Search: “research”

Constant Swap Regret in General-Sum Games via Optimistic Transition Matrices

arXiv:2609.16751v1 Announce Type: cross Abstract: We give deterministic and uncoupled learning dynamics for finite multiplayer general-sum games under full-information feedback that achieve constant i

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Copula Adapted Directed Acyclic Graph for Cluster Representation of Biomedical Data

DGX agent

arXiv:2609.16240v1 Announce Type: cross Abstract: Diagnostic errors and mislabeling are common in biomedicine, which compromise the reliability of predictive models and data-driven outcomes. Stratifyi

researcharxiv-cs-lg

16 Sept 2026

CTAN: Cycle-Temporal Attention Network for Embodied Audio-Visual Navigation

arXiv:2609.17420v1 Announce Type: cross Abstract: Audio-visual embodied navigation equips robots with the capability to infer the locations of sound sources by integrating visual inputs and acoustic i

Decentralized Gossip Learning and Federated Averaging for Histopathology Image Classification

arXiv:2609.16448v1 Announce Type: new Abstract: Breast histopathology analysis increasingly relies on distributed learning because direct data pooling across institutions is often restricted by privac

DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Viewpoint Video Streaming

arXiv:2609.17230v1 Announce Type: new Abstract: Streaming 3D reconstruction demands both speed and temporal fidelity, goals that existing methods undermine by updating every Gaussian every frame, even

Deconstructing Stereotypes: Scope-Conditioned Generation for Effective Multilingual Counterspeech

arXiv:2609.16906v1 Announce Type: new Abstract: Counterspeech (CS) - direct responses that counter online Hate Speech (HS) using reasoning and alternative viewpoints - has emerged as an alternative to

Diagnosing the Fact-Grounding Gap in Multi-Hop Question Answering

arXiv:2609.17043v1 Announce Type: cross Abstract: Multi-hop question answering requires combining information from multiple documents to answer complex questions. These systems have grown increasingly

DiaWhisper-DPO: Role-Attributed Transcription of Clinical Interviews via Failure-Mined Preference Optimization

arXiv:2609.16661v1 Announce Type: new Abstract: Automated depression screening from clinical interviews requires attribution of utterances to the clinician or patient. We evaluate two datasets: DAIC-W

Differentiable Mesh State Estimation via Factor Graph Inference for Deformable Object Reconstruction

arXiv:2609.16686v1 Announce Type: cross Abstract: Estimating deformable object states remains a fundamental challenge in robotics and simulation. We propose a novel factor graph-based framework for pr

Digital Persuasion: Understanding the Impact of Online Influencers on Public Opinion

arXiv:2609.16062v1 Announce Type: cross Abstract: The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political

Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions

arXiv:2609.16907v1 Announce Type: cross Abstract: AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion dis

Distributed JEPA: A Self-Supervised Framework for Energy Forecasting

arXiv:2609.17029v1 Announce Type: cross Abstract: Traditional energy forecasting solutions rely on task-specific supervision and energy asset representations, limiting transferability and the ability

Drift Field Net: Learning Ocean Lagrangian advection fields from in-situ and satellite observations

arXiv:2609.16288v1 Announce Type: new Abstract: The North Pacific Subtropical Gyre (NPSG) is a major accumulation zone for floating plastic debris, resulting from basin-scale convergent ocean circulat

Early-Bird Decoding: Accelerating Diffusion LLMs with Learnable Block Sizes and Parallel Sampling

arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative

EBL: Efficient Broad Learning for Distributed Adaptive Harmonic Analysis

arXiv:2609.16358v1 Announce Type: cross Abstract: Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominate

ECHO: Early-layer Collaborative Hierarchical Orchestration with Bonus Logits in Speculative Decoding

arXiv:2609.17241v1 Announce Type: new Abstract: While draft-model-free speculative decoding offers a promising path to efficient LLM inference, it is frequently constrained by stale draft candidates a

Efficient One-to-Many Translation with Joint Multi-Stream Diffusion

arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both

Efficient Text-to-Image Generation: An Adaptive Step Schedule Controller for Diffusion Models

arXiv:2609.16572v1 Announce Type: cross Abstract: Text-to-image diffusion models often use a fixed number of denoising steps, balancing time costs and image quality. However, the optimal number of ste

Enhancing Low-resolution Image Representation Through Normalizing Flows

arXiv:2601.06834v2 Announce Type: replace Abstract: Low-resolution image representation can be regarded as a special form of sparse representation that retains only low-frequency information while dis

Equivalence of approximation by networks of single- and multi-spike neurons

arXiv:2603.13478v2 Announce Type: replace-cross Abstract: In a spiking neural network, is it enough for each neuron to spike at most once? In recent work, approximation bounds for spiking neural netwo

evMLP: An Efficient Event-Driven MLP Architecture for Vision

arXiv:2507.01927v3 Announce Type: replace Abstract: While CNNs and ViTs dominate vision architectures, all-MLP models offer a structurally simpler alternative whose patch-independent processing is nat

Excited to announce that the Korean translation of 'Deep Learning with Python (3rd Edition)' by @fchollet and @mattdangerw is published! 🚀 …

researchfrancois-chollet--x

Excited to announce that the Korean translation of 'Deep Learning with Python (3rd Edition)' by @fchollet and @mattdangerw is published! 🚀 Updated for Keras 3, TensorFlow, PyTorch, JAX, and Generative

Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction

arXiv:2503.16286v2 Announce Type: replace Abstract: Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of ca

FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

arXiv:2609.16842v1 Announce Type: new Abstract: Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD

Federated stochastic bilevel optimization with fully first-order gradients

arXiv:2609.16350v1 Announce Type: new Abstract: Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, mos

FlexEE: Self-Speculative and KV-Compatible Early Exiting for Offloading-Aware LLM Inference

arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights

Formalized Hopfield Networks and Boltzmann Machines

arXiv:2512.07766v2 Announce Type: replace Abstract: Neural networks are widely used, yet their analysis and verification remain challenging. We present a Lean~4 formalization covering both determinist

FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection

arXiv:2609.17491v1 Announce Type: new Abstract: Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to ha

From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling

arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since

Generative models for simulation based filtering: Formulations and Empirical Comparisons

arXiv:2609.16317v1 Announce Type: new Abstract: This letter presents a unified formulation and a controlled numerical comparison of generative-model approaches to the nonlinear filtering problem. Unde

Geometry of learning dynamics: Gradient descent versus natural gradient on the ridge of optimization

arXiv:2609.16805v1 Announce Type: new Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit a 'Ridge of Optimization' characterized by extreme stability and a

Goal-oriented probabilistic forecasting for dynamic PRB allocation in 5G networks

arXiv:2609.17297v1 Announce Type: cross Abstract: Efficient physical resource block (PRB) allocation in 5G networks requires accurate demand forecasting. Conventional methods minimize symmetric error

GoBench: Evaluating LLMs on the game of Go [R]

researchr-machinelearning

GoBench evaluates LLMs on 9x9 Go games against a ladder of KataGo opponents, from random to superhuman. It measures general reasoning ability, strongly correlates with ARC-AGI 2 (r=0.83 correlation),

GRACE: Geometry- and Ray-Aware Camera-Efficient Multi-View Pedestrian Tracking

arXiv:2609.16872v1 Announce Type: new Abstract: Reducing the number of cameras reduces the deployment cost but removes views that correct BEV responses stretched away from true pedestrian positions by

GraLoD: Graphics-Inspired Continuous Level-of-Detail Learning for Image Restoration

arXiv:2609.16578v1 Announce Type: new Abstract: The spatial support required for image restoration varies across degradation types, image regions, and reconstruction stages. However, most existing met

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning

arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,

HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised Learning

arXiv:2609.16060v1 Announce Type: cross Abstract: Users often need ask questions and seek answers online. The Question - Answering (QA) forums such as Stack Overflow cannot always respond to the quest

HLC-GS: Risk-Map-Guided Height-Layer Consistency Gaussian Splatting for DSM Reconstruction from Optical Satellite Imagery

arXiv:2609.16772v1 Announce Type: new Abstract: A Digital Surface Model (DSM) is a fundamental geospatial data product for representing the elevation of the Earth's surface. Recently, 3D Gaussian Spla

Implementing a White-Box Undetectable Backdoor for Random Fourier Features

arXiv:2609.16403v1 Announce Type: cross Abstract: Goldwasser et al. showed that undetectable backdoors can be planted in machine learning models trained with the Random Fourier Features (RFF) algorith

Improving Reduced-Order Rotating Detonation Engine Models with Data Assimilation and Machine Learning

arXiv:2609.16237v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) exhibit strongly nonlinear, multiscale wave dynamics that set the observed thermal field. High-fidelity simulations

InfoTaxa: Information-Calibrated Label-Free Clustering for Fine-Grained Visual Taxonomy

arXiv:2609.17218v1 Announce Type: new Abstract: Label-free clustering of frozen pretrained visual embeddings offers a scalable route to biodiversity monitoring, but image-only fine-grained taxonomy ex

Interpreting and Steering LLM Agents for Social Simulations

arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the s

IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy

arXiv:2609.17175v1 Announce Type: new Abstract: We present IRENE (Italian Radar Ensemble Nowcasting Experiment), a deep learning model for probabilistic short-range precipitation nowcasting over the I

Language Orthogonalization for Zero-Shot Cross-Lingual Audio Deepfake Detection

arXiv:2609.16458v1 Announce Type: cross Abstract: Audio deepfake detectors need to transfer to languages absent from training, as multilingual speech synthesis outpaces labeled anti-spoofing resources

LCAP: Population-Informed Latent Chip Adaptation from Few Output Probes for Photonic Neural Networks

arXiv:2609.16823v1 Announce Type: new Abstract: Photonic neural networks (PNNs) offer efficient analog inference, but parameters optimized under ideal device models can degrade after fabrication, crea

Learned Look-Ahead Splitting Rule for CART

arXiv:2609.16440v1 Announce Type: cross Abstract: Classification and regression trees are typically constructed using a greedy splitting rule that maximizes the immediate reduction in prediction error

Lit3R: Retrieve-Relate-Read for Evidence-Grounded Question Answering over Scientific Literature

arXiv:2609.16912v1 Announce Type: new Abstract: We describe tus-nlp's Lit3R (Retrieve-Relate-Read) system for LitTraceQA, a shared task for literature-grounded question answering that requires systems