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Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR

arXiv:2606.03087v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the ability of large language model, yet headline accuracy gains often conceal a hidden c

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Lexicons and grammars for language processing: industrial or handcrafted products?

DGX agent

arXiv:2606.03412v1 Announce Type: new Abstract: During the recent years, the use of linguistic data for language processing increased progressively. Such data are now commonly called language resource

researcharxiv-cs-cl

3 Jun 2026

Limit Analysis of Graph Neural Networks with Wireless Conflict Graphs

arXiv:2606.03794v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for wireless resource allocation that leverages the underlying graph structure of communica

Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detection

arXiv:2606.03334v1 Announce Type: new Abstract: Our submission presented in this paper is for SemEval-2026 Task 9: Multilingual Text Classification Challenge - Polarization Detection and it covers all

Linguistic Productivity in Large Language Models: Models Coerce, but do not Preempt

arXiv:2606.02953v1 Announce Type: new Abstract: Usage-based theories of grammars posit that creative productivity of the structures of language is both bolstered and constrained by two distinct freque

Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings

arXiv:2606.03365v1 Announce Type: new Abstract: Embedding models (KGEMs) constitute the main link prediction approach to complete knowledge graphs. Standard evaluation protocols emphasize rank-based m

LLM-Assisted Reranking to Operationalize Nuanced Objectives in Recommender Systems

arXiv:2606.02883v1 Announce Type: cross Abstract: Recommender systems have grown from content-organization tools into sophisticated systems that shape daily behavior. By controlling what we see, they

Low-Resolution Editing is All You Need for High-Resolution Editing

arXiv:2511.19945v3 Announce Type: replace Abstract: High-resolution content creation is rapidly emerging as a central challenge in both the vision and graphics communities. Images serve as the most fu

MAdam: Metric-Aware Multi-Objective Adam

arXiv:2606.03904v1 Announce Type: cross Abstract: Multi-objective optimization (MOO) underlies many machine learning problems, yet MOO solvers across the loss-balancing, gradient-balancing, and Pareto

Making Brain-Computer Interfaces More Secure

arXiv:2606.02597v1 Announce Type: new Abstract: The development of brain-computer interfaces (BCIs) based on electroencephalograms (EEGs) has advanced significantly mainly to machine learning. Althoug

Mamba-Enhanced Implicit Motion Learning for Audio-Driven Portrait Animation

arXiv:2606.03402v1 Announce Type: new Abstract: Audio-driven human motion video generation aims to synthesize realistic and temporally coherent human animations from a single static image, with applic

Memory Retrieval for Changing Preferences

arXiv:2606.02976v1 Announce Type: new Abstract: Long-context dialogue systems must decide both when to access memory and which parts of the interaction history are relevant. Existing approaches typica

MemVerse: Multimodal Memory for Lifelong Learning Agents

arXiv:2512.03627v2 Announce Type: replace Abstract: Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember. Withou

MLP Splatting: Object-Centric Neural Fields

arXiv:2606.03877v1 Announce Type: new Abstract: 3D representations are fundamental to scene rendering, understanding, and interaction. Recent approaches, such as 3D Gaussian Splatting and Neural Radia

More info on Nous Portal: https://portal.nousresearch.com/manage-subscription

The Nous Portal at portal.nousresearch.com/manage-subscription allows users to manage their subscriptions to Nous Research services and products. This management interface likely provides features for

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Motion Planning in Dynamic Environments: A Survey from Classical to Modern Methods

arXiv:2606.02677v1 Announce Type: new Abstract: Motion planning in dynamic environments requires robots to continuously adapt their paths in response to environmental changes for safe and uninterrupte

MuLoCo: Muon is a practical inner optimizer for DiLoCo

arXiv:2505.23725v3 Announce Type: replace Abstract: DiLoCo is a powerful framework for training large language models (LLMs), enabling larger optimal batch sizes and increased accelerator utilization

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

Multi-Robot Bearing-only Pose Estimation via Angle Rigidity

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

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

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

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

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

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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