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Meta-learning accelerates detector design optimization

arXiv:2609.35827v2 Announce Type: cross Abstract: The quality of a detector design is ultimately determined by the quality of the inference it enables, that is, by the accuracy with which the quantiti

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Minkowski Attractor Networks: Closed-Form Hyperbolic Flows for Visual Representations

DGX agent

arXiv:2609.37817v1 Announce Type: new Abstract: Geometric representation learning predominantly scaffolds representations onto flat Euclidean subspaces or compact product tori (T^K). However, flat man

researcharxiv-cs-cv

30 Sept 2026

MONOVAB : An Annotated Corpus for Bangla Multi-label Emotion Detection

arXiv:2309.15670v3 Announce Type: replace-cross Abstract: In recent years, Sentiment Analysis (SA) and Emotion Recognition (ER) have been increasingly popular in the Bangla language, which is the seve

MoRE: Scaling mixture of experts with hardware-aware low-rank routing

arXiv:2609.36301v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) layers are central to frontier language models, and recent architectures push toward more and smaller experts. In this regime

MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learning

arXiv:2609.37384v1 Announce Type: new Abstract: Molecular representation learning is central to computer-aided drug discovery. Molecular graphs, SMILES strings, and 3D conformations provide complement

MotionMaestro: Masked Tokenization for Unified Motion Generation

arXiv:2609.37495v1 Announce Type: new Abstract: Human motion generation plays an important role in applications such as character animation, virtual environments, and embodied interaction. While exist

MSTypography: Multi-character Semantic Typography via Balancing Word Legibility and Object Recognizability

arXiv:2609.37141v1 Announce Type: new Abstract: Semantic typography is a design technique where the visual representation of a word conveys its semantic meaning, while maintaining its legibility. Exis

Multi-Channel Mitigation of Source-Trust Shortcuts in Fact-Checking RL Agents

arXiv:2609.36611v1 Announce Type: new Abstract: Retrieval-augmented fact-checkers often receive a reliability label, such as HIGH or LOW trust, for each evidence source. These labels should adjust the

Multichannel Audio Quality Assessment: Extending Pretrained Perceptual Models to Spatial Audio

arXiv:2609.37116v1 Announce Type: cross Abstract: Accurate perceptual quality assessment is essential for evaluating and optimizing spatial audio, where perceived quality depends on both signal fideli

Multifunctional Locomotion Control of Multi-Jointed BURs with Swimming and gait Capabilities

arXiv:2609.37086v1 Announce Type: new Abstract: Multimodal biomimetic underwater robots (BURs) can conduct underwater tasks suitable for the environment. Combining the characteristics of aquatic organ

Mutually Adversarial Self-Training with Evolving Data for Unified Multimodal Models

arXiv:2609.36224v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) combine image generation and visual understanding in a shared backbone. Since generation and understanding are invers

Neural Constitutive Learning for Generalized Reaction-Diffusion Systems

arXiv:2609.37113v1 Announce Type: new Abstract: Generalized reaction-diffusion systems encompass diverse transport mechanisms and coupled reaction kinetics. A central question for neural PDE solvers i

Neural Structural Reasoner: A Brain-inspired Architecture for Reasoning over Structured Knowledge

arXiv:2609.36620v1 Announce Type: new Abstract: Structural reasoning, the ability to recognize and make inferences over the relational structure between objects and concepts, is a hallmark of human co

Neural Succession: A Mesoscopic Theory of Invasion, Coexistence, and Stabilization in Continual Learning

arXiv:2609.36375v1 Announce Type: new Abstract: Continual learning is usually studied through mechanisms that preserve old knowledge. We develop Successional Learning Theory (SLT), a mesoscopic accoun

NIDAR: NIR-Guided Intrinsic Decomposition for Scalable Scene-Agnostic LiDAR Intensity Reconstruction

arXiv:2609.36878v1 Announce Type: new Abstract: LiDAR return intensity provides complementary surface-response cues for robotic perception and state estimation, yet many simulation pipelines omit it o

Not Every Correction Helps: Gain-Guided Continual Test-Time Adaptation

arXiv:2609.36655v1 Announce Type: new Abstract: Continual test-time adaptation (CTTA) adapts a source model to an unlabeled test stream whose distribution may change over time. Existing TTA methods of

NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters

arXiv:2609.37038v1 Announce Type: cross Abstract: Precipitation nowcasting demands accurate short-term forecasts under strong spatiotemporal variability. Diffusion models are well suited to modeling c

On Calibration of Large Language Models: From Response To Capability

arXiv:2602.13540v2 Announce Type: replace-cross Abstract: Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on

On State Reduction in Linear Attention

arXiv:2602.04852v3 Announce Type: replace Abstract: Linear attention offers a computationally efficient yet expressive alternative to softmax attention. However, recent empirical results indicate that

On Task Scope and Information Retention in Source Coding

arXiv:2609.37575v1 Announce Type: cross Abstract: We argue that dividing codec design into Coding for Machines (CfM) and Coding for Humans (CfH) is a misleading distinction for deciding what informati

One-Step Next-Latent Prediction Is Not a World Model

arXiv:2609.36227v1 Announce Type: cross Abstract: Next-latent prediction fits a map from the current embedding to the next one. LeNEPA carries this objective to time series, replacing the stop-gradien

One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification

arXiv:2609.37861v1 Announce Type: new Abstract: In the Global South, the lower-income countries of Africa, Asia, and Latin America where most of the world's languages are spoken, a deployed text class

Optimal Quantum-Classical Separations for Exact Learning

arXiv:2609.38073v1 Announce Type: cross Abstract: We study exact learning with membership queries for concept classes mathcal Csubseteq{0,1}^N, focusing on the relationships among their deterministic,

Optimal scenario design for climate emulation

arXiv:2606.19302v2 Announce Type: replace-cross Abstract: As deep learning for physical systems continues to grow in popularity, efforts to improve generalizability have primarily focused on designing

Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations

arXiv:2405.07944v1 Announce Type: cross Abstract: Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are ofte

Ornstein-Uhlenbeck Is Hard to Beat, Yet Superlinear Drift Ships Lower Transport Costs

arXiv:2609.37579v1 Announce Type: cross Abstract: Bresar and Mijatovic ite{bresar2025} show that Ornstein--Uhlenbeck diffusion is hard to beat in forward convergence under assumptions that exclude sup

Orthogonal Yet Coupled: Decoupling Geometric Components for Model Merging

arXiv:2609.37564v1 Announce Type: new Abstract: Merging pretrained models has emerged as an effective approach for consolidating diverse capabilities into a single unified model. However, prevailing m

OTRetarget: Joint Robot and Object Motion Retargeting via Optimal Transport

arXiv:2609.36602v1 Announce Type: new Abstract: Transferring human motion to humanoid robots requires adapting the demonstrated motion to the robot morphology while preserving interactions with the en

Paired Multimodal Scaling Laws

arXiv:2609.36263v1 Announce Type: cross Abstract: Existing multimodal scaling laws fit multimodality terms empirically after testing and never vary how much data is multimodally paired at fixed data b

Parallel Tempering for Diffusion-Based Combinatorial Optimization

arXiv:2609.37323v1 Announce Type: new Abstract: Discrete diffusion models have emerged as a powerful paradigm for solving combinatorial optimization (CO) problems on graphs by learning to sample high-

Pattern Formation in Transformers

arXiv:2609.37921v1 Announce Type: new Abstract: What are the inductive biases of a Transformer architecture? Existing theory on how the forward pass shapes representations either considers whether Tra

PCaPaint: Prostate Cancer Inpainting by Mitigating Shortcut Learning

arXiv:2609.37350v1 Announce Type: new Abstract: The development of AI systems for tumor-specific applications is limited by the scarcity of labeled data. Synthetic tumor inpainting offers a promising

PE-EK-PINN: Physics Embedding with Evolving Kernel for Scalable Physics-Informed Neural Networks

arXiv:2609.38023v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) embed governing equations into deep learning, but enforce them only through loss residuals, leaving highly osci

Persistent Tri-State Message Passing

arXiv:2601.01207v2 Announce Type: replace Abstract: In stochastic message passing, an edge's sampled role changes the node states used to compute adaptive weights at later layers. Weight averaging the

Physical Cross-Modal Masked Autoencoding for Seismic-to-Well Representation Learning

arXiv:2609.36193v1 Announce Type: new Abstract: Learning from scientific measurements often requires aligning modalities with different spatial support and resolution. Subsurface characterization is a

PILLAR: Private Inverted-Index Lexical Lookup for Augmented Retrieval

arXiv:2609.36326v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) hands the user's query to whoever hosts the corpus. We propose PILLAR, a Privacy-Preserving RAG (PPRAG) system base

PISA: Prioritized Invariant Subgraph Aggregation for Out-of-Distribution Generalization on Graphs

arXiv:2511.22435v2 Announce Type: replace Abstract: Invariant learning on graphs aims to build predictors that rely on causal substructures rather than on environment-specific shortcuts. Current metho

Planetary Feature Fields are Scalable Earth Representations

arXiv:2609.37784v1 Announce Type: new Abstract: Satellite observations, precomputed embeddings, and map products describe the same evolving Earth, yet are stored as independent, petabyte-scale data pr

Planning Oriented 3D Scene Completion via Coupled TUDF Occupancy Representation Learning from Partial Observations

arXiv:2609.36543v1 Announce Type: new Abstract: Partial observability remains a fundamental challenge in robotic navigation, where limited sensor coverage and occlusions leave large portions of the en

Pow3R-SLAM: Real-Time RGB-D SLAM with 3D Reconstruction Priors

arXiv:2609.38054v1 Announce Type: cross Abstract: We present Pow3R-SLAM, a real-time RGB-D simultaneous localization and mapping (SLAM) system that uses Pow3R for tracking and mapping. Inspired by MAS

Preconditioned Physics-Informed Neural Operator Training

arXiv:2609.36216v1 Announce Type: new Abstract: Neural operators are typically trained in a supervised fashion, which requires a dataset to be generated with a classical solver. Training them physics-

Predictive Geometry of Hidden Trajectories in Transformers

arXiv:2609.37717v1 Announce Type: cross Abstract: Decoder-only transformers are trained only through a terminal next-token prediction loss, yet this loss constrains every intermediate hidden state thr

Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance

arXiv:2609.37789v1 Announce Type: cross Abstract: Self-supervised learning (SSL) by predicting in latent space, without generating the input data itself, learns highly abstract, useful representations

Principled MAP estimation for inverse problems: bridging the gap between convergence and performance

arXiv:2609.37529v1 Announce Type: new Abstract: Pretrained denoisers provide a powerful way to incorporate image priors into restoration algorithms. Plug-and-Play and RED approaches exploit fixed-nois

PrivacySkills: How Privacy Guidance Shapes Source Selection in LLM Agents

arXiv:2609.35937v1 Announce Type: cross Abstract: While prior work has documented privacy failures in LLM agents, it remains unclear how the presentation of privacy guidance influences their choice of

Probabilistic Symbolic-Distillation Model of Droplet Collision for Spray Simulation at High Ambient Pressures

arXiv:2609.37202v1 Announce Type: cross Abstract: Droplet collision governs droplet population dynamics in many chemical engineering processes, such as spray drying, spray cooling, agricultural sprayi

Proofs Without Nominals: Godel's Ontological Argument, its Shallow Embedding, and the Open Questions of the Monatshefte Notes

arXiv:2609.36279v1 Announce Type: cross Abstract: The shallow embedding of higher-order modal logic in classical higher-order logic, used in Benzmuller and Scott's Notes on Godel's and Scott's variant

PrototypeNAS: Rapid Design of Deep Neural Networks for Microcontroller Units

arXiv:2603.15106v2 Announce Type: cross Abstract: Enabling efficient deep neural network (DNN) inference on edge devices with different hardware constraints is a challenging task that typically requir