Search: “research”

Noisy-Channel Minimum Bayes Risk Decoding

arXiv:2607.05198v1 Announce Type: cross Abstract: Minimum Bayes Risk (MBR) decoding yields more robust and higher-quality text generation than maximum a posteriori (MAP) decoding by selecting hypothes

Non-asymptotic Convergence of Stochastic Gradient Descent in Score-based Generative Models

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DGX agent

arXiv:2607.04775v1 Announce Type: cross Abstract: Score-based Generative Models (SGMs) have achieved impressive performance in data generation across a wide range of applications. While the statistica

researcharxiv-cs-lg

7 Jul 2026

NouveauVoice: Generating Novel Pseudo Speakers for Voice Anonymization

arXiv:2607.03985v1 Announce Type: cross Abstract: Advanced neural technologies in speech synthesis and voice conversion (VC) have introduced severe risks to personal privacy, necessitating robust Spea

ObjRetarget: An Object-Aware Motion Retargeting Framework with Anthropomorphic Arm Constraints and Polyhedral Hand Modeling

arXiv:2607.03828v1 Announce Type: new Abstract: Learning robot dexterous manipulation from human manipulation videos requires reliably retargeting human intent to executable robot actions while mainta

researcharxiv-cs-ro

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights

arXiv:2607.03108v1 Announce Type: cross Abstract: Post-hoc analysis of trained neural network weights often seeks to recover geometric structure directly from the parameters. We show that, for positio

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

arXiv:2603.06577v2 Announce Type: replace Abstract: While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architec

On a Geometry of Interbrain Networks

arXiv:2509.10650v4 Announce Type: replace-cross Abstract: Effective analysis in neuroscience benefits significantly from robust conceptual frameworks. Traditional metrics of interbrain synchrony in so

On Pairwise Quantile Regression -- Statistical Guarantees and Applications

arXiv:2607.04431v1 Announce Type: cross Abstract: Quantile regression provides a powerful tool for summarizing the conditional distribution of a real valued random variable (r.v.) of interest Y as a f

On Preserving Geometrical Invariance for Superpixel Image Classification using Graph Transformer

arXiv:2607.04262v1 Announce Type: new Abstract: Convolutional Neural Network (CNN) and Vision Transformer (ViT) for image classification exploit a dense grid of pixels containing redundant information

On Regularization via Early Stopping for Least Squares Regression

arXiv:2406.04425v2 Announce Type: replace Abstract: A fundamental problem in machine learning is understanding the effect of early stopping on the parameters obtained and the generalization capabiliti

On the Convergence of Adam, Revisited

arXiv:2607.03519v1 Announce Type: new Abstract: We show that projected Adam for online optimization with arbitrary moment decay parameters eta_1,eta_2in[0,1) can have average regret bounded away from

On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models

arXiv:2607.04332v1 Announce Type: new Abstract: In this paper, we consider the setting where large language models (LLMs) are trained using reinforcement learning (RL) to simultaneously improve reason

Open Problem: Is Interaction Necessary for Order-Optimal 1-bit Mean Estimation?

arXiv:2607.02896v1 Announce Type: cross Abstract: We ask whether interaction is necessary for order-optimal 1-bit mean estimation over nonparametric finite-moment classes. Adaptive threshold-query pro

OpenSIR: Open-Ended Self-Improving Reasoner

arXiv:2511.00602v4 Announce Type: replace Abstract: Recent advances in large language model (LLM) reasoning through reinforcement learning rely on annotated datasets for verifiable rewards, which may

Operator-on-F complements value-equivalence: a planning-time diagnostic for latent world models

arXiv:2607.04464v1 Announce Type: cross Abstract: World-model evaluation for model-based reinforcement learning typically asks whether the learned model predicts reward and value well, which can leave

Optimal Mixture-of-Experts Model Averaging for Conditional Generative Models

arXiv:2607.04360v1 Announce Type: cross Abstract: Conditional generative models have emerged as powerful tools for sampling from target conditional distributions, driving substantial advances across a

Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing

arXiv:2607.05240v1 Announce Type: cross Abstract: Computing-in-Memory (CIM) accelerators execute Matrix-Vector Multiplications (MVMs) in memory, making them a compelling solution for Machine Learning

Order-based Causal Discovery for Multistage Processes

arXiv:2607.03971v1 Announce Type: cross Abstract: Causality has become an increasingly important tool for gaining a deeper understanding of complex systems. Among various causal analysis methods, caus

Ossetic-COT: Designing a morphologically annotated corpus and morphological analyzer for Ossetic

arXiv:2607.04895v1 Announce Type: new Abstract: In this work we present the first morphologically annotated corpus for Iron Ossetic that conforms to the Universal Dependencies schema. The corpus inclu

Out-of-Distribution Detection in Molecular Complexes via Diffusion Models for Irregular Graphs

arXiv:2512.18454v3 Announce Type: replace Abstract: Predictive machine learning models generally excel on in-distribution data, but their performance degrades on out-of-distribution (OOD) inputs. Reli

Out-of-distribution Neural Inference in Dynamical Ising Models

arXiv:2607.03039v1 Announce Type: new Abstract: Neural networks are increasingly used to infer hidden physical structure from dynamical observations, yet it remains unclear whether their out-of-distri

PAGE: Towards Practical Human-level Gaze Target Estimation

arXiv:2607.04860v1 Announce Type: new Abstract: Gaze target estimation, the task of predicting where a person is looking in a scene, is crucial to understanding human attention and intent. It is a cha

Panorama: Fast-Track Nearest Neighbors

arXiv:2510.00566v4 Announce Type: replace-cross Abstract: Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate ve

Parallelized Autoregressive Decoding for Omni-Modal Dense Video Captioning

arXiv:2607.02963v1 Announce Type: cross Abstract: Dense video captioning aims to generate temporally grounded descriptions of video events, benefiting both event-level video understanding and generati

PAST-TIDE: Prototype-Anchored Statement Tuning with Topic-Invariant Normalization for Stance Detection

arXiv:2607.04690v1 Announce Type: new Abstract: We introduce PAST-TIDE, our stance detection system addressing both subtasks of the StanceNakba Shared Task at NakbaNLP@LREC-COLING 2026. The main idea

Pathways of Visual Information Flow in Vision-Language Models

arXiv:2607.03358v1 Announce Type: cross Abstract: We study how visual information is routed in vision-language models (VLMs). Using causal patching on controlled synthetic and natural datasets, we fin

PCA of probability measures: Sparse and Dense sampling regimes

arXiv:2602.02190v2 Announce Type: replace-cross Abstract: A common approach to perform PCA on probability measures is to embed them into a Hilbert space where standard functional PCA techniques apply.

Personalized Causal Recourse: A Human-In-The-Loop Approach

arXiv:2607.03425v1 Announce Type: new Abstract: Algorithmic recourse addresses the challenge of providing tailored recommendations to users affected by unfavorable machine learning decisions, in poten

PhenoNEST: A Neuro-Symbolic Framework for Ontology-Aware Multimodal Plant Phenotyping and Trait Discovery

arXiv:2607.03245v1 Announce Type: new Abstract: High-throughput plant phenotyping generates valuable data that often remains trapped in unstructured text and isolated RGB images. To bridge this semant

Physics-Informed Graph Learning with Uncertainty Awareness for Open-Set Domain Generalization in Fault Diagnosis

arXiv:2607.04188v1 Announce Type: new Abstract: Intelligent industrial maintenance critically relies on reliable fault diagnosis of rotating machinery. However, it faces formidable challenges from unk

Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speech

arXiv:2607.05165v1 Announce Type: new Abstract: Non-invasive brain-to-speech decoding aims to restore communication to patients suffering from neurodegenerative disease, without the risks of neurosurg

Piecewise Dynamic Diffusion Regularization for Reconstruction of Cardiac Cine MRI

arXiv:2607.03299v1 Announce Type: cross Abstract: Real-time cardiac cine MRI enables visualization of the beating heart during free breathing, but severe undersampling and motion make reconstruction h

PixCon: Clean-Positive Contrastive Learning for Foundation-Model Semi-Supervised Segmentation

arXiv:2607.03068v1 Announce Type: cross Abstract: Semi-supervised semantic segmentation (SSSS) has long turned on one question, which pseudo-labels to trust, and answered it with ever more careful con

PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space

arXiv:2607.05373v1 Announce Type: new Abstract: 3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generat

Platonic Projection Structures: Operator-Induced Observability in Representation Learning

arXiv:2607.05175v1 Announce Type: new Abstract: We characterize observability in representation learning through Platonic Projection Structures (PPS), an operator-theoretic framework for analyzing rep

PLoRA: Efficient Concurrent LoRA Training for Large Language Models

arXiv:2508.02932v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has gained popularity as a fine-tuning approach for Large Language Models (LLMs) due to its low resource requirements and

PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction

arXiv:2607.02881v1 Announce Type: new Abstract: Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelli

Predicting the Emergence of Induction Heads in Language Model Pretraining

arXiv:2511.16893v3 Announce Type: replace Abstract: Specialized attention heads dubbed induction heads (IHs) have been argued to underlie the remarkable in-context learning capabilities of modern lang

Predicting Therapeutic Outcome via Aligning Patient-Specific Knowledge Graph and Gene-Level Perturbation Representations

arXiv:2607.04557v1 Announce Type: cross Abstract: Accurate prediction of patient-specific therapeutic response from pre-treatment transcriptomes is hindered by the scarcity of matched clinical respons

PreSIST: Vision-Language-Informed Object Persistence Prediction in Open-World Scenes

arXiv:2607.04057v1 Announce Type: new Abstract: Robots deployed over long periods must reason about environments that change over time. Existing long-term perception systems often address object chang

Pretreatment MRI reveals a latent, molecular-subtype-independent structural phenotype that organizes treatment trajectories and recurrence risk

arXiv:2607.02768v1 Announce Type: cross Abstract: Pathologic complete response and tumor shrinkage measure whether breast cancer responds to neoadjuvant therapy, but not whether that response was stru

Prior Diffusiveness and Regret in the Linear-Gaussian Bandit

arXiv:2601.02022v2 Announce Type: replace Abstract: We prove that Thompson sampling exhibits ilde{O}(sigma d sqrt{T} + d r sqrt{Tr(Sigma_0)}) Bayesian regret in the linear-Gaussian bandit with a N(mu_

Privacy-Preserving Industrial Ergonomics: mmWave-Based Automated REBA Scoring and Pose Estimation

arXiv:2607.02611v1 Announce Type: new Abstract: Work-related Musculoskeletal Disorders (WMSDs) require continuous ergonomic assessments. While Rapid Entire Body Assessment (REBA) is a gold-standard ob

Privacy-Preserving Robustness Verification for Neural Networks

arXiv:2607.05251v1 Announce Type: cross Abstract: Neural network verification and data privacy are inherently in tension: verification demands full access to model parameters and input data, yet both

Probably Correct Optimal Stable Matching under Two-Sided Uncertainty

arXiv:2607.04824v1 Announce Type: new Abstract: We study a sequential learning problem for stable matchings in two-sided markets where preferences on both sides are initially unknown. We focus on a ce

Probe-EM: Targeted Neuron Tracing via Training-Free Semantic Verification

arXiv:2607.04696v1 Announce Type: new Abstract: Establishing large-scale, high-resolution neural connectivity maps is fundamental to elucidating the structural basis of brain function. However, when p

Probing Low-Level Acoustic Attribute Encoding in CLAP Audio Embeddings

arXiv:2607.03806v1 Announce Type: cross Abstract: Audio foundation models are widely adopted as general-purpose feature extractors, yet the internal structure of their learned representations remains

ProCon: Projection-Consistency Memory for Training-Free Anomaly Detection

arXiv:2607.04894v1 Announce Type: new Abstract: Memory-based anomaly detection is attractive because it localizes defects from normal images without training a decoder or synthesizing pseudo anomalies