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arXiv:2608.16101v1 Announce Type: cross Abstract: Coresets distill large datasets into small, representative subsets for efficient downstream learning. Yet Optimal Transport (OT)-based selection typic

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Equilibrium Forcing: Adaptive Video Generation Without Noise Conditioning

DGX agent

arXiv:2608.14706v1 Announce Type: cross Abstract: Standard autoregressive video generation algorithms based on Diffusion and Flow Matching rely on rigid training objectives and static sampling schedul

researcharxiv-cs-ai

18 Aug 2026

Local Ai

EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction

arXiv:2302.12177v4 Announce Type: replace-cross Abstract: Predicting the binding sites of target proteins plays a fundamental role in drug discovery. Most existing deep-learning methods consider a pro

local-aiarxiv-cs-lg

ER-KANs: Efficient and Robust Kolmogorov-Arnold Networks for Data-Scarce Scientific Machine Learning

arXiv:2608.14773v1 Announce Type: cross Abstract: The efficient-KAN literature---covering Chebyshev, wavelet, and radial-basis-function variants of the original Kolmogorov-Arnold Network---has been be

Every Coin Has Two Sides: On the Dual Nature of Generalization in On-Policy Distillation of Large Language Models

arXiv:2608.16647v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher capabilities by supervising trajectories sampled from the student's own policy, yet its generalization be

safetyarxiv-cs-cl

Agents

Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents

arXiv:2608.15071v1 Announce Type: new Abstract: Learning from experience is critical for developing capable, self-improving large language model (LLM) agents. Existing methods typically extract knowle

agentsarxiv-cs-ai

Evolving Executable Pipeline Programs for AutoML with Language Models

arXiv:2608.16416v1 Announce Type: new Abstract: Automated machine learning (AutoML) systems search for pipelines within a space of preprocessing operators, learners, and hyper-parameters specified in

Experimentally Extending Quantum Kernel Learning to Quantum Data by NMR

arXiv:2412.09557v3 Announce Type: replace-cross Abstract: Quantum kernel learning (QKL) promises efficient machine learning by encoding feature maps onto exponentially large Hilbert spaces inherent in

Agents

Explaining Reinforcement Learning Decisions in Self-adaptive Systems

arXiv:2608.14620v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has been extensively used in autonomous and self-* systems, but RL policies, especially deep RL ones relying on neural net

agentsarxiv-cs-ai

FabriMAE I Trust Myself? Self-Evaluating VLA Action Generation with Markov Attention Entropy

arXiv:2608.16697v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) integrate visual perception, language instruction, and action generation into end-to-end policies across heterogene

Feed-Forward Hierarchical Gaussian Diffusion for Extreme CT Reconstruction

arXiv:2608.15343v1 Announce Type: new Abstract: Reconstructing three-dimensional computed tomography (CT) from severely constrained projections is highly ill-posed. Sparse angular sampling, restricted

FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction

arXiv:2608.15727v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for multivariate time-series anomaly detection by learning the distribution of normal data throu

FLEET: Token-Based Feature Extraction for Event Camera-based Reinforcement Learning

arXiv:2608.16523v1 Announce Type: new Abstract: Event cameras generate asynchronous, high-frequency data streams offering spatially sparse information at lower latency than traditional cameras.In prin

Foresight-England: Development of a National-Scale Generative AI Model of Electronic Health Records for Medical Event Prediction across the COVID-19 Pandemic

arXiv:2608.16273v1 Announce Type: cross Abstract: Foresight-England (Foresight-E) is the first national-scale generative foundation model of electronic health records (EHRs), developed as a research p

Forward Pass Domain Adaptation (Without Cross-Layer Backpropagation)

arXiv:2608.14563v1 Announce Type: cross Abstract: Forward-Pass-Only MLP training (FPO) adapts large language models without a backward pass through the model body, achieving 2.7--3.2x the throughput o

Fractional Optimizers Meet Fractal Activation Functions: An Empirical Study of Multi-Scale Optimization in Neural Network

arXiv:2608.14636v1 Announce Type: cross Abstract: Fractional optimization methods and fractal activation functions are two independent directions for improving neural network training. Fractional opti

Frequency and Edge-Guided Segment Anything Model for Remote Sensing Image Semantic Segmentation

arXiv:2608.15054v1 Announce Type: new Abstract: Remote sensing image semantic segmentation (RSISS) has attracted significant attention due to the growing demand for fine-grained land cover information

From Errors to Proofs: Minimal-Core-Guided Repair for Neuro-Symbolic Constraint Solving

arXiv:2608.14771v1 Announce Type: new Abstract: Making language models solve constraint problems reliably often means having them translate the problem into a formal specification and delegating the s

From LLM Inference to Agentic Workloads: Characterization and Implications for Serving Systems

arXiv:2608.15127v1 Announce Type: cross Abstract: Agentic applications are shifting AI serving from isolated model inference to long-running workloads in which LLMs coordinate tools, environments, and

Local Ai

From Sequence to Structure: Relational Uncertainty Propagation for LLM Agents

arXiv:2608.16002v1 Announce Type: cross Abstract: Reliable uncertainty quantification (UQ) is essential for deploying large language model (LLM) agents in complex interactive environments. Existing UQ

local-aiarxiv-cs-ai

FTA-Mem: Fact-Time-Affect Anchored Memory for Low-Density Long-Term Dialogue

arXiv:2608.16303v1 Announce Type: new Abstract: Long-term emotional-support agents require memory mechanisms for personalized understanding across sessions. However, emotional-support dialogue is ofte

researcharxiv-cs-cl

Gathered, Not Admitted: How Attention Brings a Latent Variable into Verbalizable Form

arXiv:2608.15022v1 Announce Type: new Abstract: Language models hold latent quantities in a form they can report on, and more of a quantity is present in that form when the task requires reusing it fl

GaussianDWM++: Language-Grounded 3D Gaussian Driving World Model for Unified Scene Understanding, Editing, and Multi-Modal Generation

arXiv:2608.16234v1 Announce Type: new Abstract: Driving World Models (DWMs) have recently advanced rapidly with generative models, yet most existing methods mainly focus on conditional scene generatio

Generalised Transportability via Causal Abstractions

arXiv:2608.15645v1 Announce Type: new Abstract: Transporting a causal conclusion from a source study population to a target one is a fundamental problem in causal inference. The theory of transportabi

researcharxiv-cs-lg

GenRouter: Unified Workflow Routing for Agentic Image Generation

arXiv:2608.16721v1 Announce Type: new Abstract: The rapid evolution of text-to-image (T2I) generation models has effectively solved the foundational challenge of raw pixel synthesis, shifting the comm

safetyarxiv-cs-cv

GEO-Flag: Detecting and Measuring GEO-Optimized Web Content

arXiv:2608.16824v1 Announce Type: new Abstract: Generative Engine Optimization (GEO) modifies web content to increase its likelihood of being selected and cited by generative search engines. This can

Geometrically Constrained and Token-Based Probabilistic Spatial Transformers

arXiv:2509.11218v2 Announce Type: replace-cross Abstract: Spatial transformations such as rotation and scale obscure the morphological cues needed for accurate image classification. Careful considerat

Geometry-Calibrated Closed-Form Shrinkage for SAR Despeckling

arXiv:2608.15028v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) despeckling is an inverse-recovery problem in which multiplicative non-Gaussian noise must be suppressed without erasing

researcharxiv-cs-cv

Geometry of Forgetting: Representation Flux in Continual Learning

arXiv:2608.15854v1 Announce Type: cross Abstract: Catastrophic forgetting remains a fundamental obstacle to continual learning, where neural networks lose previously acquired knowledge while learning

Local Ai

GLaQ: Grounding Latent Queries in Visual Evidence for Multimodal Reasoning

arXiv:2608.15517v1 Announce Type: new Abstract: Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence

local-aiarxiv-cs-cv

GRIP: Grounded Reasoning via Information-Restricted Premises

arXiv:2608.16776v1 Announce Type: new Abstract: High-capacity encoders in retrieval-augmented generation (RAG) can let the query dominate the latent state, leaving retrieved evidence functionally irre

safetyarxiv-cs-ai

Grounding Robot Generalization in Training Data via Retrieval-Augmented VLMs

model-releasesarxiv-cs-ro

arXiv:2603.11426v3 Announce Type: replace Abstract: Recent work on robot manipulation has advanced policy generalization to novel scenarios. However, it is often difficult to characterize how differen

Guaranteed Adaptive Modality Acquisition: When the Policy Chooses Its Own Calibration Group

arXiv:2608.15520v1 Announce Type: new Abstract: A multimodal system may begin inference holding only some of its inputs and may acquire the rest at a cost. With adaptive acquisition, the policy determ

safetyarxiv-cs-lg

HalluTracer: Hallucination Detection via Depth-Averaging Truth Signals

arXiv:2608.16353v1 Announce Type: cross Abstract: Even well-aligned large language models confidently generate factually incorrect text, making hallucination a persistent reliability risk in high-stak

Handoff-H1: An Orchestrated Vision-Agent System for Material Quantity Takeoff from Construction Blueprints

arXiv:2608.15032v1 Announce Type: cross Abstract: Converting a set of architectural blueprints into a complete material quantity takeoff requires visual perception across drawing sheets, dimensional a

HarmProfile: Characterizing Harmful Distributions in Frontier LLMs

arXiv:2608.14577v1 Announce Type: cross Abstract: Frontier large language models (LLMs) safety evaluation has largely treated harmful generation as an attack outcome rather than as an object of analys

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

model-releasesarxiv-cs-cl

arXiv:2608.15008v1 Announce Type: new Abstract: Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely th

Helios 2.0: A Robust, Ultra-Low Power Gesture Recognition System Optimised for Event-Sensor based Wearables

arXiv:2503.07825v3 Announce Type: replace-cross Abstract: We present an advance in wearable technology: a mobile-optimized, real-time, ultra-low-power event camera system that enables natural hand ges

Hoeffding adaptive splitting trees for data stream classification with concept drift and ensemble learning

arXiv:2608.16659v1 Announce Type: cross Abstract: Ensembles of decision trees are well-established methods for data stream classification. In ensemble learning, Hoeffding Trees are widely adopted as b

How Sampling Strategy Affects Imbalance Mitigation in LiDAR Segmentation: A Study of Structured vs. Random Point-Based Architectures

arXiv:2608.16673v1 Announce Type: new Abstract: Class imbalance in LiDAR point clouds poses challenges for semantic segmentation in autonomous navigation and urban mapping. While 2D vision has numerou

HP2-SLAM: Adaptive Hybrid ICP for Robust and Efficient LiDAR SLAM

model-releasesarxiv-cs-ro

arXiv:2608.14996v1 Announce Type: new Abstract: Achieving robustness, accuracy, and efficiency simultaneously remains a central challenge in light detection and ranging (LiDAR) simultaneous localizati

Hypergraph-based Multimodal Retrieval-Augmented Generation with Incremental Refinement

arXiv:2608.16628v1 Announce Type: new Abstract: Modern Multimodal Retrieval-Augmented Generation (M-RAG) systems are fundamentally limited by the binary connectivity paradigm of traditional simple gra

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities

arXiv:2501.12147v2 Announce Type: replace-cross Abstract: Selecting appropriate training data is crucial for instruction fine-tuning of large language models (LLMs), which aims to (1) elicit strong ca

Intelligent Base Station Deployment in Urban Wireless Networks: A Geographic Data-Informed Digital Twin Approach

arXiv:2608.14599v1 Announce Type: cross Abstract: The placement of base station (BS) is a fundamental determinant of coverage and capacity of urban wireless networks. Yet large-scale BS deployment opt

Intent-Driven Situation Tracking for User-Centric Multi-Turn Agents

arXiv:2608.15755v1 Announce Type: new Abstract: User-centric multi-turn agents must act on an evolving task situation shaped by changing user intents, accumulated tool-grounded facts, missing informat

Iterative Refinement Diffusion for Super-Resolved Data Assimilation of Multiscale Physical Systems

arXiv:2608.14744v1 Announce Type: new Abstract: Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation.

KeyID: Decoupled Drafting and Keyframe Editing for Identity-Preserving Video Generation

arXiv:2608.16154v1 Announce Type: new Abstract: Identity-preserving video generation (IPVG) requires synthesizing videos that are faithful to both reference subjects and text prompts. Existing methods

KHiM-Mamba: Injecting Pathology Knowledge into Mamba via Hidden-State Modulation for Whole Slide Image Analysis

arXiv:2608.14757v1 Announce Type: cross Abstract: Whole slide image analysis is commonly formulated as multiple instance learning (MIL), where instance features are contextually updated and aggregated

researcharxiv-cs-cv