Search: “research”

Real Time NILM Based Power Monitoring of Identical Induction Motors Representing Cutting Machines in Textile Industry

arXiv:2601.01616v2 Announce Type: replace Abstract: The textile industry in Bangladesh is one of the most energy-intensive sectors, yet its monitoring practices remain largely outdated, resulting in i

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Research

Realizing Robotic Swimming with Unified Fluid-Robot Multiphysics

DGX agent

arXiv:2506.05012v2 Announce Type: replace Abstract: Matching the swimming efficiency and agility of fish has remained an elusive goal in underwater robotics. Such locomotion capabilities rely on compl

researcharxiv-cs-ro

28 May 2026

RelaxFlow: Text-Driven Amodal 3D Generation

arXiv:2603.05425v2 Announce Type: replace-cross Abstract: Image-to-3D generation faces inherent semantic ambiguity under occlusion, where partial observation alone is often insufficient to determine o

Residualized Temporal Sparse Autoencoders for Interpreting Diffusion Models

arXiv:2605.27813v1 Announce Type: cross Abstract: Text-to-image diffusion models generate images through an iterative denoising process, so internal neural layers produce trajectories of activations r

Rethinking Calibration for Early-Exit Neural Networks

arXiv:2508.21495v3 Announce Type: replace Abstract: Early-exit neural networks (EENNs) accelerate inference by allowing intermediate classifiers to stop computation once predictions are confident enou

Rethinking Visual Neglect: Steering via Context-Preference for MLLM Hallucination Mitigation

arXiv:2605.27993v1 Announce Type: new Abstract: Object hallucination remains a primary obstacle to the reliable deployment of Multimodal Large Language Models (MLLMs). Current inference-time mitigatio

REVEAL: Reference-Grounded Reasoning for Multimodal Manipulation Detection

arXiv:2605.28459v1 Announce Type: new Abstract: Multimodal manipulation detection aims to simultaneously identify forged image--text pairs and localize tampered regions, yet existing methods typically

ReverseMath: Answer Inversion for Scalable and Verifiable Mathematical Problem Generation

arXiv:2605.27709v1 Announce Type: new Abstract: Mathematical reasoning benchmarks are vital for evaluating large language models (LLMs), but many are static and repeatedly exposed through public evalu

Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms

arXiv:2605.27782v1 Announce Type: new Abstract: We present the first theoretical convergence analysis of machine learning training under fully homomorphic encryption (FHE), combined with a differentia

Risk-aware Selective Prompting for Hallucination Mitigation in Large Vision-Language Models

arXiv:2605.28123v1 Announce Type: new Abstract: Prompt-based verification is widely used to mitigate hallucinations in large vision-language models (LVLMs), yet when it helps remains poorly understood

Risk-Controlled Lean-as-Judge for Natural-Language Mathematical Reasoning

arXiv:2605.28365v1 Announce Type: new Abstract: Lean is increasingly used to judge natural-language mathematical answers, but its signal is partial: many answers never formalize, and a failed proof ma

RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs

arXiv:2509.21128v2 Announce Type: replace Abstract: Large language models (LLMs) are typically trained by reinforcement learning (RL) with verifiable rewards (RLVR) and supervised fine-tuning (SFT) on

RULER: Representation-Level Verification of Machine Unlearning

arXiv:2605.27569v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific training records from a deployed model without retraining from scratch. Current protocols ve

SAFE-Diff: Scale-Aware Attention and Feature-Dispersive Diffusion with Uncertainty Estimation for Contrast-Enhanced Breast MRI Synthesis

arXiv:2605.25767v2 Announce Type: replace Abstract: Synthesizing high fidelity contrast enhanced MRI is clinically valuable for safer and more efficient breast cancer screening, yet remains challengin

SANTS: A State-Adaptive Scheduler for World Action Models

arXiv:2605.27947v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot manipulation by using video-based future representations to condition action generation. In pixel-space WAMs, h

researcharxiv-cs-ro

Satisfiability Solving with LLMs: A Matched-Pair Evaluation of Reasoning Capability

arXiv:2605.28602v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for tasks that implicitly reduce to Boolean satisfiability (SAT), yet their reasoning ability on SAT

Score Based Error Correcting Code Decoder

arXiv:2605.28358v1 Announce Type: cross Abstract: Error-correcting codes enable reliable communication, yet practical soft decoding remains challenging across code families and block lengths. We propo

Self-Consistency via Marginal Sharpening

arXiv:2605.28142v1 Announce Type: cross Abstract: Inference-time sampling can elicit strong reasoning abilities from language models without additional training. Existing power-sampling methods do so

Self-Prophetic Decoding to Unlock Visual Search in LVLMs

arXiv:2605.28741v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) are rapidly evolving toward true multimodal reasoning, with visual search representing a concrete instantiation of

SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification

arXiv:2510.02329v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates LLM inference by verifying candidate tokens from a draft model against a larger target model. Recent judge de

Semantic Flow Regularization: Teaching LLMs to Generate Diverse Yet Coherent Responses

arXiv:2605.27971v1 Announce Type: cross Abstract: When large language models are fine-tuned to generate persona- or tone-conditioned responses, their output diversity is severely limited--a failure we

Semantic-level Backdoor Attack against Text-to-Image Diffusion Models

arXiv:2602.04898v3 Announce Type: replace-cross Abstract: Text-to-image (T2I) diffusion models are widely adopted for their strong generative capabilities, yet remain vulnerable to backdoor attacks. E

Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression

arXiv:2605.28567v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have become a central tool for interpreting language models. However, two key SAE analyses that remain difficult to scale a

Semi-Supervised Hypothesis Testing by Betting on Predictions

arXiv:2605.28533v1 Announce Type: new Abstract: We introduce a testing-by-betting framework that leverages predictions on unlabeled data to enhance the power of sequential hypothesis testing. Given li

Sequential Neural Probabilistic Amplitude Shaping: Learning the Channel's Language

arXiv:2605.28143v1 Announce Type: new Abstract: We present the first neural probabilistic amplitude shaping that outperforms existing methods while accounting for all implementation losses, using a bl

Short-Term Gain, Long-Term Fragility: AI Labor Substitution and the Erosion of Sustainable Capability

arXiv:2605.27399v1 Announce Type: cross Abstract: What looks like acceleration can be a quiet transfer of burden from the present to the future. Attempts to replace human labor with AI systems are oft

SilentRetrieval: Hijacking Retrieval-Augmented Generation via Semantically-Preserving Adversarial Data Poisoning

arXiv:2605.28074v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) mitigates LLM hallucinations but introduces a critical vulnerability: corpus integrity. We present SilentRetrieva

Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities

arXiv:2410.04096v2 Announce Type: replace-cross Abstract: In this paper, we propose to use Sinc interpolation in the context of Kolmogorov-Arnold Networks, neural networks with learnable activation fu

Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection

arXiv:2605.28631v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) can yield large reasoning gains from very few training instances, yet its strong sensitivity to wh

Skillful high-resolution weather forecasting independent of physical models

arXiv:2605.28153v1 Announce Type: cross Abstract: Accurate and timely weather forecasts are critical for high-impact decisions in modern society. Machine-learning-based weather prediction is emerging

Smoothed Score Queries and the Complexity of Sampling

arXiv:2605.27769v1 Announce Type: cross Abstract: We study the query complexity of sampling from high-dimensional Gaussian distributions using gradient information. In the standard oracle model, exact

Model Releases

SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding

model-releasesarxiv-cs-ai

arXiv:2601.21666v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are a major focus of recent AI research. However, most prior work focuses on static image understanding, wh

Sparse Scheduled Diffusion Guidance for Inverse Problems

arXiv:2603.07860v2 Announce Type: replace Abstract: Pretrained diffusion models are effective priors for Bayesian inverse problems, but posterior sampling with these priors is often costly because dat

SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training

arXiv:2605.27541v1 Announce Type: new Abstract: Dynamic Sparse Training (DST) methods train neural networks by maintaining sparsity while dynamically adapting the network topology. Despite the promise

ST-ColoNet: Spatio-Temporal Colon Segment Recognition via Hybrid Attention and Edge-Guided Feature Learning

arXiv:2605.28119v1 Announce Type: new Abstract: Colo-segment recognition in colonoscopy videos is a key requirement for many downstream tasks, but existing automatic recognition methods only use colon

STAB: Specification-driven Testing for Algorithmic Bottlenecks

arXiv:2605.27981v1 Announce Type: new Abstract: Evaluating the efficiency of algorithmic code requires test cases that expose runtime bottlenecks. Previous methods generate efficiency test cases eithe

Stabilizing distribution-free probabilistic forecasts

arXiv:2605.28531v1 Announce Type: new Abstract: Multi-step-ahead forecasts are often updated as new observations become available, since shorter forecast horizons typically improve forecast quality. H

Stance Detection in Prediction Markets: Addressing Imbalanced Trader Commentary via Counterfactual Augmentation and Market Context

arXiv:2605.28745v1 Announce Type: new Abstract: Prediction markets such as Polymarket aggregate crowd beliefs into real-time probability estimates, and the comments traders post beneath each market co

STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation

arXiv:2505.18647v3 Announce Type: replace-cross Abstract: Simulating trajectories of dynamical systems is a fundamental problem in a wide range of fields such as molecular dynamics, biochemistry, and

Stop Rewarding Hallucinated Steps: Faithfulness-Aware Step-Level Reinforcement Learning for Small Reasoning Models

arXiv:2602.05897v2 Announce Type: replace Abstract: As large language models become smaller and more efficient, small reasoning models (SRMs) are crucial for enabling chain-of-thought (CoT) reasoning

Structure over Pixels: Learning Variable-Length Visual Programs

arXiv:2605.27696v1 Announce Type: new Abstract: Discrete visual tokenizers translate images into ordered sequences of codes, providing a natural representation for structural description of scenes. Ye

Super-Resolved Canopy Height Mapping from Sentinel-2 Time Series Using Airborne LiDAR HD Reference Data across Metropolitan France

arXiv:2512.11524v3 Announce Type: replace Abstract: Fine-scale forest monitoring is essential for understanding canopy structure and its dynamics, which are key indicators of carbon stocks, biodiversi

Syllabic-Structure Decoder for Automatic Speech Recognition in Vietnamese

arXiv:2605.27874v1 Announce Type: new Abstract: Most Automatic Speech Recognition (ASR) systems formulate transcription as a prediction problem over orthographic units such as characters, subwords, or

Synthetic Emotions vs. Gamification: Exploring Engagement Strategies for Small Social Robots in Different Age Groups

arXiv:2605.27539v1 Announce Type: new Abstract: Many children experience challenges in emotional regulation and social interaction, which can limit their participation in everyday activities and thera

researcharxiv-cs-ro

Tactile-Proprioceptive Sensor Fusion for Contact Wrench Estimation in Whole-Body Physical Human-Robot Interaction

arXiv:2605.28412v1 Announce Type: cross Abstract: Direct physical guidance is a natural means of teaching and interacting with robots, and robotic skins make a key contribution by enabling sensitive c

TARQ: Tail-Aware Reconstruction Quantization for Rare-Word Robust Automatic Speech Recognition

arXiv:2605.27808v1 Announce Type: new Abstract: Data-aware post-training quantization (PTQ) minimizes a per-token reconstruction loss on a small calibration corpus, implicitly weighting positions by t

Tell Me a Story! Narrative-Driven XAI with Large Language Models

arXiv:2309.17057v3 Announce Type: replace Abstract: In many AI applications today, the predominance of black-box machine learning models, due to their typically higher accuracy, amplifies the need for

Text-Only Data Synthesis for Vision Language Model Training

arXiv:2503.22655v2 Announce Type: replace Abstract: Training vision-language models (VLMs) typically requires large-scale, high-quality image-text pairs, but collecting or synthesizing such data is co