Search: “research”

Online Quantile Regression for Nonparametric Additive Models

arXiv:2604.08969v1 Announce Type: cross Abstract: This paper introduces a projected functional gradient descent algorithm (P-FGD) for training nonparametric additive quantile regression models in onli

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Optimal Multi-bit Generative Watermarking Schemes Under Worst-Case False-Alarm Constraints

DGX agent

arXiv:2604.08759v1 Announce Type: cross Abstract: This paper considers the problem of multi-bit generative watermarking for large language models under a worst-case false-alarm constraint. Prior work

researcharxiv-cs-cl

13 Apr 2026

Out-of-the-box: Black-box Causal Attacks on Object Detectors

arXiv:2512.03730v2 Announce Type: replace-cross Abstract: Adversarial perturbations are a useful way to expose vulnerabilities in object detectors. Existing perturbation methods are frequently white-b

p1: Better Prompt Optimization with Fewer Prompts

arXiv:2604.08801v1 Announce Type: cross Abstract: Prompt optimization improves language models without updating their weights by searching for a better system prompt, but its effectiveness varies wide

P3P Made Easy

arXiv:2508.01312v4 Announce Type: replace Abstract: We revisit the classical Perspective-Three-Point (P3P) problem, which aims to recover the absolute pose of a calibrated camera from three 2D-3D corr

PaceLLM: Brain-Inspired Large Language Models for Long-Context Understanding

arXiv:2506.17310v3 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) demonstrate strong performance across domains, their long-context capabilities are limited by transient neu

PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics

arXiv:2604.09058v1 Announce Type: cross Abstract: Long-horizon spatiotemporal prediction remains a challenging problem due to cumulative errors, noise amplification, and the lack of physical consisten

Physics-guided surrogate learning enables zero-shot control of turbulent wings

arXiv:2604.09434v1 Announce Type: cross Abstract: Turbulent boundary layers over aerodynamic surfaces are a major source of aircraft drag, yet their control remains challenging due to multiscale dynam

PoseGen: In-Context LoRA Finetuning for Pose-Controllable Long Human Video Generation

arXiv:2508.05091v2 Announce Type: replace Abstract: Generating temporally coherent, long-duration videos with precise control over subject identity and movement remains a fundamental challenge for con

Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing

arXiv:2604.08624v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are naturally suited for speech processing tasks due to their specific dynamics, which allows them to handle temporal d

PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images

arXiv:2511.20068v2 Announce Type: replace Abstract: Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large l

PRAGMA: Revolut Foundation Model

arXiv:2604.08649v1 Announce Type: cross Abstract: Modern financial systems generate vast quantities of transactional and event-level data that encode rich economic signals. This paper presents PRAGMA,

Predictive Entropy Links Calibration and Paraphrase Sensitivity in Medical Vision-Language Models

arXiv:2604.08941v1 Announce Type: new Abstract: Medical Vision Language Models VLMs suffer from two failure modes that threaten safe deployment mis calibrated confidence and sensitivity to question re

Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction

arXiv:2604.09123v1 Announce Type: new Abstract: Aspect Sentiment Triplet Extraction (ASTE) aims to extract all sentiment triplets of aspect terms, opinion terms, and sentiment polarities from a senten

PS-TTS: Phonetic Synchronization in Text-to-Speech for Achieving Natural Automated Dubbing

arXiv:2604.09111v1 Announce Type: cross Abstract: Recently, artificial intelligence-based dubbing technology has advanced, enabling automated dubbing (AD) to convert the source speech of a video into

PSIRNet: Deep Learning-based Free-breathing Rapid Acquisition Late Enhancement Imaging

arXiv:2604.08781v1 Announce Type: cross Abstract: Purpose: To develop and evaluate a deep learning (DL) method for free-breathing phase-sensitive inversion recovery (PSIR) late gadolinium enhancement

RAM: Recover Any 3D Human Motion in-the-Wild

arXiv:2603.19929v2 Announce Type: replace-cross Abstract: RAM incorporates a motion-aware semantic tracker with adaptive Kalman filtering to achieve robust identity association under severe occlusions

Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection

arXiv:2604.08572v1 Announce Type: cross Abstract: State-of-the-art post-hoc out-of-distribution detection methods rely on intermediate layer activation editing. However, they exhibit inconsistent perf

Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories

arXiv:2604.09429v1 Announce Type: cross Abstract: Recovering camera parameters from images and rendering scenes from novel viewpoints have long been treated as separate tasks in computer vision and gr

Reasoning Models Will Sometimes Lie About Their Reasoning

arXiv:2601.07663v3 Announce Type: replace Abstract: Hint-based faithfulness evaluations have established that Large Reasoning Models (LRMs) may not say what they think: they do not always volunteer in

RecaLLM: Addressing the Lost-in-Thought Phenomenon with Explicit In-Context Retrieval

arXiv:2604.09494v1 Announce Type: cross Abstract: We propose RecaLLM, a set of reasoning language models post-trained to make effective use of long-context information. In-context retrieval, which ide

Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA

arXiv:2604.09019v1 Announce Type: cross Abstract: Two-hop QA retrieval splits queries into two regimes determined by whether the hop-2 entity is explicitly named in the question (Q-dominant) or only i

Model Releases

ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences

model-releasesarxiv-cs-ai

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

Reservoir observer enhanced with residual calibration and attention mechanism

arXiv:2604.08592v1 Announce Type: new Abstract: Reservoir observers provide a data-driven approach to the inference of unmeasured variables from observed ones for nonlinear dynamical systems. While pr

Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective

arXiv:2604.08880v1 Announce Type: cross Abstract: Chain-of-thought (CoT) distillation transfers reasoning behaviors from a strong teacher to a smaller student, but prior work reports a capacity gap: d

Sample Complexity of Composite Quantum Hypothesis Testing

arXiv:2601.08588v4 Announce Type: replace-cross Abstract: This paper investigates symmetric composite binary quantum hypothesis testing (QHT), where the goal is to determine which of two uncertainty s

Scaling flow-based approaches for topology sampling in SU(3) gauge theory

arXiv:2510.25704v2 Announce Type: replace-cross Abstract: We develop a methodology based on out-of-equilibrium simulations to mitigate topological freezing when approaching the continuum limit of latt

Safety

Scheming in the wild: detecting real-world AI scheming incidents with open-source intelligence

arXiv:2604.09104v1 Announce Type: cross Abstract: Scheming, the covert pursuit of misaligned goals by AI systems, represents a potentially catastrophic risk, yet scheming research suffers from signifi

safetyarxiv-cs-ai

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

arXiv:2601.22160v2 Announce Type: replace-cross Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies

Self-Supervised Slice-to-Volume Reconstruction with Gaussian Representations for Fetal MRI

arXiv:2601.22990v2 Announce Type: replace-cross Abstract: Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume r

Sharp description of local minima in the loss landscape of high-dimensional two-layer ReLU neural networks

arXiv:2604.09412v1 Announce Type: cross Abstract: We study the population loss landscape of two-layer ReLU networks of the form sum_{k=1}^K ReLU(w_k^op x) in a realisable teacher-student setting with

SIC3D: Style Image Conditioned Text-to-3D Gaussian Splatting Generation

arXiv:2604.08760v1 Announce Type: new Abstract: Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differe

Silhouette Loss: Differentiable Global Structure Learning for Deep Representations

arXiv:2604.08573v1 Announce Type: cross Abstract: Learning discriminative representations is a central goal of supervised deep learning. While cross-entropy (CE) remains the dominant objective for cla

Simulation of Adaptive Running with Flexible Sports Prosthesis using Reinforcement Learning of Hybrid-link System

arXiv:2604.08882v1 Announce Type: new Abstract: This study proposes a reinforcement learning-based adaptive running motion simulation for a unilateral transtibial amputee with the flexibility of a lea

researcharxiv-cs-ro

Soft Electroadhesive Feet for Micro Aerial Robots Perching on Smooth and Curved Surfaces

arXiv:2604.09270v1 Announce Type: new Abstract: Electroadhesion (EA) provides electrically switchable adhesion and is a promising mechanism for perching micro aerial robots on smooth surfaces. However

researcharxiv-cs-ro

State Space Models are Effective Sign Language Learners: Exploiting Phonological Compositionality for Vocabulary-Scale Recognition

arXiv:2604.08761v1 Announce Type: new Abstract: Sign language recognition suffers from catastrophic scaling failure: models achieving high accuracy on small vocabularies collapse at realistic sizes. E

Stochastic-Dimension Frozen Sampled Neural Network for High-Dimensional Gross-Pitaevskii Equations on Unbounded Domains

arXiv:2604.09361v1 Announce Type: new Abstract: In this paper, we propose a stochastic-dimension frozen sampled neural network (SD-FSNN) for solving a class of high-dimensional Gross-Pitaevskii equati

Streaming Video Instruction Tuning

arXiv:2512.21334v2 Announce Type: replace Abstract: We present Streamo, a real-time streaming video LLM that serves as a general-purpose interactive assistant. Unlike existing online video models that

Strips as Tokens: Artist Mesh Generation with Native UV Segmentation

arXiv:2604.09132v1 Announce Type: new Abstract: Recent advancements in autoregressive transformers have demonstrated remarkable potential for generating artist-quality meshes. However, the token order

Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis

arXiv:2604.08809v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) represent visual content as structured, editable code. Each element (path, shape, or text node) can be individually inspe

Structure-Aware Fine-Grained Gaussian Splatting for Expressive Avatar Reconstruction

arXiv:2604.09324v1 Announce Type: new Abstract: Reconstructing photorealistic and topology-aware human avatars from monocular videos remains a significant challenge in the fields of computer vision an

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions

arXiv:2604.08477v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has significantly improved large language model (LLM) reasoning in formal domains such as mathem

Task-Aware LLM Routing with Multi-Level Task-Profile-Guided Data Synthesis for Cold-Start Scenarios

arXiv:2604.09377v1 Announce Type: new Abstract: Large language models (LLMs) exhibit substantial variability in performance and computational cost across tasks and queries, motivating routing systems

Task Vectors, Learned Not Extracted: Performance Gains and Mechanistic Insight

arXiv:2509.24169v2 Announce Type: replace Abstract: Large Language Models (LLMs) can perform new tasks from in-context demonstrations, a phenomenon known as in-context learning (ICL). Recent work sugg

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy

arXiv:2312.09436v3 Announce Type: replace-cross Abstract: The recent development of connected and automated vehicle (CAV) technologies has spurred investigations to optimize dense urban traffic to max

Testing the Assumptions of Active Learning for Translation Tasks with Few Samples

arXiv:2604.08977v1 Announce Type: new Abstract: Active learning (AL) is a training paradigm for selecting unlabeled samples for annotation to improve model performance on a test set, which is useful w

The Fast Lane Hypothesis: Von Economo Neurons Implement a Biological Speed-Accuracy Tradeoff

arXiv:2604.09229v1 Announce Type: cross Abstract: Von Economo neurons (VENs) are large bipolar projection neurons found exclusively in the anterior cingulate cortex (ACC) and frontal insula of species