research

Minimax bounds for watermarked and masked recursive discrete distribution estimation

arXiv:2608.31091v1 Announce Type: cross Abstract: Watermarking has been proposed as a way to identify synthetic samples in estimation settings where no metadata is available to distinguish them from r

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

MIRAGE-CAD: Construction-Mediated Multimodal Generation of Executable CAD Programs

DGX agent

arXiv:2608.28669v1 Announce Type: new Abstract: Recovering an executable parametric CAD program from an observed object is fundamentally ambiguous, because the same final geometry can result from diff

researcharxiv-cs-cv

1 Sept 2026

Mixture-Greedy for Online Generative Model Selection: Is UCB Necessary in Diversity-Aware Multi-Armed Bandits?

arXiv:2603.21716v2 Announce Type: replace-cross Abstract: Efficient selection among multiple generative models is increasingly important in modern generative AI, where sampling from suboptimal models

mmIR: Frequency-Space Inverse Rendering for 3D Millimeter-Wave Radar ADC Synthesis

arXiv:2608.28913v1 Announce Type: new Abstract: High-resolution 3D radar data is scarce. Commodity mmWave sensors use small antenna arrays that limit angular resolution to several degrees, and existin

Modality Fault Lines: Structural Corruptions Reveal Fragile Omni-Modal Reasoning

arXiv:2608.29278v1 Announce Type: new Abstract: Omni-modal large language models are increasingly evaluated on clean text--vision--audio inputs, where every channel is present, synchronized, and readi

Mode Connectivity Beyond Classifiers: Evidence from Generative and Contrastive Models

arXiv:2608.30366v1 Announce Type: new Abstract: The loss landscape of Deep Neural Networks (DNNs) exhibits highly complex and non-convex properties. Recent studies have revealed the phenomenon of mode

Module Number Adaptive Visual Shape Control for Serial Modular Soft Robots

arXiv:2608.29547v1 Announce Type: new Abstract: Image based shape control provides a simple means of controlling the whole body configuration of soft robots. However, existing data driven approaches a

researcharxiv-cs-ro

MolLedger: An Additive Graph Neural Network with Chemically Grounded ADME Attributions

arXiv:2608.30636v1 Announce Type: new Abstract: Optimizing absorption, distribution, metabolism, and excretion (ADME) is an important part of small molecule drug discovery. Many machine learning model

More Haste, Less Speed: Weaker Single-Layer Watermark Improves Distortion-Free Watermark Ensembles

arXiv:2602.11793v2 Announce Type: replace-cross Abstract: Watermarking has emerged as a crucial technique for detecting and attributing content generated by large language models. While recent advance

More Perspectives, Stronger Signals: Multi-Perspective Enhancement and Progressive Fusion for Multimodal Entity Representation Learning

arXiv:2608.29139v1 Announce Type: new Abstract: Learning effective multimodal entity representations is fundamental for reasoning tasks such as multimodal knowledge graph completion (MMKGC). However,

Motion-Saliency Complementary Masked Modeling for Point Cloud Video Understanding

arXiv:2608.30279v1 Announce Type: new Abstract: Point cloud video representation learning is crucial for 3D dynamic scene understanding. In this paper, we propose MoSaiC, a novel Motion-Saliency Compl

MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI

arXiv:2608.30975v1 Announce Type: cross Abstract: Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep lear

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants

arXiv:2510.01159v3 Announce Type: replace Abstract: Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applicati

Multimodal Adaptive Expert Selection with Text Routing and Ordinal Prototype Optimization for Sentiment Analysis

arXiv:2608.30726v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) is a fundamental component of affective computing that aims to decipher complex emotional states by integrating verb

Multivariate Scientific Data Compression with Learned Cross-Variable Latent Decorrelation and Autoregressive Entropy Modeling

arXiv:2608.30262v1 Announce Type: new Abstract: Scientific simulations generate collections of physical fields with heterogeneous statistics and dependencies, yet learned compressors often encode thos

Nested Convex-Body Chasing for Online Optimization with Evolving Feasible Sets

arXiv:2608.29074v1 Announce Type: new Abstract: We study online optimization with nested shrinking feasible regions in two settings: convex optimization with nested evolving feasible sets (CONES) and

Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory

arXiv:2608.29714v1 Announce Type: cross Abstract: Longitudinal cohort studies produce repeated data that enable the assessment of time-varying association patterns between exposures and health outcome

NLP-Driven Knowledge Extraction and Thematic Classification of Translated Ancient Indian Medical Texts

arXiv:2608.28608v1 Announce Type: cross Abstract: Ancient Indian medical texts like Sushruta Samhita have extensive information on diseases, treatments, and surgical techniques. Yet, their ancient for

NVE: A Separability and Coverage-Aware Internal Validation Metric for Biclustering

arXiv:2608.29045v1 Announce Type: new Abstract: Biclustering, or co-clustering, aims to discover coherent submatrices by grouping rows and columns of a data matrix simultaneously. This local two-dimen

OASIS: Optimizing Attacker Sequences for Hard-Label Black-Box Text Attacks

arXiv:2608.29568v1 Announce Type: cross Abstract: Different attack methods follow different search trajectories, they succeed on different subsets of samples, whereas existing hard-label black-box tex

ObjectSplat: Improving Mesh Fidelity and Interactivity for 3D Scenes via Object-Level Mesh Splatting

arXiv:2608.30423v1 Announce Type: cross Abstract: Splatting-based algorithms reconstruct photorealistic, real-time-renderable, and mesh-exportable 3D scenes from regular images, but they represent a s

OCR-Based Field Extraction for Archaeological Pottery Metadata: The CENTURIA Dataset

arXiv:2608.30616v1 Announce Type: new Abstract: Pottery is a primary source for reconstructing the chronological and economic dimensions of past societies. Archaeologists often document ceramic finds

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information

arXiv:2607.19313v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on diffic

Off-Manifold Refinement: Guiding Video Generators with a Frozen World Model

arXiv:2608.29904v1 Announce Type: new Abstract: Modern video generators routinely fail at physical dynamics: objects float, trajectories violate gravity, contacts vanish. Standard denoising and flow-m

On the Complexity of the Compatibility Problem for Succinctly Encoded Conditional Distributions

arXiv:2608.31120v1 Announce Type: new Abstract: The motivation for this paper is the investigation of the trade-offs implicit in probabilistic models used in machine learning. Models are often used to

On the Instance Hardness as a Decision Criterion in TinyML Systems

arXiv:2608.29913v1 Announce Type: new Abstract: TinyML includes the implementation of machine learning on devices with limited memory and computing resources. With the development of technology, AI sy

On the Optimality of Kinship Naming: an Information-theoretic Approach

arXiv:2511.19120v2 Announce Type: replace-cross Abstract: The structure of naming systems in natural languages hinges on a trade-off between high informativeness and low complexity. Focusing on the do

On the Prospects of Dynamic LLM Conversations in Software Development

arXiv:2608.30756v1 Announce Type: cross Abstract: Large language models (LLMs) have become an essential tool for assisting developers, yet we still lack knowledge on ways to effectively support their

On the Recoverability of Private Information Unlearning in Large Language Models

arXiv:2608.29943v1 Announce Type: cross Abstract: Large language models (LLMs) can memorize sensitive information, raising serious privacy concerns. Machine unlearning offers a potential solution to r

On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation

arXiv:2608.29944v1 Announce Type: new Abstract: Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learni

One note in three: a verified census of three deployed AI scribes, and the instrument that counted it

arXiv:2608.31017v1 Announce Type: cross Abstract: Ambient AI scribes draft clinical notes under the reassurance that a clinician signs every note. We audited three commercial AI scribes on the same 14

Opinionated, Hesitant and Stressed: Three Studies of How Politicians Speak in Four Slavic Parliaments

arXiv:2608.30828v1 Announce Type: new Abstract: We present three large-scale studies of spoken parliamentary speech across four Slavic languages (Croatian, Czech, Polish, Serbian), drawing on over 6,0

Optimized Modular Design and Development of a Tilt-Rotor Bicopter Drone

arXiv:2608.30222v1 Announce Type: new Abstract: Hybrid systems like tilt-rotor bicopter drones combine the beneficial characteristics of both fixed-wing and rotary-wing technology, enabling long endur

researcharxiv-cs-ro

OPUS-V2: Bridging the Gap between Sparse Points and Dense Voxels

arXiv:2608.29187v1 Announce Type: new Abstract: The point-based occupancy prediction paradigm has achieved an attractive trade-off between accuracy and efficiency by modeling 3D space sparsely. Howeve

PACE-RAG: Patient-Aware Contextual and Evidence-Constrained RAG for Clinical Drug Recommendation

arXiv:2603.17356v3 Announce Type: replace Abstract: Drug recommendation requires a deep understanding of individual patient context, especially for complex conditions like Parkinson's disease. While L

PAGE-RAG: Provenance-Aware Graph Evidence Promotion for Fixed-Budget Multi-hop Retrieval-Augmented Generation

arXiv:2608.29753v1 Announce Type: new Abstract: Multi-hop question answering in retrieval-augmented gener?ation (RAG) often benefits from retrieving beyond the few candidates that will finally be read

Parallel Time-Band Mixing with Learned Observation-Adding for Robust ASR Front-Ends

arXiv:2608.30326v1 Announce Type: cross Abstract: Speech enhancement is often used as a front-end for robust ASR, yet recurrent temporal and cross-band modules introduce sequential dependencies that r

Partition-Aware Unlearning for Removing Spurious Correlations in Large Vision-Language Models

arXiv:2608.29996v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) achieve strong performance across many multimodal tasks; however, they often exploit spurious object-background c

Peer Oversight in Collective Decision Making

arXiv:2608.28754v1 Announce Type: cross Abstract: This article introduces peer k-oversight, a property of sequential collective decision mechanisms requiring at least k agents to be responsible for ev

PEPPER: Perception-Guided Perturbation for Robust Backdoor Defense in Text-to-Image Diffusion Models

arXiv:2511.16830v4 Announce Type: replace Abstract: Recent studies show that text-to-image (T2I) diffusion models are vulnerable to backdoor attacks, where a trigger in the input prompt can steer gene

Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks

arXiv:2501.18018v2 Announce Type: replace-cross Abstract: The neurons of artificial neural networks were originally invented when much less was known about biological neurons than is known today. Our

PERSIST: Persistent-State Discrimination for Shot Boundary Detection

arXiv:2608.29287v1 Announce Type: new Abstract: Shot boundary detection (SBD) is widely treated as the localisation of local visual discontinuities, yet many false positives such as hand-held shake, i

Personalized Treatment Outcome Prediction from Scarce Data via Dual-Channel Knowledge Distillation and Adaptive Fusion

arXiv:2510.26444v2 Announce Type: replace-cross Abstract: Personalized treatment outcome prediction based on trial data for small-sample and rare patient groups is a critical task in precision medicin

Personas Differ from Native-Language Generation: Language Pathways Shape LLM Interpersonal Advice

arXiv:2608.30873v1 Announce Type: cross Abstract: LLMs are increasingly used for interpersonal advice and as tools for studying social behavior across languages and cultures. A common shortcut for eli

Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion

arXiv:2603.03485v4 Announce Type: replace-cross Abstract: Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often strugg

PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation

arXiv:2608.29549v1 Announce Type: cross Abstract: Text-to-spatial audio generation, such as text-to-First-Order Ambisonics (FOA), provides a convenient way to create spatial audio for billion-dollar g

POCI-Diff: 3D-Layout Guided Diffusion for Controllable Synthetic Surveillance Data Generation

arXiv:2601.14056v2 Announce Type: replace-cross Abstract: Training robust visual surveillance models requires large-scale datasets with precise spatial annotations, yet collecting real surveillance da

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation

arXiv:2402.04355v4 Announce Type: replace-cross Abstract: We propose a likelihood-free method for comparing two distributions given samples from each, with the goal of assessing the quality of generat