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Learning Deterministic and Stochastic Forced Hamiltonian Systems

model-releasesarxiv-cs-lg

arXiv:2608.19688v1 Announce Type: cross Abstract: We develop a geometric framework for learning deterministic and stochastic forced Hamiltonian systems with neural networks. Motivated by the Lagrange-

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Learning Early-to-Final Solution Consistency for MILP Acceleration

DGX agent

arXiv:2608.19953v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental problem class in operations research and combinatorial optimization, with broad applications to

researcharxiv-cs-ai

21 Aug 2026

Learning Hierarchical Skill Policies with Offline Quality-Diversity Reinforcement Learning

arXiv:2608.19684v1 Announce Type: new Abstract: Recent studies investigate how to leverage pre-collected datasets to improve the policy performance and sample efficiency of RL. One promising approach

safetyarxiv-cs-ai

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

arXiv:2608.19977v1 Announce Type: new Abstract: Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots ha

Learning how to Forget: Fine-tuning for Long-Context Sparse Attention

arXiv:2608.19920v1 Announce Type: new Abstract: A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer langua

safetyarxiv-cs-cl

Learning piecewise-smooth dynamical systems

model-releasesarxiv-cs-lg

arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine lear

Learning the Right Abstraction: Neural Reduced Dynamics for Complex Robot Control

arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for l

Learning to Beat: Phenotype-Guided Latent Flow with Regional Motion Priors for Biventricular Motion Synthesis

arXiv:2608.19738v1 Announce Type: cross Abstract: Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes

Learning Vision-Driven Reactive Soccer Skills for Humanoid Robots

arXiv:2511.03996v2 Announce Type: replace Abstract: Humanoid soccer poses a representative challenge for embodied intelligence, requiring robots to coordinate agile locomotion with unreliable visual p

Learning When to Think: Adaptive Reasoning for Test-Time Compute Allocation

arXiv:2608.20256v1 Announce Type: new Abstract: Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather than an explicitly adaptive one, which

safetyarxiv-cs-ai

Tutorials

Let's Scale Step by Step: Compute-Efficient Hyperparameter Transfer for Large-Scale Mixture-of-Experts

arXiv:2608.20061v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing

tutorialsarxiv-cs-ai

LF-GICP: Parameter-Free Degeneracy-Aware LiDAR Odometry via a Voxel-Normal Localizability Field

model-releasesarxiv-cs-cv

arXiv:2608.19522v1 Announce Type: cross Abstract: Scan-to-map LiDAR odometry drifts unboundedly along the unobservable axes of geometrically degenerate environments like tunnels and corridors, and exi

Linguistic Holonomy and Statistical Watermarks: Inner Geometry of Meaning-Preserving Transformations

arXiv:2608.19369v1 Announce Type: new Abstract: Statistical watermarks for language models live in the freedom of the signifier: they choose among tokens that are nearly equivalent in meaning, and the

researcharxiv-cs-cl

Tutorials

Listening Forward: Next Patch Embedding Prediction Enables Scalable Audio Learners

arXiv:2608.19863v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has driven substantial progress in audio representation learning, though existing methods have increasingly relied on e

tutorialsarxiv-cs-ai

Applications

LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection

arXiv:2608.19463v1 Announce Type: new Abstract: Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple mar

applicationsarxiv-cs-lg

LLMs as Acquisition Policies for Finite-Pool Materials Optimization: A Controlled Study

arXiv:2608.19790v1 Announce Type: new Abstract: Discovering materials with desirable properties often requires searching large candidate spaces while experimental or computational evaluations remain c

Longitudinal Bayesian Learning of Continuous Disease Position across the Alzheimer's Disease Continuum

arXiv:2608.19436v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remai

LoRA-GA^2: Low Rank Adaptation with Multi-step Gradient Adaptive Alignment

arXiv:2608.19800v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However

Loreley: Repository-Scale Program Evolution with Quality-Diversity Search

arXiv:2608.19703v1 Announce Type: cross Abstract: Sequential agent search accumulates changes from its current champion but discards alternative branches; independent proposals preserve breadth but re

safetyarxiv-cs-ai

M3: A State-Event Generative Foundation Model for Market Microstructure Dynamics

arXiv:2608.19227v1 Announce Type: cross Abstract: Market microstructure simulation aims to model how liquidity, prices, and order flow evolve in electronic financial markets. Since market data reveal

researcharxiv-cs-lg

Magnetically Self-Sealed MR Haptic Actuator With PWM-Based Excitation and High-Fidelity Torque Control

arXiv:2608.19635v1 Announce Type: new Abstract: Accurate and stable torque rendering is essential for safe and perceptive human--machine interaction. Magnetorheological fluid (MRF)-based actuators off

researcharxiv-cs-ro

MaliciousSkillBench: A Comprehensive Benchmark for Malicious Agent Skill Detection

arXiv:2608.19901v1 Announce Type: cross Abstract: Agent Skills extend LLM agents with reusable instruction packages that may also include scripts, resources, and service configuration. This creates a

MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal Prostate MRI Segmentation

arXiv:2510.17529v3 Announce Type: replace-cross Abstract: Active Surveillance (AS) is a treatment option for managing low and intermediate-risk prostate cancer (PCa), aiming to avoid overtreatment whi

Manifold Drift in Flow Preference Optimization: A Root Cause of Reward Hacking

arXiv:2608.20011v1 Announce Type: new Abstract: Preference optimization is a standard alignment method for generative models, yet extending it to continuous-time dynamics remains non-trivial. In flow

Mapping General-Purpose AI Governance in Twenty AI Middle-Power Jurisdictions

arXiv:2608.19278v1 Announce Type: cross Abstract: The most capable general-purpose AI (GPAI) models are mostly built in two jurisdictions, the United States and China, but the risks they carry land gl

Maximum Likelihood Reinforcement Learning

arXiv:2602.02710v2 Announce Type: replace Abstract: Reinforcement learning (RL) is the method of choice for training models in setups where the objective function can only be evaluated by sampling fro

researcharxiv-cs-lg

Measuring What a Specification Determines: A Formal Semantic-Block Model and an Execution-Judged Benchmark

arXiv:2608.19475v1 Announce Type: cross Abstract: This work introduces a formal semantic-block model for specifications and an execution-judged benchmark for evaluating specification quality independe

Mechanistic Tomography: Designed Measurement for Control-Oriented Interpretability

arXiv:2608.19338v1 Announce Type: cross Abstract: Mechanistic interpretability seeks quantities that models do not expose directly: represented states, component effects, interactions, and responses t

Tutorials

MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use

arXiv:2608.20202v1 Announce Type: new Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing

tutorialsarxiv-cs-ai

Merge Now, Regret Later: The Hidden Cost of Model Merging Is Adversarial Transferability

arXiv:2509.23689v2 Announce Type: replace Abstract: Model Merging (MM) has proven to be an effective alternative to multi-task learning, where several fine-tuned models are merged, without access to t

safetyarxiv-cs-lg

Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves

arXiv:2608.19419v1 Announce Type: cross Abstract: Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have t

researcharxiv-cs-lg

Agents

MidTool: Mid-training Data Synthesis for Agentic Tool Use

arXiv:2608.20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models. Recent work has shown that targeted m

agentsarxiv-cs-ai

MILD: Tractable Terrain Modeling for Learning Improved Bipedal Locomotion on Deformable Surfaces

arXiv:2608.19955v1 Announce Type: new Abstract: Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold

researcharxiv-cs-ro

Local Ai

MileGPO: Milestone Inference with Local Evidence for Graph-Based Policy Optimization of Long-Horizon LLM Agents

arXiv:2608.19803v1 Announce Type: cross Abstract: Credit assignment is challenging in long-horizon agentic reinforcement learning, where supervision often comes only from final rewards. Existing metho

local-aiarxiv-cs-ai

Mitigating GenAI-Powered Evidence Pollution for Out-Of-Context Misinformation Detection

model-releasesarxiv-cs-cl

arXiv:2501.14728v2 Announce Type: replace-cross Abstract: While generative artificial intelligence (GenAI) models have achieved significant success, their misuse for generating deceptive content raise

Mitigating Identity Essentialism in LLM Agents with Longitudinal Life Trajectories

arXiv:2608.19621v1 Announce Type: new Abstract: Large language models (LLMs) offer a scalable approach to social simulation, but their credibility depends on how agents are constructed. Existing metho

safetyarxiv-cs-cl

Mix&Fix-Net: A Dual-Stage Trajectory Prediction Model for AIS and Vision-Derived Vessel Data

arXiv:2608.19580v1 Announce Type: new Abstract: Vessel trajectory prediction is critical for maritime safety and accident prevention. While most existing trajectory prediction models rely on Automatic

safetyarxiv-cs-cv

Model-Less Feedback Control of Space-based Continuum Manipulators using Backbone Tension Optimization

model-releasesarxiv-cs-ro

arXiv:2512.06754v2 Announce Type: replace Abstract: Continuum manipulators offer intrinsic dexterity and safe geometric compliance for navigation within confined and obstacle-rich environments. Howeve

MOSAIC: Modality-agnostic Spectral Alignment for Federated Image-level Weakly Supervised Tumor Segmentation under Client-specific Missing Modalities

arXiv:2608.19788v1 Announce Type: cross Abstract: Trustworthy multimodal fusion in clinical settings requires handling incomplete and heterogeneous modality subsets across institutions, where privacy

safetyarxiv-cs-cv

Multi-Agent Orchestration with the Common-Sense Reasoning Capabilities of LLMs for Autonomous Driving

arXiv:2608.20129v1 Announce Type: cross Abstract: Autonomous vehicles require robust perception and decision-making capabilities to operate in diverse and unseen scenarios. While reinforcement learnin

safetyarxiv-cs-cl

Multi-Method Causal Evidence Synthesis: Ranking Candidate Drivers by Convergent Cross-Method Evidence from Observational Data

arXiv:2608.20187v1 Announce Type: cross Abstract: Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an

Applications

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

arXiv:1905.11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban c

applicationsarxiv-cs-lg

Multi-Source Wasserstein Distributionally Robust Graph Learning

arXiv:2608.19914v1 Announce Type: new Abstract: Network topology inference from graph signals is central to graph signal processing with applications in neuroscience, sensor, and social networks. In p

safetyarxiv-cs-lg

Multi-Tool Robotics Enables In-Situ Sample Manipulation for Time-Resolved Synchrotron Measurements

arXiv:2608.19280v1 Announce Type: cross Abstract: The high photon flux at synchrotron beamlines allows for the measurement of fast dynamical processes. However, beamline radiation-safety protocols pro

Multimodal Trajectory Planning for Surface Vehicles using Turning Circle-based Control Barrier Functions

arXiv:2608.19537v1 Announce Type: new Abstract: This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The pr

MUST-PET: MUltimodal Self-supervised learning across Tracers for whole-body PET/CT-based lesion segmentation

arXiv:2608.19666v1 Announce Type: new Abstract: Deep learning-based whole-body PET-CT lesion segmentation can support cancer staging, treatment planning, and response assessment, but generalization is

researcharxiv-cs-cv

Natural Language Code Retrieval for 1C:Enterprise: An Open Benchmark and Efficient Bi-Encoder

model-releasesarxiv-cs-cl

arXiv:2608.19957v1 Announce Type: new Abstract: Natural language code retrieval is a rapidly evolving task in computer science. However, the 1C:Enterprise ecosystem combines Russian syntax with highly

NepOOC-M: Bilingual Nepali-English Benchmark and Comparative Analysis of Multimodal Architectures for OOC Detection

model-releasesarxiv-cs-cl

arXiv:2608.19212v1 Announce Type: new Abstract: Out-of-context (OOC) misinformation pairs authentic images with misleading captions to construct false narratives without image manipulation, making det