Search: “framework”

arXiv:2610.22322v1 Announce Type: cross Abstract: The capabilities of an agent swarm depend on both its individual members and how they coordinate. Yet existing multi-agent systems often train agents

local-aiarxiv-cs-ai

Tutorials

Learning Speech Attribute Representations via Multi-Teacher Distillation

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DGX agent

arXiv:2610.21941v1 Announce Type: new Abstract: Recent post-training approaches have shown that self-supervised speech encoders can be adapted to learn a single utterance-level speech attribute throug

tutorialsarxiv-cs-cl

16 Oct 2026

Learning to Search for Executable Patternmaking from Certified Programs

arXiv:2610.21579v1 Announce Type: cross Abstract: Recent models generate sewing patterns from images or text, and program-based representations make these patterns executable. These systems produce a

researcharxiv-cs-ai

Learning Topology-Aware Representations for Mechanics-Relevant TPMS Metamaterials

arXiv:2610.20684v1 Announce Type: cross Abstract: Learning informative representations of mechanical Triply Periodic Minimal Surface (TPMS) metamaterials is important for mechanics analysis and struct

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Learning When to Think: Utility-Guided Adaptive Reasoning for Efficient Text Retrieval

model-releasesarxiv-cs-cl

arXiv:2610.21030v1 Announce Type: cross Abstract: Reasoning-conditioned embeddings can improve retrieval by progressively refining semantic constraints. However, additional reasoning may introduce ove

LEASH: Uncertainty-Aware Weak-to-Strong Escalation and Oversight for Computer-Use Agents

arXiv:2610.22280v1 Announce Type: new Abstract: Computer-use agents increasingly tackle long-horizon tasks, where running a frontier model at every step is expensive and a small open-weight model alon

Let's Ask Gauss: Improved One-Run Privacy Auditing

arXiv:2606.12733v3 Announce Type: replace Abstract: Privacy auditing provides an important safeguard by estimating the actual information leaked by a model, thus ensuring that theoretical privacy guar

Librarian Agents: Training LLMs to Curate Long-Context Workspaces that Anticipate Future Queries

arXiv:2610.22273v1 Announce Type: cross Abstract: Reasoning over long document contexts remains a challenge for large language models (LLMs). Standard retrieval methods are inherently reactive, bottle

Agents

LOOP-MAC: Learning-Based Multi-Agent Coordination with Guaranteed Local Feasibility in a Virtual Power Plant

arXiv:2310.17882v3 Announce Type: replace Abstract: By aggregating distributed energy resources (DERs) into a single dispatchable resource, virtual power plants (VPPs) enable the grid to use the flexi

agentsarxiv-cs-lg

LoopAhead: Speculating Ahead for Faster Decoding in Looped Language Models

arXiv:2610.21594v1 Announce Type: new Abstract: Looped Transformers improve parameter efficiency by repeatedly applying the same Transformer layers. However, generating each token still involves seque

MAGMA: Multiplier-Augmented Geometric Motion Algorithm

arXiv:2610.21852v1 Announce Type: new Abstract: Solving optimal control problems for high-dimensional mechanical systems subject to constraints remains challenging due to nonlinear dynamics and non-co

researcharxiv-cs-ro

Agents

MAI-Gym: An Open All-in-One Platform for GUI Agent Evaluation and RL Training across Mobile and Computer Environments

arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to G

agentsarxiv-cs-ai

MAIA: Anticipating Interaction Anomalies in Contact-Rich Manipulation via Multimodal World Models

arXiv:2610.21686v1 Announce Type: new Abstract: Reliable contact-rich manipulation requires detecting execution deviations early enough for corrective action. Yet most monitoring methods are reactive,

Manifold Generative Annealing for Contact Constraint-aware Impedance Control with Reinforcement Learning Prior

arXiv:2610.21140v1 Announce Type: new Abstract: Contact-rich robotic tasks require coordinated motion and impedance under uncertain interaction dynamics and physical constraints. While recent methods

Tutorials

ManiFusion: Unlocking the High-Throughput Generation via Superposition in Manifold Space

arXiv:2610.21433v1 Announce Type: new Abstract: Diffusion models achieve high-quality image generation but remain computationally expensive due to iterative denoising across many timesteps. Existing a

tutorialsarxiv-cs-cv

MedPAO-VL: Interpretable and Protocol-Compliant Agent for Structured Radiology Report Generation

arXiv:2610.21794v1 Announce Type: new Abstract: Despite the remarkable generalization capabilities of Large Language Models, generating clinically accurate and structured radiology reports from medica

safetyarxiv-cs-cv

Mem4Act: Learning Effective Latent Memory for Long-Horizon Robotic Manipulation

arXiv:2610.22323v1 Announce Type: new Abstract: Long-horizon robotic manipulation fundamentally requires memory: agents must retain task-relevant information from past observations and interactions an

MemComposer: Learning to Assemble Memories for LLM Agents via Reinforcement Learning

arXiv:2610.21091v1 Announce Type: new Abstract: Agent memory enables large language model (LLM) agents to reuse past experiences without updating their parameters. However, semantic similarity alone d

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Memory as Weights: Internalizing Long-Term History for Streaming Videos

arXiv:2610.22070v1 Announce Type: cross Abstract: Streaming vision-language models (VLMs) must continuously integrate information from the past while remaining responsive to current observations and u

MemScope: Evolving Agent Memory Architectures through Localized Code Repair

arXiv:2610.21170v1 Announce Type: new Abstract: Agent memory architectures define how LLM agents store and reuse experience across tasks, but they are typically fixed after deployment, limiting their

MetaExp: Learning to Self-Improve through Experience via Verifiable Cross-Task Environment Scaling

arXiv:2610.21492v1 Announce Type: new Abstract: Language-model agents can accumulate interaction feedback, but reliably turning that feedback into reusable experience remains challenging. Existing met

researcharxiv-cs-ai

MIDI-REPA: Improving Text-to-Music Generation with Symbolic Representation Alignment

model-releasesarxiv-cs-lg

arXiv:2610.20967v1 Announce Type: cross Abstract: State-of-the-art text-to-music models increasingly rely on scaling model capacity, data, and compute, while still learning musical structure directly

Mind the Shift: Decoding Monetary Policy Stance from FOMC Statements with Large Language Models

arXiv:2603.14313v2 Announce Type: replace Abstract: Federal Open Market Committee (FOMC) statements are a major source of monetary-policy information, and even subtle changes in their wording can move

safetyarxiv-cs-cl

MindEval2: Clinically Grounded Patients and Rubrics for Evaluating Language Models in Mental Health Support

arXiv:2610.22314v1 Announce Type: new Abstract: With people increasingly turning to AI chatbots for mental health support, the need to evaluate these tools is becoming more pressing. Recent benchmarks

researcharxiv-cs-cl

Mitigating Memorization Where It Happens

arXiv:2602.08901v2 Announce Type: replace Abstract: Large language models (LLMs) can memorize and reproduce training sequences verbatim, raising privacy and copyright concerns. Existing mitigation met

Hardware

MJev-Spatial: System One Spatial Intelligence via Native Attention Matching

arXiv:2610.22276v1 Announce Type: new Abstract: Spatial intelligence lets an agent perceive and act in the physical world, and many of its judgments must be made at interaction rates: which spatial re

hardwarearxiv-cs-cv

MoCaP: Mobile Code-as-Policies for Zero-Shot Mobile Manipulation from Passive Human Videos

arXiv:2610.20998v1 Announce Type: new Abstract: Passive human videos of everyday activity offer robots access to a massive amount of human experience without requiring a demonstration for each task. H

Tutorials

Motion- and Gravity-Aware Feedforward 3D Reconstruction

arXiv:2610.22177v1 Announce Type: cross Abstract: Feed-forward transformer models have recently achieved strong performance in multi-view 3D reconstruction, but they still rely primarily on appearance

tutorialsarxiv-cs-ai

MR-MPCC: Model Predictive Contouring Control for Robotic Manipulator Tracking under Moving Reference Frames

arXiv:2610.21292v1 Announce Type: new Abstract: Maintaining small path-tracking errors under moving reference frames is essential for robotic manipulation tasks with tight execution tolerances, such a

MSP: Modality Self-Play for Training Multimodal LLMs Without Paired Cross-Modal Data

arXiv:2610.20965v1 Announce Type: new Abstract: Large multimodal models have achieved remarkable progress by scaling model capacity and training on massive paired multimodal data. However, this paradi

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Agents

Multi-Agent Transactive Memory

arXiv:2606.19911v2 Announce Type: replace Abstract: Decentralized deployment of LLM agents with diverse capabilities motivates infrastructure for knowledge sharing across heterogeneous agent populatio

agentsarxiv-cs-ai

Multi-Teacher On-Policy Distillation for Flow-Based Vision-Language-Action Models

arXiv:2610.21522v1 Announce Type: new Abstract: Specialized vision-language-action (VLA) policies acquire strong domain-specific skills, yet consolidating these skills into one shared policy remains c

MYOPIA: Understanding the Limits of Tree-Based Reasoning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.21573v1 Announce Type: new Abstract: Decision trees can make vision-language model (VLM) classification interpretable by replacing a single prediction with a sequence of root-to-leaf questi

Navigation by Skylight Polarization via Rayleigh Model Optimization on a Road Vehicle

arXiv:2610.20797v1 Announce Type: new Abstract: Reliable absolute heading estimation is critical for road-vehicle navigation, particularly when magnetic, inertial, or GNSS-based references are degrade

researcharxiv-cs-ro

NICE Toolbox: Nonverbal Interpersonal Communication Exploration Toolbox

arXiv:2610.21786v1 Announce Type: new Abstract: Understanding human communication is a long-standing goal in psychological research. People express themselves through many verbal and nonverbal channel

researcharxiv-cs-cv

Not Just a Subject: Capturing Adaptive Scene-Specific Variance for Visual Storytelling

model-releasesarxiv-cs-cv

arXiv:2610.22320v1 Announce Type: new Abstract: Recent advancements in diffusion models have significantly improved text-to-image generation, enabling their application to visual storytelling, where c

OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling

arXiv:2610.22355v1 Announce Type: new Abstract: Generative visual verifiers play a crucial role in advancing multimodal intelligence. To enhance the robustness of visual verifiers in complex multimoda

safetyarxiv-cs-cl

On-Policy Residual Learning for Diffusion Language Models

arXiv:2610.20687v1 Announce Type: new Abstract: Residual context is key to unlocking the speed-quality Pareto frontier of diffusion language models (DLMs) by carrying forward predictive distributions

safetyarxiv-cs-lg

OntoAct: Hypothesis-Based Neuro-Symbolic Agents through Ontological Abstraction

arXiv:2610.21983v1 Announce Type: new Abstract: Learning from experience requires recovering reusable knowledge and determining when it applies to a new situation. We introduce OntoAct, a hypothesis-b

OpCredit: Operation-Aware Policy Learning for Agentic Knowledge Graph Question Answering

arXiv:2610.21345v1 Announce Type: new Abstract: Agentic knowledge graph question answering(KGQA) relies on sequences of executable operations, but trajectory-level rewards obscure their individual con

safetyarxiv-cs-cl

Optimal Condition for Initialization Variance in Deep Neural Networks: An SGD Dynamics Perspective

arXiv:2508.12834v2 Announce Type: replace-cross Abstract: Stochastic gradient descent (SGD), one of the most fundamental optimization algorithms in machine learning (ML), can be recast through a conti

Local Ai

Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets

arXiv:2610.20753v1 Announce Type: cross Abstract: Large language models (LLMs) trained on vast amounts of data have demonstrated impressive performance over a range of tasks, but future performance ga

local-aiarxiv-cs-ai

Orchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation

arXiv:2602.18891v2 Announce Type: replace-cross Abstract: Advances in large language models (LLMs) are rapidly transforming scientific work, yet empirical evidence on how these systems reshape researc

safetyarxiv-cs-ai

Local Ai

P2TPO: Structure-Aligned Page-to-Token Credit Assignment for Full-Page Document Parsing

arXiv:2610.21979v1 Announce Type: cross Abstract: End-to-end full-page document parsing must preserve the content and structure of heterogeneous elements, yet otherwise accurate outputs can contain lo

local-aiarxiv-cs-cl

Phase Kernel Lifts Capacity of Dense Associative Memory

arXiv:2610.21493v1 Announce Type: new Abstract: Dense associative memory underlies modern attention mechanisms; however, Modern Hopfield Networks (MHNs) with linear kernels yield overlapping attractor

PiCo: Physics-Informed Concept Probing for Geo-Foundation Models

arXiv:2610.20973v1 Announce Type: new Abstract: Geo-foundation models (GFMs) are typically evaluated by downstream task predictive performance, revealing little about which physical features they are

researcharxiv-cs-cv

Planning to Learn: Real-Time Robust Adaptive Control on the GPU with Guaranteed Future Learning

model-releasesarxiv-cs-lg

arXiv:2610.20925v1 Announce Type: cross Abstract: Robust adaptive control is vital for keeping robots safe while actively reducing uncertainty in unfamiliar settings. However, traditional methods are

PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning

model-releasesarxiv-cs-cl

arXiv:2610.21308v1 Announce Type: cross Abstract: Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text ra