Search: “research”

Privacy-Preserving LLMs Routing

arXiv:2604.15728v1 Announce Type: cross Abstract: Large language model (LLM) routing has emerged as a critical strategy to balance model performance and cost-efficiency by dynamically selecting servic

Proper Body Landmark Subset Enables More Accurate and 5X Faster Recognition of Isolated Signs in LIBRAS

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DGX agent

arXiv:2510.24887v4 Announce Type: replace Abstract: This paper examines the feasibility of utilizing lightweight body landmark detection for recognizing isolated signs in Brazilian Sign Language (LIBR

researcharxiv-cs-cv

20 Apr 2026

Protecting Language Models Against Unauthorized Distillation through Trace Rewriting

arXiv:2602.15143v2 Announce Type: replace Abstract: Knowledge distillation is a widely adopted technique for transferring capabilities from LLMs to smaller, more efficient student models. However, una

Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)

arXiv:2604.15398v1 Announce Type: new Abstract: We explore the possibility of solving Partial Differential Equations (PDEs) using discrete weak formulations. We propose a programming environment for d

RAGognizer: Hallucination-Aware Fine-Tuning via Detection Head Integration

arXiv:2604.15945v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is widely used to augment the input to Large Language Models (LLMs) with external information, such as recent or do

Ranking XAI Methods for Head and Neck Cancer Outcome Prediction

arXiv:2604.16034v1 Announce Type: new Abstract: For head and neck cancer (HNC) patients, prognostic outcome prediction can support personalized treatment strategy selection. Improving prediction perfo

Reading today's open-closed performance gap

This article analyzes the performance differences between open-source and closed-source AI models in the current landscape, examining factors that influence their relative capabilities and market posi

researchinterconnects

RelativeFlow: Taming Medical Image Denoising Learning with Noisy Reference

arXiv:2604.15459v1 Announce Type: cross Abstract: Medical image denoising (MID) lacks absolutely clean images for supervision, leading to a noisy reference problem that fundamentally limits denoising

Resource-efficient equivariant quantum convolutional neural networks

arXiv:2410.01252v2 Announce Type: replace-cross Abstract: Equivariant quantum neural networks (QNNs) are promising variational models that exploit symmetries to improve machine learning capabilities.

Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking

arXiv:2604.15621v1 Announce Type: cross Abstract: Adaptive Retrieval-Augmented Generation aims to mitigate the interference of extraneous noise by dynamically determining the necessity of retrieving s

Reward Modeling for Scientific Writing Evaluation

arXiv:2601.11374v2 Announce Type: replace Abstract: Scientific writing is an expert-domain task that demands deep domain knowledge, task-specific requirements and reasoning capabilities that leverage

Robust Fleet Sizing for Multi-UAV Inspection Missions under Synchronized Replacement Demand

arXiv:2604.15890v1 Announce Type: new Abstract: Multi-UAV inspection missions require spare drones to replace active drones during recharging cycles. Existing fleet-sizing approaches often assume stea

researcharxiv-cs-ro

Scalable spatial point process models for forensic footwear analysis

arXiv:2602.07006v2 Announce Type: replace Abstract: Shoe print evidence recovered from crime scenes plays a key role in forensic investigations. By examining shoe prints, investigators can determine d

Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning

arXiv:2509.25300v4 Announce Type: replace-cross Abstract: While scaling laws for large language models (LLMs) during pre-training have been extensively studied, their behavior under reinforcement lear

SegMix:Shuffle-based Feedback Learning for Semantic Segmentation of Pathology Images

arXiv:2604.15777v1 Announce Type: cross Abstract: Segmentation is a critical task in computational pathology, as it identifies areas affected by disease or abnormal growth and is essential for diagnos

Self-Aligned Reward: Towards Effective and Efficient Reasoners

arXiv:2509.05489v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards has significantly advanced reasoning in large language models (LLMs), but such signals remain coarse,

Self-Supervised Angular Deblurring in Photoacoustic Reconstruction via Noisier2Inverse

arXiv:2604.15681v1 Announce Type: new Abstract: Photoacoustic tomography (PAT) is an emerging imaging modality that combines the complementary strengths of optical contrast and ultrasonic resolution.

Sentiment Analysis of German Sign Language Fairy Tales

arXiv:2604.16138v1 Announce Type: new Abstract: We present a dataset and a model for sentiment analysis of German sign language (DGS) fairy tales. First, we perform sentiment analysis for three levels

Sequential KV Cache Compression via Probabilistic Language Tries: Beyond the Per-Vector Shannon Limit

arXiv:2604.15356v1 Announce Type: cross Abstract: Recent work on KV cache quantization, culminating in TurboQuant, has approached the Shannon entropy limit for per-vector compression of transformer ke

SignX: Continuous Sign Recognition in Compact Pose-Rich Latent Space

arXiv:2504.16315v4 Announce Type: replace-cross Abstract: The complexity of Sign Language (SL) data processing brings many challenges. The current approach to recognition of SL signs aims to translate

Similarity-Based Bike Station Expansion via Hybrid Denoising Autoencoders

arXiv:2604.15783v1 Announce Type: new Abstract: Urban bike-sharing systems require strategic station expansion to meet growing demand. Traditional allocation approaches rely on explicit demand modelli

SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators

arXiv:2603.20410v2 Announce Type: replace Abstract: Scientific machine learning is increasingly used to build surrogate models, yet most models are trained under a restrictive assumption in which futu

Special Unitary Parameterized Estimators of Rotation

arXiv:2411.13109v4 Announce Type: replace Abstract: This paper revisits the topic of rotation estimation through the lens of special unitary matrices. We begin by reformulating Wahba's problem using S

researcharxiv-cs-ro

Splats in Splats++: Robust and Generalizable 3D Gaussian Splatting Steganography

arXiv:2604.15862v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently redefined the paradigm of 3D reconstruction, striking an unprecedented balance between visual fidelity and com

SPLIT: Self-supervised Partitioning for Learned Inversion in Nonlinear Tomography

arXiv:2604.15651v1 Announce Type: new Abstract: Machine learning has achieved impressive performance in tomographic reconstruction, but supervised training requires paired measurements and ground-trut

SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification

arXiv:2604.15711v1 Announce Type: cross Abstract: Pathological diagnosis is highly reliant on image analysis, where Regions of Interest (ROIs) serve as the primary basis for diagnostic evidence, while

StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models

arXiv:2604.15416v1 Announce Type: cross Abstract: Sign-based optimization algorithms, such as SignSGD, have garnered significant attention for their remarkable performance in distributed learning and

Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants

arXiv:2604.15727v1 Announce Type: new Abstract: Large language models exhibit systematic limitations in structured logical reasoning: they conflate hypothesis generation with verification, cannot dist

Struggle Premium : How Human Effort and Imperfection Drive Perceived Value in the Age of AI

arXiv:2604.15324v1 Announce Type: cross Abstract: As AI enters creative practice, audiences face growing uncertainty in judging authenticity and value. This study examines the Struggle Premium, the ad

SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos

arXiv:2602.05638v3 Announce Type: replace Abstract: While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that w

SWNet: A Cross-Spectral Network for Camouflaged Weed Detection

arXiv:2604.16147v1 Announce Type: cross Abstract: This paper presents SWNet, a bimodal end-to-end cross-spectral network specifically engineered for the detection of camouflaged weeds in dense agricul

Target-Oriented Pretraining Data Selection via Neuron-Activated Graph

arXiv:2604.15706v1 Announce Type: new Abstract: Everyday tasks come with a target, and pretraining models around this target is what turns them into experts. In this paper, we study target-oriented la

Teaching Language Models Mechanistic Explainability Through MechSMILES

arXiv:2512.05722v2 Announce Type: replace Abstract: Chemical reaction mechanisms are the foundation of how chemists evaluate reactivity and feasibility, yet current Computer-Assisted Synthesis Plannin

The Amazing Stability of Flow Matching

arXiv:2604.16079v1 Announce Type: new Abstract: The success of deep generative models in generating high-quality and diverse samples is often attributed to particular architectures and large training

The countries MAGA describes as collapsing and joyless hold positions 1 through 6 in the global happiness rankings. They have held them for …

The countries MAGA describes as collapsing and joyless hold positions 1 through 6 in the global happiness rankings. They have held them for years. The country producing the most content about European

researchyann-lecun--x

The Download: murderous ‘mirror’ bacteria, and Chinese workers fighting AI doubles

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. No one’s sure if synthetic mirror life will kill us all In Feb

researchmit-tech-review

The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformation

arXiv:2604.15372v1 Announce Type: cross Abstract: As generative AI advances, the distinction between authentic and synthetic media is increasingly blurred, challenging the integrity of online informat

Think Multilingual, Not Harder: A Data-Efficient Framework for Teaching Reasoning Models to Code-Switch

arXiv:2604.15490v1 Announce Type: new Abstract: Recent developments in reasoning capabilities have enabled large language models to solve increasingly complex mathematical, symbolic, and logical tasks

🤖 This debate is largely a matter of productivity gains-@a_bergeaud's latest book is a must read to easily understand why ! 📈 With @BunelS…

🤖 This debate is largely a matter of productivity gains-@a_bergeaud's latest book is a must read to easily understand why ! 📈 With @BunelSimon @XJaravel @tmikaelsen @alexandraroulet J.Søgaard we found

researchyann-lecun--x

Time-optimal Convexified Reeds-Shepp Paths on a Sphere

arXiv:2504.00966v2 Announce Type: replace Abstract: This article studies the time-optimal path planning problem for a convexified Reeds-Shepp (CRS) vehicle on a unit sphere, capable of both forward an

researcharxiv-cs-ro

To LLM, or Not to LLM: How Designers and Developers Navigate LLMs as Tools or Teammates

arXiv:2604.15344v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into design and development workflows, yet decisions about their use are rarely binary or pur

Topology-Driven Fusion of nnU-Net and MedNeXt for Accurate Brain Tumor Segmentation on Sub-Saharan Africa Dataset

arXiv:2604.15964v1 Announce Type: cross Abstract: Accurate automatic brain tumor segmentation in Low and Middle-Income (LMIC) countries is challenging due to the lack of defined national imaging proto

Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset

arXiv:2604.16114v1 Announce Type: new Abstract: Tone style transfer for photo retouching aims to adapt the stylistic tone of the reference image to a given content image. However, the lack of high-qua

Towards Rigorous Explainability by Feature Attribution

arXiv:2604.15898v1 Announce Type: new Abstract: For around a decade, non-symbolic methods have been the option of choice when explaining complex machine learning (ML) models. Unfortunately, such metho

TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG

arXiv:2512.07515v4 Announce Type: replace-cross Abstract: Detecting hallucinations in Retrieval-Augmented Generation remains a challenge. Prior approaches attribute hallucinations to a binary conflict

Training Flow Matching: The Role of Weighting and Parameterization

arXiv:2603.06454v2 Announce Type: replace Abstract: We study the training objectives of denoising-based generative models, with a particular focus on loss weighting and output parameterization, includ

Training Time Prediction for Mixed Precision-based Distributed Training

arXiv:2604.16145v1 Announce Type: cross Abstract: Accurate prediction of training time in distributed deep learning is crucial for resource allocation, cost estimation, and job scheduling. We observe

Transfer Learning from Foundational Optimization Embeddings to Unsupervised SAT Representations

arXiv:2604.15448v1 Announce Type: cross Abstract: Foundational optimization embeddings have recently emerged as powerful pre-trained representations for mixed-integer programming (MIP) problems. These