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Drift-Aware Multimodal User Representation Learning via Multi-Scale Temporal Modeling and Sparse Mixture-of-Experts

arXiv:2608.25773v1 Announce Type: new Abstract: Understanding user preferences from noisy and temporally evolving social media behaviors is fundamentally challenging due to interest drift, where user

applicationsarxiv-cs-lg

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Drift Variation Autoencoder: Unifying Generation and Representation Learning through Conditional Posterior Flow Matching

DGX agent

arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi

model-releasesarxiv-cs-lg

27 Aug 2026

DualOPSD: Adaptive Privileged Teachers for On-Policy Self-Distillation

arXiv:2608.26019v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a privileged copy of the student model to provide dense supervision without an external teacher. OPSD keeps this

safetyarxiv-cs-lg

Dynamic Influence-Weighted Distillation for Single-IMU Activity Recognition

arXiv:2608.24904v1 Announce Type: new Abstract: Inertial sensors at multiple body locations can improve activity recognition, but requiring every sensor at inference increases the deployment burden. W

Dynamic Modeling of a Welding Torch Umbilical and Its Impact on Robot Dynamics

arXiv:2608.25509v1 Announce Type: new Abstract: Robotic welding is widely used in industrial manufacturing, where the welding torch is often connected to the generator through an external umbilical. W

applicationsarxiv-cs-ro

Dynamically-Consistent Trajectory Optimization for Legged Robots via Contact Point Decomposition

arXiv:2510.24069v2 Announce Type: replace Abstract: To generate reliable motion for legged robots through trajectory optimization, it is crucial to simultaneously compute the robot's path and contact

researcharxiv-cs-ro

E2Rank: Unifying Text Embedding and Listwise Reranking for Effective and Efficient Search

arXiv:2510.22733v3 Announce Type: replace Abstract: Text embedding models deliver competitive retrieval performance with high efficiency, but their ranking fidelity remains limited compared to LLM-bas

EduAgentQG: Multi-Agent Personalized Mathematics Question Generation with Explicit Diversity and Objective-Aware Evaluation

arXiv:2511.11635v2 Announce Type: replace-cross Abstract: In intelligent education, personalized mathematics question generation aims to produce mathematics questions that satisfy educational requirem

EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus

arXiv:2510.12899v3 Announce Type: replace Abstract: Recently, several multi-turn dialogue benchmarks have been proposed to evaluate the conversational abilities of large language models (LLMs). As LLM

applicationsarxiv-cs-cl

Efficient Estimation of High Information Projections using Nearest Neighbours

arXiv:2608.25887v1 Announce Type: cross Abstract: An intuitive method for dimensionality reduction is proposed, which is highly effective for finding interesting projections of multivariate data. Foll

Efficient Training with Foresight: Multi-Token Auxiliary Supervision for Autoregressive Image Generation

arXiv:2608.25386v1 Announce Type: new Abstract: Autoregressive (AR) image generation has shown strong potential for scalable high-fidelity synthesis by modeling images as discrete token sequences. How

EgoArgus: Benchmarking VLMs as Situational Assistants for Modality-Grounded User Supports

arXiv:2608.25561v1 Announce Type: new Abstract: VLMs are increasingly positioned as daily assistants that perceive first-person environments, follow user dialogue, and decide how to help. Existing ego

EgoNav: Bridging Learned Waypoints and Geometry-Aware Local Control for Robust Indoor Navigation

arXiv:2608.25642v1 Announce Type: new Abstract: Image-goal navigation using lightweight topological maps is a practical paradigm for indoor robot deployment: the map requires only geotagged images, an

safetyarxiv-cs-ro

Embedding NDRE Trajectories into Contrastive Learning for Label-Free, Physiology-Aware Crop-Stress Staging and DSS Outputs

arXiv:2608.25888v1 Announce Type: new Abstract: Timely detection of crop stress is critical for sustaining yields under increasing drought frequency, yet conventional vegetation index thresholds or im

Emergent Abilities in Large Language Models: A Survey

arXiv:2503.05788v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are leading a new technological revolution as one of the most promising research streams toward artificial genera

Emyx: Fast and efficient all-atom protein generation

arXiv:2606.19377v2 Announce Type: replace Abstract: Computational enzyme design requires generating proteins that scaffold catalytic residues and ligands, a task that demands both geometric accuracy a

EncoTESS: Age-Sensitive Encodings from Raw TESS Light Curves

arXiv:2608.25019v1 Announce Type: cross Abstract: Main sequence stars of spectral types late F through M exhibit systematic variability in photometric light curves, particularly when they are young. R

Energy Yield and Lifetime Climate Classification via Machine Learning for Optimizing Photovoltaic Module Design and Materials

arXiv:2608.25448v1 Announce Type: cross Abstract: To resiliently and sustainably meet our future energy demand, photovoltaic (PV) modules must be deployed across a broad and diverse range of geographi

Agents

Epistemic Memory: A Validity Layer for Self-Maintaining Intelligent Systems

arXiv:2510.16899v2 Announce Type: replace Abstract: AI memory mechanisms primarily focus on preserving information content, often neglecting the validity conditions under which knowledge remains appli

agentsarxiv-cs-lg

Escaping Low-Dimensional Overlap: Multi-Task Model Merging via High-Dimensional Sparse Disentanglement

arXiv:2608.25354v1 Announce Type: cross Abstract: Model merging provides an efficient way to construct multi-task generalist models without additional training, but its performance often degrades unde

Evidence-Grounded Mapping of Multimodal Human Sensing Psychological Transdiagnostic Dimensions

arXiv:2608.24903v1 Announce Type: cross Abstract: Mobile and wearable sensing enables longitudinal observation of behavior, yet translating these signals into meaningful mental health constructs remai

Evolutionary chemical learning in dimerization networks

arXiv:2506.14006v2 Announce Type: replace-cross Abstract: We present a framework for chemical learning based on Competitive Dimerization Networks (CDNs) - systems in which multiple molecular species,

EXAONE Tabular 1.0 : Technical Report

arXiv:2608.25774v1 Announce Type: new Abstract: EXAONE Tabular is a compact tabular foundation model family for classification and regression via in-context learning, producing predictions without dat

Hardware

ExFold: Unified Expert Folding for Training-Free MoE Prefill-Decode Acceleration

arXiv:2608.24938v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale capacity for strong quality while keeping per-token compute bounded through sparse expert activation. Yet low-late

hardwarearxiv-cs-lg

Extending Ground-Constraint LiDAR-IMU Calibration to Tilted Surfaces in a Continuous-Time Framework

arXiv:2608.25135v1 Announce Type: new Abstract: This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically ne

researcharxiv-cs-ro

Fairness-Aware Test-Time Prompt Tuning

arXiv:2608.25707v1 Announce Type: new Abstract: Vision-language models have displayed remarkable capabilities in multi-modal understanding and are increasingly used in critical applications where econ

safetyarxiv-cs-lg

FAMPWQ: Fisher Information-based Adaptive Mixed Precision Weight Quantization for Effective LLM Inference

arXiv:2608.24945v1 Announce Type: new Abstract: Recent years have witnessed remarkable achievements of Large Language Models (LLMs) in multiple domains, while the excessive resource requirements of LL

Tutorials

Fast Generative Grasping via Lie Group-Constrained MeanFlow

arXiv:2608.26076v1 Announce Type: new Abstract: Grasp synthesis is a core task in robotic manipulation, for which the solution typically forms a multimodal distribution rather than a point estimate. G

tutorialsarxiv-cs-ro

Fast rates in Bayesian online learning with approximate posteriors

arXiv:2608.25706v1 Announce Type: cross Abstract: Exact Bayes prediction enjoys fast predictive regret guarantees, but exact posterior updating or representation may be too costly for online use. We s

Local Ai

FedQoS: Federated QoS-Risk Learning for Heterogeneous Indoor-Outdoor Access Selection

arXiv:2608.25496v1 Announce Type: new Abstract: Reliable access selection in dynamic and heterogeneous indoor-outdoor environments is challenging because instantaneous radio measurements alone cannot

local-aiarxiv-cs-lg

Finding and using interpretable latents in a neutrino foundation model with sparse autoencoders

arXiv:2608.26090v1 Announce Type: cross Abstract: We present a first application of sparse-autoencoder-based mechanistic interpretability to particle physics. Studying a neutrino foundation model pret

Fine-Tuning Whisper for Automatic Speech Recognition in Baniwa: A Preliminary Study

arXiv:2608.26060v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technologies have achieved remarkable performance in recent years through the use of large multilingual foundation mo

researcharxiv-cs-cl

FinRiskAtlas: Decision-Aligned Evaluation of Large Language Models for Financial Risk Review

arXiv:2608.25325v1 Announce Type: cross Abstract: Deploying large language models for professional financial review requires more than measuring general financial competence: models must perform the s

FlashNormal: Detailed Surface Normal Estimation from Flash and No-Flash Images

arXiv:2608.25360v1 Announce Type: new Abstract: High-quality surface normal estimation is preferred for detailed surface shape recovery and image editing. Existing single image-based methods, though b

applicationsarxiv-cs-cv

Flower Hub: A Reproducible Benchmarking Platform for Federated Learning in Simulation and Deployment

arXiv:2608.25114v1 Announce Type: new Abstract: Federated learning (FL) has emerged as a key approach for training models across decentralized data, yet benchmarking in FL remains difficult to reprodu

Local Ai

FlowMimic: Mask-free Visual Editing and Generation with Pixel-pair Warped Flow Field for Online Video Editing Data Generation and Modality Mimicry

arXiv:2607.18227v2 Announce Type: replace Abstract: In line with the prevailing direction of vision research, we explore the integration of both generation and editing capabilities for video and image

local-aiarxiv-cs-cv

FlowMoDL: Model-Based Deep Learning with Conjugate-Gradient Data Consistency for Highly Accelerated 4D Flow MRI Reconstruction

arXiv:2608.25828v1 Announce Type: new Abstract: We present FlowMoDL, an unrolled neural network for highly accelerated 4D flow MRI reconstruction that directly optimizes for both anatomical magnitude

Forecasting Multiple Observables with SCROLL: Score-Trained Uncertainty for Stochastic Dynamics

arXiv:2608.25898v1 Announce Type: new Abstract: Forecasting a stochastic dynamical system rarely means a single number: one wants several observables---future state, threshold event, regime label---ea

Local Ai

Forecasting Weather-Driven Price Dynamics Across Sri Lankan Tea Market Catalogues

arXiv:2608.24894v1 Announce Type: cross Abstract: The Colombo Tea Auction (CTA) plays a vital role in determining global tea prices, yet the relationship between local weather conditions and price beh

local-aiarxiv-cs-lg

Forge4D: Feed-Forward 4D Human Reconstruction and Interpolation from Uncalibrated Sparse-view Videos

arXiv:2509.24209v2 Announce Type: replace Abstract: Instant reconstruction of dynamic 3D humans from uncalibrated sparse-view videos is critical for numerous downstream applications. Existing methods,

Formal, Executable and Explainable Runtime Monitoring of Spoken Air Traffic Control Operational Procedures

arXiv:2608.25926v1 Announce Type: cross Abstract: Air traffic control procedures are executed through spoken exchanges between controllers and pilots. These interactions are essential to the safety of

FORMSpoT: Revealing Fine-Scale Forest Disturbances from Nation-Wide 1.5 m Forest Canopy Height Time Series

arXiv:2512.17021v2 Announce Type: replace Abstract: Current large-scale satellite-based forest disturbance monitoring systems operate at 10-30~m resolution, too coarse to detect changes at the scale o

FRAME: separating sampling variation from representational cause in medical imaging fairness

arXiv:2608.25981v1 Announce Type: new Abstract: Subgroup performance differences are the standard evidence for fairness bias in medical imaging, and the usual response removes the demographic informat

safetyarxiv-cs-cv

Frequency-aware forecasting for short-term typhoon gust prediction

arXiv:2608.25604v1 Announce Type: new Abstract: Accurate gust forecasting under typhoon conditions remains challenging due to the highly non-stationary and multi-scale characteristics of extreme wind

From Memorization to Absorption: Mixed-Policy RL for Continual Knowledge Injection

arXiv:2608.25243v1 Announce Type: new Abstract: Continual knowledge injection is essential for keeping large language models up-to-date in a fast-evolving world. Existing methods rely on supervised fi

From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset

arXiv:2601.04632v2 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance on many tasks, but their progress remains uneven across languages and cultures, often reflec

From Passive Response to Proactive Correction: Enhancing LLM Robustness Against Input Fact Perturbations

arXiv:2608.25894v1 Announce Type: new Abstract: Large language models (LLMs) frequently produce confident yet factually incorrect responses when user inputs contain misleading premises, a phenomenon w

From Specialization to Generalization: Instruction-tuned LLMs for Robust Harmful Content Mitigation

arXiv:2608.25605v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate impressive performance across a wide range of general NLP tasks; however, their effectiveness in sensitive doma