Search: “models”

MDKeyChunker: What Does One LLM Call per Chunk Buy for Markdown Retrieval?

arXiv:2603.23533v3 Announce Type: replace-cross Abstract: Markdown carries structure a parser reads for free: headers, section paths, and block boundaries. Many RAG pipelines also spend LLM calls per

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MemPilot: Orchestrating On-Demand Multimodal Memory Curation for LLM Agents

DGX agent

arXiv:2610.06830v1 Announce Type: cross Abstract: Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent me

safetyarxiv-cs-lg

6 Oct 2026

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

local-aiarxiv-cs-lg

Mind the Drift: Diagonal Linear Networks Under Large Learning Rates

arXiv:2610.06120v1 Announce Type: new Abstract: Large learning rates can qualitatively change the trajectory of neural network training, often pushing optimization into regimes far from classical grad

Monocular markerless biomechanics for clinically interpretable gait assessment in spinal cord injury

arXiv:2610.05552v1 Announce Type: new Abstract: Three-dimensional gait analysis guides rehabilitation after spinal cord injury but depends on marker-based motion capture and force plates, which few cl

Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data

arXiv:2610.06389v1 Announce Type: new Abstract: Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context. However, learning both tasks i

NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis

arXiv:2610.04722v1 Announce Type: new Abstract: Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, maki

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

local-aiarxiv-cs-ro

Optimal Oracle Complexity for Finite-Sum Monotone Inclusions

arXiv:2610.05038v1 Announce Type: cross Abstract: We present an oracle-optimal method for finite-sum monotone inclusions under mean-square Lipschitz continuity. Our switching regularization method fin

Optimizer Geometry Sets the Pace: Spectral Learning Dynamics in Matrix Factorization

arXiv:2610.04249v1 Announce Type: new Abstract: Recent successes of matrix- and curvature-based optimizers have renewed interest in how update geometry shapes learning. These methods normalize or prec

Order Matters: Competition-Guided Query Ordering for RNN-Based Object Detection

arXiv:2610.05191v1 Announce Type: new Abstract: DETR-style detectors use one-to-one bipartite matching during training to assign object queries to ground-truth objects, enabling end-to-end set predict

Tutorials

Out-of-control Hamiltonian Learning

arXiv:2610.06709v1 Announce Type: cross Abstract: Learning the Hamiltonian of a many-body system from its dynamics is a central task in quantum science, yet the algorithms with the strongest provable

tutorialsarxiv-cs-lg

Outcome-Guided On-Policy Self-Distillation

arXiv:2610.05070v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) provides denser token-level supervision and better computational efficiency than Reinforcement Learning with Verifiab

Agents

Pareto-Dominant Clarification: Post-Training Coding LLMs via PPO-Lagrangian Budget Constraints

arXiv:2610.04089v1 Announce Type: new Abstract: Coding agents operating under ambiguous instructions or user prompts must decide whether to ask clarifying questions or attempt a solution directly. Whi

agentsarxiv-cs-lg

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

local-aiarxiv-cs-lg

Physics is the Best Teacher: Consistency Learning for Time-Invariant Operators of Chaotic Dynamics

arXiv:2610.04108v1 Announce Type: new Abstract: Accelerating the prediction of long-term behavior in chaotic systems is crucial in scientific computing. However, existing methods rely on numerical sol

PlatoLTL: Scaling LTL-Guided Multi-Task RL

arXiv:2601.22891v3 Announce Type: replace Abstract: Linear temporal logic (LTL) has emerged as a powerful formalism for specifying structured, temporally extended tasks in multi-task reinforcement lea

Poisson-GENERIC Neural Operators: Exact Metriplectic Structure in Function Space via Casimir Entropies

arXiv:2610.05570v1 Announce Type: new Abstract: Existing thermodynamically consistent neural operators impose the GENERIC degeneracy conditions by projecting the reversible operator onto the complemen

Polynomial neural surrogates for designing photonic quantum experiments

arXiv:2610.06032v1 Announce Type: cross Abstract: Physics simulators can support the discovery of quantum experiments by predicting the states generated by experimental configurations. When these simu

Prompt Dominance and Asymmetric Verifier Costs: Empirical Ablations of GRPO at 1B Scale on GSM8K

arXiv:2610.04928v1 Announce Type: new Abstract: This paper studies GRPO at 1B scale from both directions: what estimator choices do to the learning signal, and what a degraded reward signal does to wh

RAGrasp: Geometry-Semantic Template Retrieval and Grasp Transfer

arXiv:2610.04438v1 Announce Type: cross Abstract: We present RAGrasp, a retrieval-augmented pipeline for planar parallel-jaw grasping from a compact set of locally collected, grasp-annotated RGB-D (co

local-aiarxiv-cs-ro

Ramp Metering Control via Hybrid State Deep Reinforcement Learning in Partially Observable Connected Vehicle Environments

arXiv:2610.06266v1 Announce Type: new Abstract: Freeway on-ramp merges are major sources of congestion, causing significant economic and environmental costs. While Deep Reinforcement Learning (DRL) of

Referring Multi-Object Tracking in Moving-Camera Videos via Global Motion Compensation

arXiv:2610.04185v1 Announce Type: new Abstract: Referring multi-object tracking (RMOT) takes a video and a language expression as input and tracks all referred objects. Many tracking requirements invo

Relational Synthesis: Structure-Mediated Concatenative Synthesis for Foley and Retrieval-Augmented Audio Generation

arXiv:2610.05768v1 Announce Type: cross Abstract: We ask: given a retrieved source audio S and a separate reference audio R, can we synthesize novel audio Y out of this pair (S,R) such that Y remains

Residual Visual Credit Optimization: Conserved Evidence Routing for Multimodal Reinforcement Learning

arXiv:2610.04918v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards scales multimodal reasoning, but an outcome reward says how much a trajectory is worth, not how that valu

local-aiarxiv-cs-lg

Revealing After Overwriting: An Exponential POMDP OPE Lower Bound under History-Dependent Logging

arXiv:2610.05063v1 Announce Type: new Abstract: Multi-step revealing can make off-policy evaluation tractable under memoryless logging. With history-dependent logging, state decodability and target-re

Robot Learning with Visual Predicted Force

arXiv:2610.04741v1 Announce Type: new Abstract: Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through

safetyarxiv-cs-ro

Robust Local Optimization Done Right

arXiv:2610.05743v1 Announce Type: new Abstract: RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.

local-aiarxiv-cs-cv

Robust Tensor Completion via Reflective Convolution Nuclear Norm Minimization

arXiv:2610.04979v1 Announce Type: new Abstract: Robust tensor completion recovers multidimensional data from partial observations corrupted by sparse gross errors. Existing convolutional low-rank mode

Tutorials

S^3N: A Spherical Spiral Scanning Network for Weather Forecasting

arXiv:2610.04338v1 Announce Type: new Abstract: Machine learning-based weather prediction (MLWP) has achieved strong performance in global weather forecasting. Recent Hierarchical Equal Area isoLatitu

tutorialsarxiv-cs-lg

Scalable Minimal-Change Learning for Controllable Image Editing

arXiv:2610.06021v1 Announce Type: new Abstract: Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended

local-aiarxiv-cs-cv

Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training

arXiv:2610.05831v1 Announce Type: new Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study t

Shadow Feature Refinement Network: Progressive Feature Refinement based on Knowledge Distillation for Effective Shadow Removal

arXiv:2610.05325v1 Announce Type: new Abstract: In the field of deep learning, has seen significant advancements; however, shadow removal remains a persistent challenge owing to the variable sizes and

Agents

SPACE-CLIP: Spatial Perception via Adaptive CLIP Embeddings for Monocular Depth Estimation

arXiv:2601.17657v4 Announce Type: replace Abstract: Robotic and autonomous systems need dense spatial cues, yet adding a dedicated depth estimator can duplicate visual processing already performed by

agentsarxiv-cs-cv

Sparse Calibration-Based Personalization of Kernel-Based Gait Phase and Speed Estimation Using Wearable IMUs

arXiv:2610.03931v1 Announce Type: new Abstract: This paper presents sparse calibration-based personalization for kernel-based gait phase and walking speed co-estimation from wearable inertial measurem

researcharxiv-cs-ro

Stability and Generalization of Stochastic Nonconvex Optimization under Heavy-Tailed Noise: From Gradient Norm to Goldstein Stationarity

arXiv:2601.19730v2 Announce Type: replace Abstract: The empirical evidence indicates that stochastic optimization with heavy-tailed gradient noise is more appropriate to characterize the training of m

Stability-Shaped Deep Graph Learning

arXiv:2610.06344v1 Announce Type: new Abstract: In deep graph neural networks, increasing depth enlarges the receptive field but often leads to over-smoothing, where node representations tend to align

Strategic Multi-Agent Learning for Interpretable Action Valuation of All Players in Football

arXiv:2610.05961v1 Announce Type: new Abstract: Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioni

Applications

Structural Foundations of Nonlinear Systems with Unknown Inputs: The UID-Induced Normal Form and Minimal-Sensing Structure-from-Motion

arXiv:2610.05939v1 Announce Type: cross Abstract: This paper establishes the first general structural solution to the problem of state estimation for nonlinear systems driven by unknown inputs. Buildi

applicationsarxiv-cs-cv

Agents

Synergizing Drone Delivery Order Pooling and Road Network Monitoring through Monitoring-Task Orderization

arXiv:2610.05270v1 Announce Type: cross Abstract: This paper investigates the real-time dispatch of a shared drone fleet for on-demand food delivery and urban road network monitoring. We consider a co

agentsarxiv-cs-lg

TAME:Topology-Aware Text-Driven Motion Editing across Heterogeneous Humanoid Skeletons

arXiv:2610.04529v1 Announce Type: new Abstract: Text-driven motion editing modifies an existing motion sequence according to a text instruction while preserving the content of the source motion. Exist

safetyarxiv-cs-cv

Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes

arXiv:2610.03824v1 Announce Type: cross Abstract: Treatment efficacy is traditionally demonstrated on the basis of a single primary outcome. However, clinical decision-making usually requires consider

Task-Error Residual Learning for Real-Robot Five-Ball Juggling

arXiv:2606.16978v2 Announce Type: replace-cross Abstract: For residual learning that refines existing behavior, sample efficiency depends on two things: how much information each rollout returns, and

TDC: Sim-to-Real Transferable Directional Compliance for Contact-Rich Manipulation

arXiv:2602.14174v2 Announce Type: replace Abstract: Contact-rich manipulation requires robots to regulate both motion and interaction forces, yet achieving adaptive compliance remains a fundamental ch

safetyarxiv-cs-ro

Textual Echo Cancellation

arXiv:2008.06006v5 Announce Type: replace-cross Abstract: In this paper, we propose Textual Echo Cancellation (TEC) - a framework for cancelling the text-to-speech (TTS) playback echo from overlapping

The Value of Information in Resource-Constrained Pricing

arXiv:2603.24974v2 Announce Type: replace-cross Abstract: Firms that price perishable resources -- airline seats, hotel rooms, seasonal inventory -- now routinely use demand predictions, but these pre

Topology-Informed Prompt-Conditioned Universal Segmentation of Uterine Structures from Ultrasound and MRI

arXiv:2610.06494v1 Announce Type: new Abstract: Multi-structure segmentation of the uterus is important for computer-assisted screening, diagnosis, and treatment planning of uterine diseases, where ul

Towards Optimal Valve Prescription for Transcatheter Aortic Valve Replacement (TAVR) Surgery: A Machine Learning Approach

arXiv:2512.09198v2 Announce Type: replace Abstract: Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a l