research

Multi-Modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification

arXiv:2606.03322v1 Announce Type: cross Abstract: The graphical representation of the brain offers critical insights into diagnosing and prognosing neurodegenerative disease via relationships between

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Multi-Robot Bearing-only Pose Estimation via Angle Rigidity

DGX agent

arXiv:2606.03931v1 Announce Type: new Abstract: This letter proposes a novel distributed bearing-based pose estimator for time-varying multi-robot systems. The method uses angles computed from body-fr

researcharxiv-cs-ro

3 Jun 2026

Multiple Choice Learning of Low-Rank Adapters for Language Modeling

arXiv:2507.10419v3 Announce Type: replace-cross Abstract: We propose LoRA-MCL, a training scheme that extends next-token prediction in language models with a method designed to decode diverse, plausib

Names Don't Matter: Symbol-Invariant Transformer for Open-Vocabulary Learning

arXiv:2601.23169v2 Announce Type: replace Abstract: Current neural architectures lack a principled way to handle interchangeable tokens, i.e., symbols that are semantically equivalent yet distinguisha

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models

arXiv:2602.03681v2 Announce Type: replace Abstract: The quadratic computational complexity of softmax transformers has become a bottleneck in long-context scenarios. In contrast, linear attention mode

NeurIPS used uncalibrated AI detector for desk rejections [D]

researchr-machinelearning

NeurIPS 2026 used an AI detector to identify policy violations, resulting in 178 desk-rejected submissions (18.4% of all submissions) and 123 flagged for further review (12.7%) . The detection approac

Non-Identical Diffusion Models in MIMO-OFDM Channel Generation

arXiv:2509.01641v3 Announce Type: replace-cross Abstract: We propose a novel diffusion model, termed the non-identical diffusion model, and investigate its application to wireless orthogonal frequency

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration

arXiv:2507.23035v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated impressive capabilities across a wide range of applications, but demand substantial memory and comput

On The Computational Complexity of Minimum Aerial Photographs for Planar Region Coverage

arXiv:2512.18268v3 Announce Type: replace Abstract: With the popularity of drone technologies, aerial photography has become prevalent in many daily scenarios such as environment monitoring, structure

researcharxiv-cs-ro

One Transit Is All You Need: Detecting Exoplanets Through Learned Stellar Behaviour with EXOVEIL

arXiv:2606.02778v1 Announce Type: cross Abstract: I present EXOVEIL, a transit detection system that learns what a star's brightness should look like and flags when reality disagrees. Unlike existing

Online Learning with Gradient-Variation Interval Regret

arXiv:2606.03831v1 Announce Type: new Abstract: This paper investigates non-stationary online learning using the metric of interval regret, which requires an online algorithm to perform well over ever

Optimal Design and Analytical Modeling of a Soft Fin-Ray Effect Gripper Finger Using the Finite Rigid Elements Method

arXiv:2606.03798v1 Announce Type: new Abstract: Fin Ray-inspired soft grippers offer a promising solution for gently handling delicate, irregular objects, especially in agriculture. The objective of t

researcharxiv-cs-ro

Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images

arXiv:2505.08886v2 Announce Type: replace Abstract: The rising incidence of skin cancer, coupled with limited public awareness and a shortfall in clinical expertise, underscores an urgent need for adv

PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training

arXiv:2606.03264v1 Announce Type: new Abstract: We introduce PaddleOCR-VL-1.6, an upgraded compact document parsing model built upon PaddleOCR-VL-1.5. Although PaddleOCR-VL-1.5 establishes a strong 0.

PersistGS: Differentiable Physics for Object Permanence in 4D Gaussian Splatting

arXiv:2606.03479v1 Announce Type: new Abstract: Dynamic 3D Gaussian Splatting (3DGS) methods reconstruct time-varying scenes from synchronized multi-camera video using photometric supervision. When a

Pixel Cube: Diffusion-based Portrait Video Relighting Through Realistic Lighting Reproduction

arXiv:2606.02919v1 Announce Type: new Abstract: We present a diffusion-based method for relighting dynamic portrait videos with photorealism and temporal consistency. Our method is fueled by a hybrid

PixVOD: Pixel-Distributed Direct Visual Odometry and Depth Estimation

arXiv:2606.03989v1 Announce Type: new Abstract: Images composed of 2D pixel arrays are the standard input to computer vision algorithms, yet many underlying computations can be distributed across pixe

PointAction: 3D Points as Universal Action Representations for Robot Control

arXiv:2606.03943v1 Announce Type: new Abstract: Video-Action Models (VAMs) leverage the broad visual dynamics captured by pre-trained video diffusion models, offering a promising path toward generaliz

researcharxiv-cs-ro

Position: Adversarial ML for LLMs Is Not Making Any Progress

arXiv:2502.02260v2 Announce Type: replace Abstract: In the past decade, considerable research effort has been devoted to securing machine learning (ML) models that operate in adversarial settings. Yet

Position: Prioritize Identifying Structure, Not Complex Models, for Scientific Discovery

arXiv:2606.02632v1 Announce Type: cross Abstract: Modern Machine Learning (ML) and Artificial Intelligence (AI) models, especially large language models (LLMs), are increasingly used to generate scien

Predicting Inference-Time Scaling Gains from Labeled Validation-Set Output Statistics

arXiv:2606.02981v1 Announce Type: new Abstract: Best-of-N inference scaling (drawing N candidate answers from a language model and returning the one a reward model ranks highest) improves accuracy by

PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization

arXiv:2606.03444v1 Announce Type: cross Abstract: Unifying the complementary strengths of diverse Vision Foundation Models (VFMs) into a single efficient model is highly desirable but challenged by th

Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss

arXiv:2606.03878v1 Announce Type: cross Abstract: Advertising platforms use randomized lift tests to measure incrementality, but privacy-preserving reporting systems degrade the observed signal throug

PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

Qiskit Fall Fest 2026: Applications open

Qiskit Fall Fest 2026 is an event organized by IBM that focuses on quantum computing education and community engagement through the open-source Qiskit framework. The event likely provides opportunitie

researchibm-research

R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks

arXiv:2504.01250v2 Announce Type: replace Abstract: This paper presents the Robust Recurrent Deep Network (R2DN), a scalable parameterization of robust recurrent neural networks for machine learning a

R^{2k} is Theoretically Large Enough for Embedding-based Top-k Retrieval

arXiv:2601.20844v3 Announce Type: replace-cross Abstract: This paper studies the Minimal Embeddable Dimension (MED): the least dimension in which there exists a configuration of m object vectors so th

Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains

arXiv:2505.16014v5 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems deployed in sensitive domains must provide interpretable evidence selection and robust safeguards again

Ref-DGS: Reflective Dual Gaussian Splatting

arXiv:2603.07664v3 Announce Type: replace-cross Abstract: The reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface

Regime-Arrival Uncertainty in Generalization Bounds under Distribution Shift

arXiv:2606.02657v1 Announce Type: new Abstract: The standard generalization bounds assume that the training and deployment distributions are the same, or are static, and don't consider regime switchin

ReLoRA: Knowledge-Reusing Adaptation for Fast Rollout of Evolving LLM Services

arXiv:2606.02606v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as continuously evolving services, where frequent base-model updates may invalidate previously

Representational Capacity: Geometric Limits on Feature Representation in Transformer Language Models

arXiv:2606.02765v1 Announce Type: cross Abstract: Model dimension (d_{model}) is a fundamental hyperparameter in transformer language models, yet its role in setting the geometric limits of feature re

Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning

arXiv:2606.03817v1 Announce Type: new Abstract: Idioms can be analysed in terms of their decomposability, the extent to which constituent meanings contribute to the figurative whole. Decomposability i

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression

arXiv:2606.03465v1 Announce Type: cross Abstract: Post-training compression is essential for deploying large language models (LLMs) under tight resource constraints. Tensor decompositions have emerged

Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers

arXiv:2502.08834v4 Announce Type: replace-cross Abstract: Deep generative models based on neural differential equations have become state-of-the-art for many generation tasks. These models rely on ODE

RGMem: Renormalization Group-inspired Memory Evolution for Language Agents

arXiv:2510.16392v3 Announce Type: replace Abstract: Personalized and continuous interactions are critical for LLM-based conversational agents, yet finite context windows and static parametric memory h

RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Construction

arXiv:2606.03074v1 Announce Type: new Abstract: Diffusion models achieve high-fidelity radio map construction through iterative denoising, yet their sampling cost limits practicality in dynamic wirele

RRISE: Robust Radius Inference via a Surrogate Estimator

arXiv:2606.02876v1 Announce Type: new Abstract: Randomized smoothing (RS) uses a smoothed classifier to provide architecture-agnostic certificates of ell_2 classification robustness, but its dependenc

Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models

arXiv:2511.02986v2 Announce Type: replace-cross Abstract: Computational modeling of single-cell gene expression is crucial for understanding cellular processes, but generating realistic expression pro

Scalable Uncertainty Quantification for Extreme Weather Forecasting via Empirical Neural Tangent Kernels

arXiv:2606.02886v1 Announce Type: cross Abstract: Deep learning weather models now match numerical weather prediction accuracy while running orders of magnitude faster, but produce deterministic forec

scBatchProx: Federated-Inspired Refinement for Stable Cell-Type Discriminability under Heterogeneous Batch Compositions

arXiv:2602.00423v3 Announce Type: replace Abstract: Single-cell integration workflows often construct low-dimensional cell embeddings and then refine them with post-hoc methods to reduce batch effects

Self-Soupervision: Cooking Model Soups without Labels

arXiv:2602.02890v2 Announce Type: replace Abstract: Model soups are strange and strangely effective combinations of parameters. They take a model (the stock), fine-tune it into multiple models (the in

Set-Preserving Calibration from Conformal P-Values to E-Values

arXiv:2606.03600v1 Announce Type: cross Abstract: Standard conformal prediction (CP) procedures are typically formulated in terms of p-values, but reliance on p-values alone limits flexibility, for ex

Sign Lock-In: Randomly Initialized Weight Signs Persist and Bottleneck Sub-Bit Model Compression

arXiv:2602.17063v2 Announce Type: replace-cross Abstract: Sub-bit model compression targets storage below one bit per weight; as magnitudes are aggressively compressed, the sign bit becomes a fixed-co

Signed Spiking Neuron Enabled by an Orthogonal-Easy-Axis Magnetic Tunnel Junction

arXiv:2606.03796v1 Announce Type: cross Abstract: Signed spiking neurons carry richer information than standard spiking neurons. This work proposes a compact magnetic tunnel junction (MTJ)-based neuro

SketchSong: Hierarchical Song Generation with Sketch Planning and Fine-Grained Multi-Track Modeling

arXiv:2606.03169v1 Announce Type: cross Abstract: Recent song generation systems can synthesize realistic audio, yet generating complete songs remains challenging for two reasons. First, explicit song

SkillPyramid: A Hierarchical Skill Consolidation Framework for Self-Evolving Agents

arXiv:2606.03692v1 Announce Type: new Abstract: Recent AI agents can flexibly invoke skills to solve complex tasks, but their long-term improvement is fundamentally constrained by a lack of systematic

SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model

arXiv:2603.26738v3 Announce Type: replace-cross Abstract: While automated sleep staging has achieved expert-level accuracy, its clinical adoption is hindered by a lack of auditable reasoning. We intro