:2607.20955v1 Announce Type: new Abstract: Accurate segmentation of brain stroke lesions in non-contrast computed tomography (NCCT) scans is critical for rapid clinical decision-making, yet remai

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

arXiv:2607.21085v1 Announce Type: new Abstract: Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatia

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation

arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic under

Gibbs randomness-compression proposition

arXiv:2505.23869v5 Announce Type: replace-cross Abstract: A proposition that connects randomness and compression is put forward via Gibbs entropy over set of measurement vectors associated with a loss

GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes

arXiv:2607.21117v1 Announce Type: cross Abstract: Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, partic

Graph Learning on Ensembles of Cyclic Peptides: An Investigation of Molecular Ensemble Modeling

arXiv:2607.21561v1 Announce Type: new Abstract: Molecular property prediction from structure often uses a single representative conformation, even though many molecules exist as conformational ensembl

GraphVid: Interactive Graph-Controllable Video Generation

arXiv:2607.21580v1 Announce Type: cross Abstract: Controllable video generation remains challenging due to the difficulty of specifying precise multi-object interactions using text prompts or motion-c

Grounding Investor Views: Neural Predicates in the Black-Litterman Model

arXiv:2607.20533v1 Announce Type: cross Abstract: Portfolio construction under the Black-Litterman model requires investors to specify views on asset returns alongside explicit uncertainty estimates -

HAMON: Passive Optical Sequence Mixing for Long-Horizon Forecasting

arXiv:2606.17028v2 Announce Type: replace-cross Abstract: Simple linear and frequency-domain models remain surprisingly competitive in long-horizon time-series forecasting, and recent mechanistic evid

HierarchicalDAEW: Domain-Aware Edge-Weighted Graph Convolution with Evidential Uncertainty for Multi-Section Spatial Gene Expression Prediction from H&E Histology

arXiv:2607.20896v1 Announce Type: new Abstract: Spatial transcriptomics assays remain costly and technically demanding, restricting transcriptome-wide profiling to specialist settings and preventing r

Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks

arXiv:2607.21366v1 Announce Type: cross Abstract: Deep neural networks encode complex representations, but deconstructing this internal knowledge remains a challenge. Given the link between learning a

How Rules Represent Causal Knowledge: Causal Modeling with Probabilistic Logic Programming

arXiv:2607.21208v1 Announce Type: new Abstract: Pearl famously argues that causal knowledge enables the prediction of intervention effects. By contrast, purely descriptive knowledge supports only conc

Identifying Good Rules for Efficient SAT Encodings of Single-Constant Multiplication Using Machine Learning

arXiv:2607.21188v1 Announce Type: new Abstract: The Single Constant Multiplication problem is a fundamental NP-hard optimization task in hardware design, which seeks to decompose a fixed constant usin

Improved lower bounds for the Shannon capacity of odd cycles

arXiv:2607.21517v1 Announce Type: cross Abstract: The Shannon capacity Theta(G) of a graph G quantifies the maximum rate at which information can be transmitted with zero error over a noisy channel. I