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Language-Grounded Semantic Target Navigation for Autonomous Surface Vehicles

arXiv:2609.14558v1 Announce Type: new Abstract: Autonomous Surface Vehicles (ASVs) are increasingly expected to operate in ports and harbour environments, where operators may specify navigation target

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Language-Guided Representation Learning for Robust Cross-Sensor Material Recognition

DGX agent

arXiv:2609.14783v1 Announce Type: cross Abstract: Robots need touch to manipulate objects safely and reliably, as many properties, such as softness, texture, and contact stability, are hard to infer f

model-releasesarxiv-cs-cl

15 Sept 2026

Agents

Large-FOV RGBD Imaging via Structured PSF Coding in a Bio-inspired Monocentric System

arXiv:2510.25314v2 Announce Type: replace Abstract: High-fidelity large-field-of-view (LFOV) 3D sensing, essential for autonomous platforms, is hindered by the coupling of anisotropic off-axis aberrat

agentsarxiv-cs-cv

Large-scale bioacoustic detection using semantic segmentation: a deep learning framework applied to fin whale calls in ocean-bottom seismometer recordings

arXiv:2609.13281v1 Announce Type: cross Abstract: Ocean-bottom seismometers (OBS), originally deployed for geophysical research, continuously record low-frequency sound for months to years across broa

LayerRoute: Adaptive Layer-Skipping with LoRA-Preserved Quality for Efficient LLM Inference

arXiv:2609.13682v1 Announce Type: cross Abstract: We introduce LayerRoute, a parameter-efficient method for adaptive transformer layer-skipping that combines per-layer hard-gated routing (trained via

Leakage-Safe and Scheduler-Aware Machine Learning for Grid Job Runtime Prediction

arXiv:2609.13701v1 Announce Type: cross Abstract: Accurate job runtime prediction can improve scheduling-aware resource management in grid and distributed computing environments, but prediction models

Learned Bow Control on a Measured Bowed-String Model: a Revised Minimum-Bow-Force Law, a Recurrent Controller, and the Domain of a Supervision Ceiling

arXiv:2609.14990v1 Announce Type: cross Abstract: A finite-difference bowed-string model with implicitly resolved Stribeck friction is presented, with a regime diagnostic, the Schelleng bow-force limi

Learning Agile Flight Maneuvers: Deep SE(3) Motion Planning and Control for Quadrotors

arXiv:2209.11097v2 Announce Type: replace Abstract: Agile flights of autonomous quadrotors in cluttered environments require constrained motion planning and control subject to translational and rotati

Local Ai

Learning-Based Dynamic Obstacle Avoidance for a UAV Using Only Three Range Sensors

arXiv:2609.14426v1 Announce Type: new Abstract: We present a learning-based approach to kinodynamic online motion planning for an Unmanned Aerial Vehicle (UAV) operating at a fixed altitude in unknown

local-aiarxiv-cs-ro

Learning CNF Formulas from Uniform Random Solutions: Near-Tight Sample Complexity for Valiant's Algorithm

arXiv:2609.15268v1 Announce Type: new Abstract: We revisit Valiant's algorithm (Commun. ACM'84) for learning n-variable CNF formulas with clause size k and variable degree d from i.i.d. uniform random

Local Ai

Learning Communication-Conditioned Generative Policies for Decentralized Multi-Agent Collision Avoidance

arXiv:2609.14268v1 Announce Type: new Abstract: In this work, we propose a decentralized communication-conditioned generative framework for multi-agent collision avoidance. Agents generate short-horiz

local-aiarxiv-cs-ro

Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

arXiv:2609.14316v1 Announce Type: new Abstract: Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustwor

researcharxiv-cs-cv

Agents

Learning from Reliable Negatives: Confidence-Anchored Test-Time Adaptation for GUI Grounding

arXiv:2609.15307v1 Announce Type: new Abstract: Graphical User Interface (GUI) grounding is essential for autonomous agents to map natural language instructions to precise screen coordinates. However,

agentsarxiv-cs-cv

Learning Human-Like Badminton Skills for Humanoid Robots

arXiv:2602.08370v2 Announce Type: replace-cross Abstract: Realizing versatile and human-like performance in high-demand sports like badminton remains a formidable challenge for humanoid robotics. Unli

Applications

Learning In-Hand Object Reaching to General 6D Poses

arXiv:2609.13761v1 Announce Type: new Abstract: In-hand manipulation allows multi-fingered dexterous hands to reconfigure grasped objects without releasing and regrasping them. This improves manipulat

applicationsarxiv-cs-ro

Learning Manipulation-Sufficient Representations via Outcome Bottlenecks

arXiv:2609.13235v1 Announce Type: cross Abstract: Networked manipulation endpoints couple perception to actuation across compute- and bandwidth-limited links, yet commonly exchange dense geometric sta

safetyarxiv-cs-cv

Tutorials

Learning Metastable Dynamics

arXiv:2609.14712v1 Announce Type: cross Abstract: Metastability---a phenomenon where systems remain trapped in quasi-stable states before abruptly transitioning under rare perturbations---is ubiquitou

tutorialsarxiv-cs-lg

Learning Multi-Agent Task Assignment and Navigation in the Factory: from Simulation to Real Robots

arXiv:2609.14567v1 Announce Type: cross Abstract: Reinforcement learning (RL) has shown considerable promise for robotic decision-making, yet deploying multi-agent RL (MARL) on physical multi-robot sy

Learning Multimodal One-step Flow Policy via Value-weighted Optimal Transport

arXiv:2609.15883v1 Announce Type: cross Abstract: Offline reinforcement learning aims to learn a policy solely from fixed datasets, which often contain multimodal action distributions. Flow policies c

Learning Source Acquisition Policies by Offline Planning

arXiv:2609.14299v1 Announce Type: new Abstract: Predicting under an acquisition budget requires choosing feature groups whose value can depend on later queries. O-MPAC transfers finite-horizon risk-co

Learning Steerable Clarification Policies with Collaborative Self-play

arXiv:2512.04068v3 Announce Type: replace Abstract: To handle underspecified or ambiguous queries, AI assistants need a policy for managing their uncertainty to determine (a) when to guess the user in

Learning the Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou Trajectories: A Nonlinear Approach using a Deep Autoencoder Model

arXiv:2601.19567v3 Announce Type: replace-cross Abstract: We address the intrinsic dimensionality (ID) of high-dimensional trajectories, comprising n_s = 4,000,000 data points, of the Fermi-Pasta-Ulam

Learning Through Energy Refinement and Manifold Projection: A Cooperative EBM-AE Framework

arXiv:2609.13917v1 Announce Type: new Abstract: Energy-Based Models (EBMs) provide a flexible framework for generative modeling by learning an energy landscape that assigns low energy values to realis

Tutorials

Learning to Coach for Experiential Learning

arXiv:2609.15851v1 Announce Type: new Abstract: Language models can learn from experience, but raw solution trajectories are often too long and noisy to provide effective guidance. In this work, we pr

tutorialsarxiv-cs-cl

Learning to Exploit Passive Dynamics for Energy-Efficient Target Hopping of a Spring-Legged Quadcopter

arXiv:2609.15447v1 Announce Type: new Abstract: Combining aerial thrust with spring-loaded hopping makes monopedal quadcopters promising for locomotion over complex terrain, but heuristic proportional

Learning to Refer from Estimated Listener Gaze

arXiv:2609.14207v1 Announce Type: new Abstract: We propose to finetune vision-language models to generate more pragmatically optimal referring expressions by transforming observations of incremental l

safetyarxiv-cs-cl

Learning to Solve Hard Problems in RL for LLMs by Never Giving Up

arXiv:2609.13443v1 Announce Type: cross Abstract: We demonstrate that training LLMs with RL does not improve performance equally across a dataset. RL shows large improvements on easy problems that an

Learning to Solve Stochastic Controls with Unknown Drifts and Running Rewards: Theory, Algorithms and Convergence

arXiv:2609.14972v1 Announce Type: new Abstract: We study continuous-time and possibly high-dimensional stochastic control problems where drift coefficients and running reward functions are unknown. Du

Learning under Target Shift: Optimal Density Ratio Estimation and Importance-Weighted Regression

model-releasesarxiv-cs-lg

arXiv:2609.15785v1 Announce Type: cross Abstract: We study density ratio estimation and importance-weighted regression under target shift with continuous outputs. Under target shift, the conditional d

Legislating World-Model-Based Planning with Legal Reasoning

arXiv:2609.15113v1 Announce Type: cross Abstract: As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning le

LePlanner: An Iterative Amortized Controller For World Models

arXiv:2609.13845v1 Announce Type: cross Abstract: World models trained with joint-embedding predictive architectures learn compact, structured latent representations from physical interaction, yet pla

Lexical Prompt Compression for Large Language Models: A Training-Free, Deterministic Pipeline with Empirical Pareto Analysis Across Eleven Task Categories

model-releasesarxiv-cs-cl

arXiv:2609.13154v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have made prompts increasingly large and complex. Techniques such as chain-of-thought reasoning (Wei et

LG-VLN: A Zero-Shot Vision-and-Language Navigation Framework with LangGraph State Orchestration

model-releasesarxiv-cs-cv

arXiv:2609.15098v1 Announce Type: new Abstract: Continuous-environment vision-and-language navigation (VLN-CE) requires interpreting natural-language instructions in unseen 3D environments and executi

Lie to me: Detecting Managerial Evasiveness in Earnings Calls via Conversational Audio Encoders

arXiv:2609.13893v1 Announce Type: new Abstract: Earnings conference calls are a primary channel through which managers disclose information under analyst scrutiny. Prior work has linked vocal and lexi

LieSpline-DP: Lie-Group B-Spline Diffusion Policy for Smooth Robot Manipulation

arXiv:2609.15162v1 Announce Type: new Abstract: Diffusion Policy (DP) is a powerful Learning from Demonstration (LfD) method for robotic manipulation, yet it suffers from discontinuous and non-smooth

LiftGCN: Efficient Energy-Preserving Graph Learning via Joukowski Spectral Lifting for Finite Element Stress Prediction

arXiv:2609.14977v1 Announce Type: cross Abstract: Finite element stress fields often exhibit strong local non-smoothness, where stress concentrations near holes, notches, and loading regions induce sh

Lightning Weave: Improving the Accuracy-Efficiency Frontier of Reasoning Models through Capability Composition

arXiv:2609.14708v1 Announce Type: new Abstract: A core goal of efficient reasoning is to improve the accuracy-efficiency frontier. However, jointly improving reasoning accuracy and inference efficienc

Applications

Lightweight Generalized DeepFake Face Detection with WAVIE: Wavelet Augmented Vision Intermediate Embeddings

arXiv:2609.14437v1 Announce Type: cross Abstract: Deepfake detection systems often exhibit significant performance degradation when deployed on unseen manipulation methods, limiting their reliability

applicationsarxiv-cs-ai

LIMBO: Lifelong Inference-Time Memory and Budget Optimization for LLM Agents

arXiv:2609.14138v1 Announce Type: cross Abstract: As LLM agents become integrated into increasingly complex workflows, they must continually acquire new capabilities while retaining competence on prev

Applications

LIMODENet: Attention-Free Compact Encoders for Information-Preserving Onboard Satellite Image Restoration

arXiv:2609.14690v1 Announce Type: new Abstract: Onboard satellites must restore a channel-degraded image on a few watts, using neuromorphic accelerators (e.g., BrainChip Akida, Intel Loihi-2) that sup

applicationsarxiv-cs-cv

Linear Ensemble Sampling with Smaller Ensembles

arXiv:2609.13954v1 Announce Type: new Abstract: Ensemble sampling offers a practical approach to randomized exploration by maintaining a collection of models, but how small an ensemble can be while re

Linearized PINN with pretrained nonlinear layers

model-releasesarxiv-cs-lg

arXiv:2609.14926v1 Announce Type: cross Abstract: We propose a linearized Physics-Informed Neural Network (lPINN), a reduced-order neural basis method for forward and inverse differential equations. I

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

arXiv:2609.13287v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) achieve high decoding efficiency through block-parallel, arbitrary-order generation, making them attractive fo

LLaTSA: Large Language Model-Aligned General-Purpose Transient Stability Analysis

arXiv:2609.14374v1 Announce Type: cross Abstract: Dynamic trajectory prediction has become an important paradigm for data-driven transient stability analysis (TSA), yet most existing predictors remain

LLM-Based Schema-Aware Split Learning for Privacy-Preserving Mental Distress Prediction Across Heterogeneous Surveys

arXiv:2609.15871v1 Announce Type: cross Abstract: Rising societal and lifestyle complexity has been linked to a growing prevalence of mental distress worldwide. Educational institutions, workplaces, c

Agents

LLM-Enhanced Multi-Agent Reinforcement Learning for Unified Electric Vehicles-Charging Station-Grid Optimization in Public Charging Systems

arXiv:2609.13805v1 Announce Type: new Abstract: In the era of the Internet of Things (IoT), coordinating connected electric vehicle (EV) charging scheduling to balance EV charging satisfaction, statio

agentsarxiv-cs-ai

LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers

arXiv:2502.15007v2 Announce Type: replace-cross Abstract: We introduce methods to quantify how Large Language Models (LLMs) encode and store contextual information, revealing that tokens often seen as

LLM Probability Concentration: How Alignment Shrinks the Generative Horizon

arXiv:2506.17871v4 Announce Type: replace-cross Abstract: Despite their impressive capabilities, aligned large language models (LLMs) often generate outputs that lack diversity. What drives this consi