Search: “models”

JSIR: An Audio-Aligned, Multi-Task Dataset of Jazz Standard Recordings

arXiv:2610.15356v1 Announce Type: cross Abstract: Beat tracking, chord estimation, and structure analysis are staple tasks of music information retrieval. Their datasets are drawn largely from Western

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Just Respect the Semantics: Image-Token Compression via Pre-LLM Semantic Variable-Resolution Tokenization and In-LLM Relevance Pruning

DGX agent

arXiv:2610.18690v1 Announce Type: new Abstract: Image-token compression must reduce computation without hurting the semantics. We introduce Varest, guided by semantic fungibility: tokens within a cohe

tutorialsarxiv-cs-cv

14 Oct 2026

KedgeFlow: A Programmable Control Plane for Enterprise AI Agents

arXiv:2610.14810v1 Announce Type: cross Abstract: Enterprise AI agents can execute altered versions of approved actions, concurrently reuse the same permission, or retry operations whose responses wer

Last-Iterate Convergence of Clipped SGD with Linear Decay

arXiv:2610.18555v1 Announce Type: new Abstract: In this paper, we study the last-iterate convergence of clipped stochastic gradient descent under heavy-tailed noise. We assume that the stochastic grad

Applications

Latent-Space Importance Weighting under Covariate Shift

arXiv:2610.15571v1 Announce Type: cross Abstract: In this work, we propose a transfer learning algorithm for covariate shift, integrating sample reweighting with representation learning. A key feature

applicationsarxiv-cs-lg

Layer-wise Input Recoverability in Deep Neural Networks

arXiv:2610.14290v1 Announce Type: new Abstract: The inner workings of deep neural networks are still not well understood. The information bottleneck framework, which characterizes deep networks by the

Applications

Learning Deployable Causal Action Geometry under Temporal Non-Stationarity

arXiv:2610.16644v1 Announce Type: new Abstract: Learning a response law for continuous decisions from observational time series is central to many real-world decision systems, yet temporal non-station

applicationsarxiv-cs-lg

Learning Dynamic Grasping

arXiv:2610.14848v1 Announce Type: new Abstract: Synthesizing believable 4D hand-object grasping sequences is important for character animation, extended reality, and embodied agents. Grasping requires

Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting

arXiv:2610.16645v1 Announce Type: new Abstract: Recovering divergence-free velocity fields from sparse and corrupted observations requires reconciling physical consistency, expressive representations,

Learning Source Structure: Bayesian Prediction with Transformers

arXiv:2610.18725v1 Announce Type: new Abstract: A transformer trained on sequences whose source parameters are drawn afresh each time can learn only what the sequences share: the source family and its

Learning to Sync at the Edge: Client-Side Adaptive Synchronization for Federated Learning

arXiv:2610.14268v1 Announce Type: cross Abstract: The scalability and performance of edge federated learning are fundamentally constrained by synchronization bottlenecks. Clients operate under heterog

local-aiarxiv-cs-lg

LETS: Low-Overhead External-Torque Sensing for Force-Feedback Bilateral Teleoperation

arXiv:2610.14889v1 Announce Type: new Abstract: Bilateral teleoperation with force feedback is becoming increasingly important, and the quality of external-torque estimation is critical to this proces

LexiCan: Lexicographic Canonicalization of Point Clouds for Machine Learning Applications

arXiv:2610.15171v1 Announce Type: new Abstract: Canonicalization resolves the rotational and permutation ambiguity of 3D point clouds by selecting a unique orbit representative, maintaining their geom

LLM-Augmented Bayesian Optimization with Adaptive Policies for Chiplet Design Space Exploration

arXiv:2610.14612v1 Announce Type: new Abstract: Chiplet technology is a key approach for extending Moore's Law. However, its design process is constrained by two primary challenges: the scarcity of ea

LLM-HB: Language-Aware LLM-Guided Hotword Biasing for Code-Switching ASR

arXiv:2610.16579v1 Announce Type: cross Abstract: Code-switching (CS) speech, characterized by language alternation within a single utterance, is prevalent in multilingual communities and poses challe

LLM Judges Have Dark Current: Stratified Null and Utility Tests for LLM Judge Reliability

arXiv:2606.15610v2 Announce Type: replace-cross Abstract: Passing an exact-clone null gate does not entail passing a matched target-selection utility gate. We call a non-tie preference between exact d

LLM-to-Flow Distillation: Teaching Natural Language Goals to Scientific Generators

arXiv:2610.17246v1 Announce Type: new Abstract: Generative discovery in science requires coupling high-level scientific reasoning with the ability to generate samples respecting the structure of a des

Look Before You Move: Agent-Interface-Aligned Supervision for Open-World Mobile Manipulation

arXiv:2610.15572v1 Announce Type: new Abstract: Open-world mobile manipulation requires a robot to find an object, approach it, and move it to a target receptacle from a language instruction. Training

Looped Reasoning Finishes Earlier Than You Think

arXiv:2610.18174v1 Announce Type: new Abstract: Looped reasoning with dynamic depth can be viewed as relaxation toward solution attractors in a learned dynamical landscape. In practice, however, laten

Make {pi}0.5 Learn to Call Astra for Reliable Robot Manipulation

arXiv:2610.14117v1 Announce Type: new Abstract: GPT-6 Astra provides robust embodied reasoning, but frequent external queries increase inference time and token costs. We equip a frozen pi_{0.5} policy

MARTS: A Modular Agricultural Robot for Targeted Spraying of Diseased Tomato Plants in Greenhouses

arXiv:2610.18123v1 Announce Type: new Abstract: Broadcast spraying remains the dominant method of disease control in greenhouse tomato production, yet it treats healthy and diseased tissue alike, expo

local-aiarxiv-cs-ro

Meaningful Moments: A Corpus of VLM-Derived Temporal Importance Labels for Video Action Recognition

arXiv:2610.16009v1 Announce Type: new Abstract: Not every moment in a video is equally useful for recognizing an action. A few decisive moments often carry the evidence: the instant an object moves, t

researcharxiv-cs-cv

Memory Without Curation: Learning Multi-Stream Latent Memory for Robot Policies

arXiv:2610.14406v1 Announce Type: cross Abstract: It is widely appreciated that robotic policies require long-term memory to perform complex tasks. However, directly conditioning policies on all past

MENTOR: Procedural Shielding of Tool-Using LLM Agents

arXiv:2610.17039v1 Announce Type: cross Abstract: Tool-using LLM agents are increasingly used to automate workflows governed by procedural manuals, such as company rules for booking travel or procurin

local-aiarxiv-cs-lg

Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices

arXiv:2509.22707v2 Announce Type: replace-cross Abstract: Dynamic Voltage and Frequency Scaling is essential for enhancing energy efficiency in mobile platforms. However, traditional heuristic-based g

Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree

arXiv:2610.16906v1 Announce Type: new Abstract: Multi-modal fusion for 3D object detection assumes that cameras and LiDAR are broadly complementary. In practice, how much each modality is trusted at a

safetyarxiv-cs-cv

MIST: Multi-Scale Spatial Context for Gene Expression Prediction from Histology

arXiv:2610.18769v1 Announce Type: new Abstract: Predicting spatial gene expression from standard H&E images could extend molecular analysis to tissues without spatial transcriptomic measurements. A st

local-aiarxiv-cs-cv

MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning

arXiv:2610.15205v1 Announce Type: cross Abstract: Efficient task scheduling in heterogeneous computing systems remains a fundamental challenge in embedded and high-level synthesis flows. This paper pr

MvFFN: Multi-view Floor plan Feed-forward Network for Unposed Wide-Baseline Panorama Layout Reconstruction

arXiv:2610.14315v1 Announce Type: new Abstract: Reconstructing accurate camera poses and floor-plan layouts from sparse, unposed, wide-baseline RGB panoramas remains a challenging open problem. Direct

tutorialsarxiv-cs-cv

NetRL: Powering Network Decisions via NetGRPO-Driven Reinforcement Learning

arXiv:2610.16226v1 Announce Type: cross Abstract: Network decision-making tasks, including adaptive bitrate streaming, load balancing, and congestion control, require policies to process heterogeneous

Applications

NeuSE: Neural SE(3)-Equivariant Embedding for Long-Term Object-Based Simultaneous Localization and Mapping

arXiv:2303.07308v3 Announce Type: replace-cross Abstract: We present NeuSE, a novel Neural SE(3)-Equivariant Embedding for objects, and illustrate how it supports object-based Simultaneous Localizatio

applicationsarxiv-cs-cv

OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows

arXiv:2610.16586v1 Announce Type: new Abstract: Generating accurate 3D molecules requires jointly determining a variable number of atoms, their identities, and geometry across spatial scales: global s

OIL: An Object Interaction Layer for Humanoid Whole-Body Control

arXiv:2610.14033v1 Announce Type: new Abstract: Recent progress in learned whole-body controllers for humanoid robots has enabled robust free-space motion by tracking kinematic targets such as joint o

On Making SE(2)-Invariant Networks Optimal

arXiv:2610.17424v1 Announce Type: new Abstract: Respecting a-priori known symmetries of underlying data is a key principle in designing efficient neural architectures. Convolutional neural networks ar

On physical implementability of reinforcement-learning-driven reasoning

arXiv:2610.14131v1 Announce Type: cross Abstract: In the machine learning community, the reinforcement-learning-driven reasoning process has been intensively studied since around 2025. In this article

On the Theoretical Limits of Learning Unconstrained Interatomic Potentials

arXiv:2610.15078v1 Announce Type: new Abstract: Machine-learned interatomic potentials (MLIPs) accelerate molecular dynamics (MD) simulations by learning the energies and forces that govern atomic mot

One-Layer Transformers Provably Learn In-Context K-Nearest Neighbor Prediction with Chain-of-Thought

arXiv:2610.16798v1 Announce Type: new Abstract: Chain-of-Thought (CoT) enables transformers to solve complex reasoning tasks by generating intermediate reasoning steps. Despite strong empirical succes

Optimizing Team Behavior via Extremum-seeking Control in Multi-agent Reinforcement Learning

arXiv:2610.18808v1 Announce Type: cross Abstract: In cooperative Multi-Agent Reinforcement Learning (MARL), agents must learn to coordinate their actions to achieve shared objectives. A key indicator

agentsarxiv-cs-ro

Orientation Estimation of Cryo-EM Images for Molecules with Arbitrary Symmetry by Semidefinite Programming

arXiv:2610.18691v1 Announce Type: new Abstract: This paper extends the non-unique games framework introduced in Bandeira et al. (2020) to address symmetric structures. Precisely, we consider the probl

researcharxiv-cs-cv

PathLift: Depth-Conditioned Metric Lifting for Visual-Navigation Priors

arXiv:2610.16103v1 Announce Type: new Abstract: Generalist visual-navigation policies tell a robot which direction to go but not how far. A separate lifting step is needed at deployment to convert the

Pickalo: Leveraging 6D Pose Estimation for Low-Cost Industrial Bin Picking

arXiv:2604.04690v3 Announce Type: replace Abstract: Bin picking in real industrial environments remains challenging due to severe clutter, occlusions, and the high cost of traditional 3D sensing setup

Pixels or Code? Benchmarking Instruction-Guided Visual Artifact Operation

arXiv:2610.16444v1 Announce Type: new Abstract: Visual artifacts such as charts, technical diagrams, webpages, and document pages underpin scientific, commercial, and engineering workflows. Editing th

agentsarxiv-cs-cv

PLEDGE: Progressive Lossy Error-Bounded Compression of 3D Gaussian Splatting

arXiv:2610.17605v1 Announce Type: new Abstract: Existing 3D Gaussian Splatting (3DGS) codecs report reconstruction quality after compression, and give users little control over the distortion of indiv

researcharxiv-cs-cv

Position: Beyond Training Time, Test-Time Coordination is Essential for Cooperative MARL

arXiv:2610.17409v1 Announce Type: new Abstract: We argue that cooperative multi-agent reinforcement learning (MARL) should treat test-time coordination as part of the problem definition rather than a

agentsarxiv-cs-lg

Predict Before You Modify: Learning Improvement Dynamics for Self-Evolving Agents

arXiv:2610.13991v1 Announce Type: new Abstract: Self-evolving agents improve through repeated cycles of modification and evaluation. However, existing methods receive feedback on modifications only af

agentsarxiv-cs-lg

Predict in Chunks, Revise in Spans: History-conditioned Action Regeneration for Robotic Manipulation

arXiv:2610.14864v1 Announce Type: new Abstract: Action chunking improves temporal coherence in visuomotor imitation learning by jointly predicting sequences of future actions. However, many existing p

Probabilistic Simulation of Gas-Liquid Interfaces with Coupled Flow Matching on Spherical Harmonics

arXiv:2610.16327v1 Announce Type: new Abstract: Bubbly flows involve strongly coupled bubble motion, deformation, and hydrodynamic interactions, making high-fidelity simulation computationally expensi

Push the Limit: Learning High-Speed Sprinting and Aggressive Cornering on a Full-Scale Humanoid

arXiv:2610.14840v1 Announce Type: new Abstract: We present a learning-based framework that enables a full-scale bipedal humanoid to sprint at over 7 m/s with motion-prior-guided gait and perform aggre