Search: “research”

Latent Cluster Analysis for Vision-Language-Action Models

arXiv:2609.02634v1 Announce Type: new Abstract: Vision-Language-Action (VLA) Models are increasingly used in robotics for their ability to ground language and perception into action, yet the internal

researcharxiv-cs-ro

Learning-Based Reconstruction Attacks on Coordinate-Obfuscated Point Clouds

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DGX agent

arXiv:2609.02568v1 Announce Type: cross Abstract: Volumetric video based on point cloud representations enables immersive virtual and augmented reality applications but introduces significant challeng

researcharxiv-cs-lg

3 Sept 2026

Learning Evidence Sufficiency Boundaries for Selective Answering in Grounded Multi-Hop QA

arXiv:2609.01687v1 Announce Type: new Abstract: Grounded question answering systems should answer only when the supplied evidence supports the answer. In multi-hop QA, this requirement is difficult be

Learning Spectral-Like Mesh-Free Discretisations

arXiv:2609.02833v1 Announce Type: cross Abstract: Meshfree methods such as smoothed particle hydrodynamics (SPH) with kernel corrections, radial basis function-generated finite differences (RBF-FD), a

Learning the Constitutive Behavior of Materials via Neural Operators and Causal Attention: Case Studies in Plasticity and Damage

arXiv:2609.02194v1 Announce Type: new Abstract: Classical constitutive modeling of path-dependent inelastic materials relies on internal state variables whose evolution equations must be postulated ba

Looped Transformers under the Jacobian Lens: Does the Global Workspace Survive Recurrence?

arXiv:2609.01924v1 Announce Type: new Abstract: Recent work identifies a mid-depth band of verbalisable, causally potent representations in a standard feedforward transformer --- a functional analogue

MARS: What Retrieval Signals Are Hidden in Multimodal Large Language Models for Text-Video Retrieval?

arXiv:2609.02565v1 Announce Type: new Abstract: Text-video retrieval requires representations that can distinguish videos with similar scenes, actions, and temporal patterns. Recent multimodal large l

Median-of-Means as an Extremal Convex Estimator and a Nonconvex Route to the Trimmed Oracle

arXiv:2609.01689v1 Announce Type: new Abstract: We revisit median-of-means estimation from a deterministic optimization viewpoint and develop a family of block-Lp estimators for robust learning with h

MineTRACE: An Evidence-Grounded Interactive Reasoning System for Mineral Prospectivity

arXiv:2609.02060v1 Announce Type: new Abstract: Mineral exploration requires integrating heterogeneous geochemical, geophysical, and geological evidence, yet existing prospectivity systems often provi

MM++: Post-Hoc Scale-Invariant Multilayer OOD Detection via Top-K Gated Feature Fusion

arXiv:2606.17352v2 Announce Type: replace-cross Abstract: We introduce MM++ (Multilayer Mahalanobis++), a strictly post-hoc, and scale-invariant framework for Out-of-Distribution (OOD) detection. To a

MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation

arXiv:2405.00448v5 Announce Type: replace Abstract: This paper introduces MMTryon, a multi-modal multi-reference VIrtual Try-ON (VITON) framework, which can generate high-quality compositional try-on

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy

arXiv:2505.21907v3 Announce Type: replace Abstract: AI copilots represent a new generation of AI-powered systems designed to assist users, particularly knowledge workers and developers, in complex, co

Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency

arXiv:2609.02728v1 Announce Type: cross Abstract: We study when and how momentum improves large-batch training in the one-pass regime, using power-law kernel regression as a tractable setting. We firs

Monotonic anomaly detection

arXiv:2410.23158v3 Announce Type: replace Abstract: Semi-supervised anomaly detection is based on the principle that any record that looks different from normal training data is a potential anomaly. H

MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection

arXiv:2609.02493v1 Announce Type: new Abstract: Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locat

researcharxiv-cs-ro

Multi-Tool Image Editing Attribution in Facial Forgery

arXiv:2609.02751v1 Announce Type: new Abstract: As generative AI tools become increasingly powerful and easy to use, people can easily edit portrait images with a prompt, necessitating the task of ima

NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo

Neural operators approximate strongly continuous convex monotone semigroups

arXiv:2609.02727v1 Announce Type: cross Abstract: We approximate strongly continuous convex monotone semigroups by learning their Chernoff-type one-step operators with neural operators. First, we intr

Nonasymptotic CLT and Error Bounds for Linear Two-Time-Scale Stochastic Approximation

arXiv:2502.09884v4 Announce Type: replace-cross Abstract: We consider linear two-time-scale stochastic approximation algorithms driven by martingale noise. Recent applications in machine learning moti

Not All Agreement Counts as Corroboration: Provenance-Conserving Multi-View Fusion for Typed Action Admission in Human-Robot Collaboration

arXiv:2609.01662v1 Announce Type: cross Abstract: For embodied systems, predictive agreement alone does not determine whether evidence warrants action; evidential origin matters. Repeated inference ov

oHC: Orthogonal Hyper-Connections on SO(4) via Quaternions

arXiv:2609.02672v1 Announce Type: new Abstract: Hyper-Connections (HC) replace the single residual stream of a Transformer with n parallel ones, mixing them at every layer with a learned n imes n resi

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models

arXiv:2607.19128v2 Announce Type: replace Abstract: Vision-language models (VLMs) provide a unified representation space for textual and visual information, yet their potential as general-purpose back

Online Non-Monotone DR-Submodular Maximization Matching the Offline 0.401 Factor

arXiv:2609.02145v1 Announce Type: cross Abstract: We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the d-dimensional unit cu

OR-Transformer: Scaling Real-Time Decision-Making to 1,000 Items

arXiv:2609.01933v1 Announce Type: new Abstract: Modern supply chain operations can require coordinating replenishment across thousands of heterogeneous items under correlated stochastic demand, hetero

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

arXiv:2609.01896v1 Announce Type: cross Abstract: Power-outage planning requires scenarios before an event occurs. These scenarios must represent uncertainty in magnitude, timing, and duration while p

PIE-APT: Abductive Planning over Temporal Dynamic Knowledge Graphs via Incremental Reasoning

arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis

PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation

arXiv:2609.02860v1 Announce Type: new Abstract: Modern crop breeding demands precise organ-level analysis for trait quantification, making plant point cloud segmentation (PPCS) increasingly important.

Plenoptic Condensation: A Novel Approach to Generalized Scene Reconstruction

arXiv:2607.18151v2 Announce Type: replace Abstract: We present a novel Generalized Scene Reconstruction (GSR) approach called Plenoptic Condensation (PCon). PCon uses a multi-stage reconstruction pipe

Poisoning Attacks on the PGM-index

arXiv:2609.02328v1 Announce Type: cross Abstract: The PGM-index (Ferragina and Vinciguerra, VLDB'20) is one of the most practical learned indexes, owing to its theoretical elegance and consistently st

PolERo: Studying Political Evasion in Romanian

arXiv:2609.02391v1 Announce Type: cross Abstract: Political evasion refers to responses that engage with a question while withholding the requested information. Recent NLP work frames political evasio

Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling

arXiv:2609.01999v1 Announce Type: cross Abstract: We study a variant of the Thompson Sampling (TS) algorithm, called alpha-TS, for solving stochastic generalized linear bandit problems. Existing analy

Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

arXiv:2609.02108v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to the auto-regressive paradigm. With bidirectional attention and any-order g

Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language

arXiv:2609.02606v1 Announce Type: new Abstract: Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objec

Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture

arXiv:2609.01667v1 Announce Type: cross Abstract: Artificial Intelligence has shown to help improve agricultural practices, yet adoption remains limited: 69% of U.S. farmers have privacy concerns with

ProbeMatchDTI: Probe-Driven Multi-Scale Biochemical Pattern Matching for Drug-Target Interaction Prediction

arXiv:2609.02549v1 Announce Type: cross Abstract: Drug-target interaction (DTI) prediction is an important task in AI-driven drug discovery. Although recent biochemical representation learning methods

Quantum Speedups for Sampling and Non-convex Optimization with Stochastic Oracles

arXiv:2504.03626v2 Announce Type: replace-cross Abstract: We present quantum speedups for sampling from distributions of the form pipropto e^{-f} on R^d. We consider two stochastic oracle models: a st

Recursive Value Learning for Long-Horizon Offline Goal-Conditioned RL

arXiv:2609.02237v1 Announce Type: new Abstract: Scaling offline goal-conditioned reinforcement learning (GCRL) to long-horizon tasks is difficult because (1) long-range value learning depends on short

Refining Heuristic-Based Bitcoin Address Clustering with Graph Neural Networks

arXiv:2609.01942v1 Announce Type: new Abstract: Bitcoin's pseudonymous nature makes it challenging to analyze user-level activity, since a single user may control multiple identifiers (addresses). Exi

Retrosynthesis of Synthetic Media for Explainable AI Provenance Forensics

arXiv:2609.02268v1 Announce Type: cross Abstract: With the rapid proliferation of generative models on Machine Learning as a Service (MLaaS) platforms, reliably tracing the provenance of synthetic med

Reviewing the Reviewer: LLM-Assisted Reviewer Feedback Generation for Guideline Compliance

arXiv:2602.10118v2 Announce Type: replace Abstract: Peer review is central to scientific quality, yet reliance on simple heuristics, namely lazy thinking and non-specific critiques, has threatened rev

RoGe: Novel View Synthesis via End-to-End Implicit Reconstruction and Generation

arXiv:2609.02847v1 Announce Type: new Abstract: Novel view synthesis from sparse inputs requires both geometric grounding from the observed views and generative priors of unobserved regions, motivatin

SAUF-Net: Structure--Appearance Representation Learning with Uncertainty Feedback for Semi-Supervised Medical Image Segmentation

arXiv:2609.02247v1 Announce Type: cross Abstract: Semi-supervised learning has shown great potential for reducing annotation costs in medical image segmentation. However, most existing methods mainly

Schrodinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation

arXiv:2609.02196v1 Announce Type: cross Abstract: Generative modeling directly on geometric manifolds can avoid errors introduced by flattening non-Euclidean data, repeated ambient projection, and coo

Secure AI-Driven Super-Resolution for Real-Time Mixed Reality Applications

arXiv:2512.15823v3 Announce Type: replace-cross Abstract: Immersive formats such as 360{eg} and 6DoF point cloud videos require high bandwidth and low latency, posing challenges for real-time AR/VR st

SelfMOTR: Revisiting MOTR with Self-Generating Detection Priors

arXiv:2511.20279v3 Announce Type: replace Abstract: End-to-end transformer architectures have driven significant progress in multi-object tracking by unifying detection and association into a single,

Simulating Classification Models for Ex-Ante Evaluation of Predict-Then-Optimize Methods

arXiv:2509.02191v3 Announce Type: replace Abstract: Predict-Then-Optimize combines machine learning predictions with downstream optimization to support decision-making when problem parameters are unkn

SkillGLoW: Procedural-Family Skill Consolidation for Self-Improving Agents on Long-Horizon Task Streams

arXiv:2609.02217v1 Announce Type: new Abstract: LLM agents increasingly self-improve by writing and reusing textual skills, kept either as one global document or as a flat pool of per-task entries, th

SonicCaps: Large-Scale Diverse and Fine-Grained Captioning for Improved Audio-Retrieval

arXiv:2609.02343v1 Announce Type: cross Abstract: Recent advances in audio-language modeling have been driven by large-scale audio captioning datasets. However, existing datasets remain limited by low