Search: “research”

DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data

arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics

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Dual-Form ASR: Semantics-Aware Inverse Text Normalization for Chinese Speech Recognition

DGX agent

arXiv:2609.02901v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) scenarios require both spoken-form transcripts for faithful transcription and readable written-form transcript

researcharxiv-cs-cl

4 Sept 2026

Efficient Semantic Understanding from Digital Foveation

arXiv:2609.04088v1 Announce Type: new Abstract: Dense semantic segmentation allocates computational resources uniformly across the entire image, regardless of scene complexity or task relevance. Inspi

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

arXiv:2609.03756v1 Announce Type: cross Abstract: We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the l

Establishing a Dynamic Multimodal HRI Dataset for Engagement Analysis with a Humanoid Robot

arXiv:2609.03255v1 Announce Type: new Abstract: This paper presents an experimental design for constructing a multimodal dataset to analyze user engagement in human-robot interaction (HRI). Prior stud

researcharxiv-cs-ro

Tools

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published rese…

Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind thos

toolsperplexity--x

Ex-Omni: Enabling 3D Facial Animation Generation for Omni-modal Large Language Models

arXiv:2602.07106v3 Announce Type: replace-cross Abstract: Omni-modal large language models (OLLMs) aim to unify multimodal understanding and generation, yet extending them to jointly produce speech an

Exemplar: Classical Priors Complement Frozen Features for Few-Shot Microscopy Segmentation at Native Resolution

arXiv:2609.03080v1 Announce Type: new Abstract: Segmenting a new biomedical dataset usually means a domain-specific model trained on substantial annotation, or a foundation model steered at inference

Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus Images

arXiv:2405.07338v2 Announce Type: replace-cross Abstract: Early detection of vision-threatening conditions such as diabetic retinopathy, glaucoma, and age-related macular degeneration depends on retin

F4Splat: Feed-Forward Predictive Densification for Feed-Forward 3D Gaussian Splatting

arXiv:2603.21304v3 Announce Type: replace Abstract: Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-G

Feasible but Not Safe: Constraint Violations and Report-Channel Attacks in Learned Cell-Free ISAC Association

arXiv:2609.03147v1 Announce Type: cross Abstract: Learning-based schedulers have been proposed to provide real-time user, target, and access point (AP) association in distributed cell-free integrated

Feature Reconfiguration With Visual Prior for Medical Lesion Segmentation

arXiv:2609.03535v1 Announce Type: new Abstract: Lesion segmentation in medical images plays a critical role in clinical diagnosis and treatment planning. Despite significant advances, lesion segmentat

Federated Causal Discovery via Regression-Directed Cumulants

arXiv:2609.03705v1 Announce Type: new Abstract: In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Marko

Finite-Time Convergence of Single-Trajectory Chi-Square Robust Q-Learning With Linear Function Approximation

arXiv:2510.01721v4 Announce Type: replace Abstract: Distributionally robust reinforcement learning seeks policies that remain effective when the deployment environment differs from the one that genera

FoRIS: Progressive Foreground Refinement for Training-Free In-Context Segmentation

arXiv:2609.03384v1 Announce Type: new Abstract: In-Context Segmentation (ICS) aims to precisely segment arbitrary semantic concepts, such as objects or parts, given one or a few annotated visual exemp

FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions

arXiv:2609.02948v1 Announce Type: cross Abstract: Predicting the thermodynamic properties of an alloy requires sampling its configurations across many chemical conditions and recovering free energies

From Ordered Bernoulli Levels to Critical-Line Geometry: Integer Quantization, Bernoulli Residual Phase, and Prime-Power Spectra

arXiv:2609.03801v1 Announce Type: new Abstract: We study the ordered Bernoulli-word kernel f(p,n,k)=p^k(1-p)^(n-k) and the geometry generated by its inverse-integer level sets. The binary level 2^(-n)

Frontier LLMs are effective batch optimizers: Assessing reasoning models in continuous and discrete settings

arXiv:2609.03177v1 Announce Type: new Abstract: Frontier large language models (LLMs) have become attractive priors for optimization due to their large-scale pretraining that enables them to navigate

Geometry-Aware Graph Construction via Adaptive Spectral Bandwidth Control

arXiv:2609.03306v1 Announce Type: new Abstract: Kernelized graph methods - spectral clustering, diffusion maps, and sparse kernel -regression graphs - that use Gaussian kernels depend on the choice of

GraFT: A Training-Free Framework for Spatial Reasoning in Multimodal Large Language Models via 3D Scene Graphs

arXiv:2609.03892v1 Announce Type: cross Abstract: 3D spatial reasoning underpins understanding and acting in the physical world, yet it remains unreliable in current multimodal large language models (

Grammar-Aligned Decoding

arXiv:2405.21047v4 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code, mathematical formulas, or well-forme

GrowPage: On-Demand KV Budgeting for Efficient LLM Reasoning Serving

arXiv:2609.03494v1 Announce Type: new Abstract: Long-output reasoning has made the key--value (KV) cache a critical memory bottleneck for efficient LLM serving. Existing KV compression methods usually

Imagination Helps Visual Reasoning, But Not Yet in Latent Space

arXiv:2602.22766v3 Announce Type: replace Abstract: Latent visual reasoning aims to mimic human's imagination process by meditating through hidden states of Multimodal Large Language Models. While rec

Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial

arXiv:2609.03186v1 Announce Type: cross Abstract: Training deep learning-based medical image segmentation models is challenging with limited curated datasets. For AGITG TOPGEAR, a gastric cancer trial

Improving precipitation forecasts in an AI weather model using observational data

arXiv:2609.03210v1 Announce Type: cross Abstract: Artificial intelligence weather prediction (AIWP) systems now surpass state-of-the-art physical models for medium-range weather forecasting. Current g

Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach

arXiv:2609.04028v1 Announce Type: cross Abstract: The geometric morphology of deposited filaments can significantly influence the structural performance and stability of 3D concrete-printed (3DCP) str

Instruction Duplication as an Inference-Time Control Primitive

arXiv:2609.04024v1 Announce Type: new Abstract: Procedural instruction following is a basic requirement for controllable language-model systems, especially when generated trajectories are inspected or

Applications

ISP-AD: A Large-Scale Real-World Dataset for Advancing Industrial Anomaly Detection with Synthetic and Real Defects

arXiv:2503.04997v4 Announce Type: replace Abstract: Automatic visual inspection using machine learning plays a key role in achieving zero-defect policies in industry. Research on anomaly detection is

applicationsarxiv-cs-cv

Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation

arXiv:2609.02942v1 Announce Type: cross Abstract: LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candida

K-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFs

arXiv:2607.14415v2 Announce Type: replace Abstract: Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representatio

Kernel Reboot: Breaking the Boundaries of Neural Tangent Kernels for Neural Fields

arXiv:2609.03117v1 Announce Type: cross Abstract: Neural fields (NFs) map continuous coordinates to signals such as color or density, but fast high-quality reconstruction from sparse observations rema

KnowVis: Knowledge-Centric Visual Summarization for Video Lectures

arXiv:2609.03742v1 Announce Type: cross Abstract: Video lectures are valuable educational resources, but their dense and lengthy formats often overwhelm novice learners. This difficulty stems from a f

Landmark-Based Discrimination of Injury-Associated Athlete-Sessions from Minute-Resolution Multimodal Football Monitoring Data

arXiv:2609.03790v1 Announce Type: new Abstract: Athlete monitoring data may be recorded minute by minute throughout a match or training session, while injury information may only indicate whether the

Language-encoded network topology enables large language models to reason about complex networks

arXiv:2609.03229v1 Announce Type: new Abstract: Networks describe systems in biology and beyond, from protein interactions and social relationships to power grids and citation records. Reasoning about

Language, Language Models, and What We're Talking About

arXiv:2609.03577v1 Announce Type: new Abstract: Language models are commonly discussed as technical artefacts, but they are obviously shaped by the linguistic worlds conveyed by data during their trai

Laplacian Frequency Hierarchies for Efficient 3D Gaussian Splatting Training

arXiv:2609.03334v1 Announce Type: new Abstract: A key bottleneck in 3D Gaussian Splatting training is the continual growth of Gaussian primitives, which increases optimization cost and slows convergen

Learnable composition for neural operators

arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating

Learning Informative Prior with Infinite-Dimensional Continuous Normalizing Flow for Bayesian Inverse Problem

arXiv:2609.03343v1 Announce Type: cross Abstract: This paper addresses infinite-dimensional Bayesian inference for inverse problem of partial differential equations with model parameters in infinite-d

Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning

arXiv:2609.04194v1 Announce Type: new Abstract: Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats the

Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories

arXiv:2602.15154v2 Announce Type: replace Abstract: Reliable video understanding requires high-quality video datasets that can provide both precise semantic labels and temporally consistent annotation

Masked Autoregressive Speech Enhancement with Continuous Neural Audio Codec Representations

arXiv:2609.03940v1 Announce Type: cross Abstract: Most previous work on speech enhancement (SE) based on masked generative modeling relied on discrete token representations of audio signals, obtained

MemoryLACE: Memory Lifecycle-Aware Consolidation and Evidence Retrieval

arXiv:2609.03201v1 Announce Type: new Abstract: Long-term LLM agents must preserve information across interactions while distinguishing repeated evidence, historical states, updates, and unresolved co

Mixed Data Clustering Survey and Challenges

arXiv:2512.03070v2 Announce Type: replace-cross Abstract: The advent of the big data paradigm has transformed how industries manage and analyze information, ushering in an era of unprecedented data vo

Modern Transformers Are Implicit Hybrids: From Functional Differentiation to Principled Hybrid Architecture Design

arXiv:2609.02986v1 Announce Type: new Abstract: Hybrid architectures combining Full Attention (FA) and Linear Attention (LA) are increasingly prominent, yet their allocation remains heuristic. We seek

MoMaStage: Skill-State Graph Guided Planning and Closed-Loop Execution for Long-Horizon Indoor Mobile Manipulation

arXiv:2603.08383v2 Announce Type: replace Abstract: Long-horizon indoor mobile manipulation (MoMa) requires robots to execute extended navigation-manipulation sequences whose feasibility depends on st

researcharxiv-cs-ro

Neural-Network Maxent: a general extension with learned nonlinearity, applied to time-series for Desert Locust distribution modelling

arXiv:2609.03603v1 Announce Type: new Abstract: Species Distribution Modelling (SDM) is essential for understanding how environmental conditions shape biodiversity, particularly for destructive pests

Observation-Conditioned Latent Energy Priors for Sparse Implicit Neural Shape Completion

arXiv:2609.03694v1 Announce Type: new Abstract: Implicit neural representations (INRs) can model continuous 3D shapes with a shared coordinate decoder and per-instance latent codes. At test time, auto

Occlusion-Robust Multimodal Emotion Recognition in VR via Fusion of Facial Images and EMG

arXiv:2609.03569v1 Announce Type: new Abstract: Head-mounted displays (HMDs) fundamentally limit emotion recognition in virtual reality (VR): by occluding the upper face, they render conventional imag