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RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction

arXiv:2608.06259v1 Announce Type: new Abstract: Reaction yield prediction remains challenging because labeled data are scarce and reaction space is both combinatorially large and sparsely populated, l

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Tutorials

Shaping Human-AI Interactions to Provide Improvement Pathways and Balance Competing Objectives

DGX agent

arXiv:2608.05710v1 Announce Type: new Abstract: When an AI system is deployed, the individuals who use and or are evaluated by it form beliefs about how the system operates and use those beliefs to st

tutorialsarxiv-cs-ai

7 Aug 2026

Spectral Aliasing Pretext: A novel task for Self-Supervised fault diagnosis in rotating machinery

arXiv:2608.05705v1 Announce Type: cross Abstract: Deep learning is a new way for machinery fault diagnosis but requires extensive labeled data, a scarce resource in industrial settings. We propose Spe

Spectral Distillation: From Nonlinear Dynamics to Linear State-Space Models

arXiv:2608.05416v1 Announce Type: new Abstract: Can nonlinear dynamical systems be learned through a compact linear state-space representation, without directly solving a non-convex system-identificat

SR-JEPA: Learning Predictive Latent State in 3D Scenes

arXiv:2608.05774v1 Announce Type: new Abstract: Joint-embedding predictive architectures learn by predicting latent representations of missing observations, yet many masked JEPAs are evaluated primari

STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts

arXiv:2602.14265v3 Announce Type: replace Abstract: Inference-Time-Compute (ITC) methods like Best-of-n and Tree-of-Thoughts are meant to produce output candidates that are both high-quality and diver

Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

arXiv:2608.06276v1 Announce Type: cross Abstract: Persistence diagrams (PDs) provide stable and interpretable summaries of multiscale topological structure. While substantial progress has been made in

Stochasticity Is Not the Hard Part: Reduction and Complexity in Instructional Sequencing over Prerequisite DAGs

arXiv:2608.05455v1 Announce Type: new Abstract: When a student must learn concepts connected by prerequisite dependencies, when does the order of instruction matter, and what does it cost to find the

VLAff: Vision-Language-Affordance Model for Unified Actionable Affordances

arXiv:2608.05215v1 Announce Type: cross Abstract: Learning manipulation skills from human videos is promising for scalable robot learning. However, the embodiment mismatch between humans and robots ma

An entropic explanation of insistence on sameness in autism

arXiv:2608.04616v1 Announce Type: new Abstract: An information theory-based framework is proposed in attempt to explain insistence on sameness in autism as an instance of a general behavior pattern in

Dense Metric Depth Completion from Sparse Direct Time-of-Flight Sensors

arXiv:2608.04737v1 Announce Type: new Abstract: Direct Time-of-Flight (dToF) sensors provide highly accurate metric depth and are more robust than indirect ToF systems in challenging real-world condit

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds

arXiv:2608.04827v1 Announce Type: cross Abstract: We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with ge

Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics

arXiv:2607.18559v2 Announce Type: replace-cross Abstract: Gaussian graphical model selection is usually studied under independent sampling, but in many applications the data arise as a single trajecto

NeuMoSync: End-to-End Neuromodulatory Control for Plasticity and Adaptability in Continual Learning

arXiv:2608.04358v1 Announce Type: new Abstract: Continual learning (CL) requires models to learn tasks sequentially, yet deep neural networks often suffer from plasticity loss and poor knowledge trans

NodeJEPA: Structure-Conditioned Latent Prediction for Node-Level Graph Self-Supervised Learning

arXiv:2608.04381v1 Announce Type: cross Abstract: Self-supervised learning on graphs is largely shaped by contrastive methods that depend on carefully designed augmentations, and by generative methods

SJEPA: Learning Elegant Latent Dynamics with Hybrid Symbolic-Neural Predictors

arXiv:2608.04060v1 Announce Type: cross Abstract: Joint-embedding predictive architectures learn abstract states by predicting target embeddings from context embeddings, but their transition models ar

Spatiotemporal Graph Transformer for Traffic Intelligence in Edge Computing

arXiv:2608.04075v1 Announce Type: cross Abstract: Accurate traffic forecasting is essential for proactive resource management in edge computing, where service demand evolves dynamically across both sp

SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding

arXiv:2608.04676v1 Announce Type: new Abstract: Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis

Unforgettable Generalization in Language Models

arXiv:2409.02228v2 Announce Type: replace-cross Abstract: When language models (LMs) are trained to forget (or 'unlearn'') a skill, how precisely does their behavior change? We study the behavior of t

VQ-VAD: Vector-quantized Motion Representation Learning for Human-centric Video Anomaly Detection

arXiv:2608.05069v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) is inherently challenging due to the scarcity of anomalies and the large visual variability in surveillance footage, inc

When Diffusion Models Forget Who You Are: Identity Preservation in Face Inpainting under Large Occlusions

arXiv:2608.04820v1 Announce Type: new Abstract: Face inpainting with diffusion models has recently achieved impressive visual quality, yet preserving identity fidelity under significant occlusion and

Zero-shot Sim2Real Transfer for Magnet-Based Tactile Sensor on Insertion Tasks

arXiv:2505.02915v2 Announce Type: replace Abstract: Tactile sensing is an important sensing modality for robot manipulation. Among different types of tactile sensors, magnet-based sensors, like u-skin

tutorialsarxiv-cs-ro

A New Theory of Value for Post-AGI Economics

arXiv:2608.01432v2 Announce Type: replace Abstract: Artificial general intelligence (AGI) may weaken scarcities in labour, expertise, information, and productive capability that underpin established t

Agogic: Performance-Timed Music Tokens for LLM-Native Text-to-Symbolic-Music Generation

arXiv:2608.03999v1 Announce Type: cross Abstract: Text-to-music language models begin with a choice usually made by default: how to tokenize music. Normally entangled with backbone, data, and recipe,

AI Sandbox: Technical Report

arXiv:2608.02679v1 Announce Type: cross Abstract: Collaborative AI experimentation across industry and academia requires platforms that enable rapid prototyping while preserving controlled access, ten

Causal Inference with Unstructured Outcomes

arXiv:2608.03085v1 Announce Type: cross Abstract: Causal inference has traditionally centered on scalar outcomes: whether a patient recovers, how much a worker earns, or how many visits a website rece

CRIL-U-Net: Compact Ratio-Interaction Learning for Focal Cortical Dysplasia Segmentation from T1w and FLAIR MRI

arXiv:2608.03185v1 Announce Type: new Abstract: Focal cortical dysplasia (FCD) type II is an important structural cause of drug-resistant focal epilepsy, but its small size, heterogeneous appearance,

DiffImaginE: Imagine to Verify Entity Types with Diffusio

arXiv:2608.03025v1 Announce Type: new Abstract: Multimodal named entity recognition (MNER) determines whether each candidate span and entity-type hypothesis is supported by joint textual and visual ev

Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model

arXiv:2608.03566v1 Announce Type: cross Abstract: The drift diffusion model (DDM) is a cornerstone of cognitive decision-making research. Although numerous estimation methods exist, researchers contin

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density

arXiv:2608.03260v1 Announce Type: new Abstract: Pretraining has shown strong potential for learning transferable representations, yet it remains underexplored for electron-density-based molecular lear

FedCARE: A Multi-Objective Personalised Federated Learning Framework for Smart Healthcare

arXiv:2608.03498v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training across distributed healthcare institutions without centralising sensitive patient data. How

From SQL Errors to Concept Gaps: An AI-Powered Knowledge Graph Analytics Platform for Personalized Feedback

arXiv:2608.03118v1 Announce Type: new Abstract: This innovative practice full paper describes an AI-powered knowledge graph platform that connects SQL errors to conceptual gaps in undergraduate and gr

GraspMeanFlow: SE(3)-Equivariant MeanFlow for Few-Step 6-DoF Grasp Generation

arXiv:2608.03295v1 Announce Type: new Abstract: Recent data-driven methods for synthesizing 6-DoF grasp poses use generative models to learn complex grasp pose distributions and generate diverse candi

tutorialsarxiv-cs-ro

GVCCTurbo: Rate-Compute Quality Scheduling for Codebook Driven Generative Compression

arXiv:2608.03517v1 Announce Type: new Abstract: Codebook-driven generative compression uses a pretrained image or video generator as a zero-shot visual prior and transmits compact codebook indices to

Human Centric Embodied Intelligence for Soft Wearable Robotics

arXiv:2608.03556v1 Announce Type: new Abstract: Soft wearable robots have evolved rapidly from proof-of-concept devices into promising platforms for rehabilitation, occupational assistance, and human

tutorialsarxiv-cs-ro

Measuring Explainer Stability via Attribution Separability

arXiv:2608.02697v1 Announce Type: cross Abstract: Attribution methods (AMs) assign an importance score to each feature and are widely adopted to explain black-box models. However, most methods can pro

MIMIC-MJX: Neuromechanical Emulation of Animal Behavior

arXiv:2511.20532v3 Announce Type: replace-cross Abstract: The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavi

Neurosymbolic Reasoning with Incremental Knowledge for Sample Efficient Hierarchical Reinforcement Learning

arXiv:2608.02993v1 Announce Type: new Abstract: (Flat) Reinforcement Learning (RL) agents face significant challenges in environments with sparse rewards that require long-horizon reasoning. A compell

Oh Deer, How Should I Handle This? Seasonal Priors for Selective Wildlife Annotation and Classification

arXiv:2608.02762v1 Announce Type: new Abstract: Fine-grained wildlife classification in aerial imagery is limited not only by model performance, but also by unreliable labels: animals occupy few pixel

Population-Robust Feature Selection via Generalized Welfare Optimization

arXiv:2608.02887v1 Announce Type: new Abstract: Choosing which features to collect is a deployment decision: the same limited questionnaire, test panel, or sensor set may need to serve several heterog

Progressive Learning of a Diffusion-based Inpainting Model for Separating Overlapped Fingerprints

arXiv:2608.03937v1 Announce Type: new Abstract: Overlapped friction ridge patterns are a recurring problem in latent fingerprints recovered from crime scenes and in live-scan scenarios where residual

Revisiting TD Target Aggregation under Uncertainty in Q-Learning

arXiv:2608.03069v1 Announce Type: new Abstract: Deep Q-Networks (DQNs) learn value functions through bootstrapped temporal-difference updates, where future returns are approximated using a greedy maxi

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve

arXiv:2608.03550v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting remains the standard baseline for evaluating models' reasoning abilities. Originally, this technique was introduced to

Sparse Weight Decomposition for Efficient Circuit Extraction

arXiv:2608.03913v1 Announce Type: cross Abstract: Dense pretrained transformers do not naturally expose interpretable units for circuit extraction. Existing approaches obtain such units by learning au

Style-Aware Gloss Control for Generative Non-Photorealistic Rendering

arXiv:2602.16611v3 Announce Type: replace-cross Abstract: Humans can infer material characteristics of objects from their visual appearance, and this ability extends to artistic depictions, where simi

TaskPress: Query-Agnostic KV Cache Compression via Task-Guided Pruning

arXiv:2608.03276v1 Announce Type: new Abstract: Long-context inference with large language models is constrained by the linear growth of the key-value cache to sequence length. While pruning offers mi

AdaForensics: Learning A Characteristic-aware Adaptive Deepfake Detector

arXiv:2608.02160v1 Announce Type: new Abstract: In this paper, we propose a characteristic-aware adaptive network named AdaForensics for deepfake detection. Most existing methods learn a fixed network