Search: “research”

Programming over Thinking: Efficient and Robust Multi-Constraint Planning

arXiv:2601.09097v3 Announce Type: replace Abstract: Multi-constraint planning involves identifying, evaluating, and refining candidate plans while satisfying multiple, potentially conflicting constrai

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Research

Progressive Refinement: An Iterative Pseudo-Labeling Approach for Mandarin-English Code-Switching ASR

DGX agent

arXiv:2607.05224v1 Announce Type: new Abstract: Code-switching (CS), alternating languages within the same utterance, poses significant challenges for automatic speech recognition (ASR) due to limited

researcharxiv-cs-cl

7 Jul 2026

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space

arXiv:2607.02907v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but still struggle with complex visual reasoning tasks requiring multi-step

Property-Constrained 3D Porous Media Reconstruction from 2D Images via Conditional Generative Adversarial Networks

arXiv:2607.02693v1 Announce Type: new Abstract: This study presents a conditional Generative Adversarial Network (cGAN) framework for generating 3D porous media volumes with controlled porosity, train

ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions

arXiv:2607.05276v1 Announce Type: cross Abstract: Speaker embeddings, or x-vectors, are widely used to represent speaker identity and speaker-related attributes, but existing embedding extractors are

Provable Pruning for Efficient 3D Gaussian Splatting via Coresets

arXiv:2607.02721v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis, but practical scenes often contain millions of Gaussians, making compr

psytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysis

arXiv:2607.03003v1 Announce Type: new Abstract: Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In th

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference

arXiv:2511.04805v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models have shown strong potential in scaling language models efficiently by activating only a small subset of expert

Q-TriM: Question-Guided Tri-Modal Attention for Audio-Visual Question Answering

arXiv:2607.03825v1 Announce Type: cross Abstract: Audio-Visual Question Answering (AVQA) extends classical VQA by requiring joint reasoning over video and synchronized audio. However, many AVQA system

Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control

arXiv:2607.04978v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) underpin a growing family of latent world models for control from raw pixels, but every existing JEPA

Model Releases

QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs

model-releasesarxiv-cs-lg

arXiv:2602.20629v3 Announce Type: replace Abstract: As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated ev

Quadrature-Aware Complex-Linear Neural Operator for Boundary-to-Field Prediction in Resonant Acoustics

arXiv:2607.04407v1 Announce Type: cross Abstract: Repeated prediction of acoustic fields from spatially distributed boundary excitation is computationally expensive when each source realization requir

Quantum Kolmogorov--Arnold representation theorem for continuous unitary-valued maps

arXiv:2607.03187v1 Announce Type: cross Abstract: The classical Kolmogorov--Arnold representation theorem states that any continuous multivariate function can be exactly decomposed into a finite compo

Quantum Spectral Anomaly Detection

arXiv:2607.05307v1 Announce Type: cross Abstract: A core task in quantum anomaly detection is to compute an anomaly score that quantifies how strongly a test quantum state deviates from a given quantu

Quick ViTs: Speeding up Vision Transformers through Equivariance

arXiv:2505.15441v5 Announce Type: replace-cross Abstract: Natural images exhibit strong geometric regularities: local structures, such as edges, corners, and textures, appear in many orientations and

Quickest Detection of Hallucination Onset: Delay Bounds and Learned CUSUM Statistics

arXiv:2606.12476v3 Announce Type: replace-cross Abstract: Token-level hallucination detectors are evaluated as classifiers, by AUC over all tokens, yet a streaming monitor is judged by its reaction ti

Rank-Order N-of-M Codes for Sparse Distributed Memory: Disentangling Representation and Learning Effects in Noise Robustness Against Contemporary Neuromorphic Architectures

arXiv:2607.02967v1 Announce Type: new Abstract: Large language models remain limited as continual learning systems, motivating renewed interest in Sparse Distributed Memory (SDM) as an explicit online

Rating the Pitch, Not the Product: User Evaluations of LLMs Reflect Expectations More Than Performance

arXiv:2607.05113v1 Announce Type: new Abstract: Imagine two users interact with the same LLM. One has been told it is the cutting-edge flagship model; the other, an older, weaker model. They walk away

Real-Time LiDAR Gaussian Splatting SLAM

arXiv:2607.04127v1 Announce Type: new Abstract: We present a real-time LiDAR-based framework for Gaussian Splatting SLAM that tightly couples fast G-ICP registration with spherical rasterization-based

Reconstructing Rational Functions on Finite Abelian Groups with Higher Autocorrelations

arXiv:2503.21022v2 Announce Type: replace Abstract: The higher-order autocorrelations of integer-valued or rational-valued functions on finite Abelian groups appear naturally in X-ray crystallography,

Recursive Entropic Variational Inference for Nonlinear State-Space Models

arXiv:2511.15409v2 Announce Type: replace Abstract: We present a class of algorithms for state estimation in nonlinear, non-Gaussian state-space models. Our approach is based on a variational Lagrangi

Reflected Schrodinger Bridge Matching

arXiv:2607.03626v1 Announce Type: new Abstract: Recent advances in generative modeling have enabled the efficient computation of Schrodinger bridges (SB) in high-dimensional settings by leveraging par

Reliability-Aware Monocular Depth Supervision for Sparse-View Neural Reconstruction

arXiv:2607.02554v1 Announce Type: new Abstract: Sparse-view neural reconstruction is challenging in outdoor driving scenes, where cameras usually move along a narrow forward-facing trajectory and prov

Representation Recycling for Streaming Video Analysis

arXiv:2204.13492v5 Announce Type: replace Abstract: We present StreamDEQ, a method that aims to infer frame-wise representations on videos with minimal per-frame computation. Conventional deep network

Representing and Detecting Label Ambiguity in IMU-Based Exercise Evaluation

arXiv:2607.04842v1 Announce Type: new Abstract: Home-based physiotherapy is performed without supervision, which leads to incorrect execution and motivates systems that assess movement automatically f

Repurposing CLIP to Localize at Pixel Level

arXiv:2607.05253v1 Announce Type: new Abstract: Large-scale Vision-Language Models like CLIP have demonstrated impressive open-set localization capabilities at the image level. However, adapting this

Restricted Bernoulli Matrix Factorization: Balancing the trade-off between prediction accuracy and coverage in classification based collaborative filtering

arXiv:2210.10619v3 Announce Type: replace-cross Abstract: Reliability measures associated with the prediction of the machine learning models are critical to strengthening user confidence in artificial

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective

arXiv:2607.03784v1 Announce Type: cross Abstract: While prior studies have successfully compressed vision Transformers (ViTs) through various pruning techniques, most have concentrated on width prunin

Rethinking Neural Nonlinearity as Gating

arXiv:2607.03148v1 Announce Type: cross Abstract: Activation functions are considered an essential primitive for neural nonlinearity, i.e., they enable neural networks to serve as universal approximat

Robust Bayes-Assisted Conformal Prediction

arXiv:2607.04236v1 Announce Type: cross Abstract: Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Althou

RotateAttention: RoPE-Aware Rotation and Range Rectification for INT4 Quantized Attention in Video Generation

arXiv:2607.02584v1 Announce Type: new Abstract: In extbf{DiT-based video generation models equipped with 3D Rotary Position Embeddings (3D RoPE)}, the attention mechanism remains a primary computation

Routing Anonymity and Identifiability of Noisy Quantum Hardware

arXiv:2607.05281v1 Announce Type: cross Abstract: Present-day quantum computing is cloud-based, where a user submits a circuit to a service provider's proprietary backend hardware. While providers may

RSTNet: Enhancing Small-Target Recognition in Noisy SAR Imagery via Robust Feature Learning and Distribution-Aware Regression

arXiv:2602.23820v2 Announce Type: replace Abstract: SAR supports all-day-and-night oceanic observation, yet vessel identification from SAR images is hampered by speckle noise, intricate land-sea backg

RUFNet: Query-Guided Support Mask Refinement and Uncertainty Fusion based on Hybrid Mamba for Few-Shot Brain Tumor Segmentation

arXiv:2607.05035v1 Announce Type: cross Abstract: Few-shot brain tumor segmentation remains challenging due to noisy support masks, inter-patient variations between support and query images, and the l

S-DiverSe: Spanish Diverse Speech

arXiv:2607.03207v1 Announce Type: new Abstract: Automatic speech recognition (ASR) has advanced remarkably for standard speech, yet speech affected by neurological conditions remains a challenge. We p

SA-ResGS: Self-Augmented Residual 3D Gaussian Splatting for Next Best View Selection

arXiv:2601.03024v3 Announce Type: replace Abstract: We propose Self-Augmented Residual 3D Gaussian Splatting (SA-ResGS), a novel framework to stabilize uncertainty quantification and enhancing uncerta

SAF3R: Dynamic Sparse Attention for Feed-Forward 3D Reconstruction Transformers

arXiv:2607.03612v1 Announce Type: new Abstract: Feed-forward 3D reconstruction (F3R) transformers have recently achieved remarkable success. However, scaling them to long image sequences remains chall

Sangam: Efficiently Serving Diffusion LLMs with the AR Stack

arXiv:2607.04206v1 Announce Type: cross Abstract: Diffusion language models (dLLMs) generate text by iteratively denoising a masked response and can commit multiple output positions per model invocati

SAVER: Stochastic Adaptive Variance-Driven Exploration and Reconstruction for Low-Dose Computed Tomography

arXiv:2607.03761v1 Announce Type: new Abstract: Computed Tomography (CT) is indispensable in clinical diagnostics, yet minimizing radiation dose without compromising image quality remains a critical c

Scalable Cross-Attention Transformer for Cooperative Multi-AP OFDM Uplink Reception

arXiv:2602.04728v3 Announce Type: replace-cross Abstract: We propose a cross-attention Transformer for joint decoding of uplink OFDM signals received by multiple coordinated access points. A shared pe

Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes

arXiv:2607.03392v1 Announce Type: cross Abstract: The ever-increasing collection of personal data has created mounting pressure to develop technologies that protect sensitive aspects of individual ide

Scalable Maximal Frequent Episode Mining with Desbordante

arXiv:2607.03188v1 Announce Type: cross Abstract: Episode mining aims to extract subsequences of events that possess certain distinctive properties and constitute facts valuable to the user. Maximal f

Score Distributions, Not Cells: Evaluating Single-Cell Perturbations Under Class Overlap

arXiv:2607.04595v1 Announce Type: new Abstract: Most classification problems assume the classes are roughly separable, so that an individual sample can usually be assigned to one class. Single-cell pe

Score-Regularized Joint Sampling with Importance Weights for Flow Matching

arXiv:2511.17812v3 Announce Type: replace-cross Abstract: Flow matching models effectively represent complex distributions, yet estimating expectations of functions of their outputs remains challengin

See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition

arXiv:2607.02912v1 Announce Type: new Abstract: Despite the high accuracy of EEG-based emotion recognition, existing models remain opaque 'black boxes', lacking semantic grounding between abstract neu

Seeing Once is Enough? Online Geometry-Aware Token Pruning for 3D Question Answering

arXiv:2607.04079v1 Announce Type: cross Abstract: Recent Multi-modal Large Language Models (MLLMs) have demonstrated remarkable performance on 2D question answering tasks. However, extending these mod

SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering

arXiv:2607.04163v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual understanding tasks such as image captioning and visual question answ

Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration

arXiv:2606.12913v2 Announce Type: replace-cross Abstract: The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which ret