Search: “framework”

Adapter Thickets: Splitting an RLVR Budget Beats Concentrating It

arXiv:2610.00991v1 Announce Type: new Abstract: Majority voting over sampled completions is the workhorse of test-time scaling, and reinforcement learning with verifiable rewards (RLVR) is the workhor

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AdaptManip: Learning Adaptive Whole-Body Object Lifting and Delivery with Online Recurrent State Estimation

DGX agent

arXiv:2602.14363v2 Announce Type: replace-cross Abstract: This paper presents Adaptive Whole-body Loco-Manipulation, AdaptManip, a fully autonomous framework for humanoid robots to perform integrated

safetyarxiv-cs-lg

2 Oct 2026

Ai2 releases Olmo-core 3 to make developing large mixture-of-experts LLMs more efficient

model-releasessiliconangle

Seattle-based artificial intelligence research firm Allen Institute for AI announced a development framework for large language models Thursday that significantly improves how mixture-of-experts large

ESCROW: Guarded and Dual-Objective Continual Maintenance for Agents in Policy-Governed Enterprise Workflows

arXiv:2608.01772v2 Announce Type: replace Abstract: LLM agents increasingly run policy-bound enterprise workflows, where they must apply rules consistently and stay auditable. Deploying such an agent

Flowing Faster to Coordinate: One-Step Online Multi-Agent Flow Policies

arXiv:2610.01882v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment.

Tutorials

MotionPersona: Real-Time Locomotion Control across Personas, Bodies, and Styles

arXiv:2506.00173v2 Announce Type: replace-cross Abstract: We present MotionPersona, a generative framework for character-aware locomotion control, in which the motion for a command depends on the capt

tutorialsarxiv-cs-ro

SkillEvoLean: Mutation-enhanced skill evolution for Lean provers

arXiv:2610.01799v1 Announce Type: new Abstract: Skill evolution offers a promising way to improve large language model agents without updating their parameters, but its use in formal theorem proving r

Structured-Noise Masked Modeling for Video, Audio and Beyond

arXiv:2503.16311v2 Announce Type: replace-cross Abstract: Masked modeling has emerged as a robust self-supervised learning framework. However, most methods rely on random masking, which disregards the

researcharxiv-cs-ai

Local Ai

Uncertainty-Guided Handshake: Efficient Human-in-the-Loop Refinement for Surgical-Grade Glioma Segmentation

arXiv:2610.01452v1 Announce Type: new Abstract: While state-of-the-art automated models for medical image segmentation achieve high mean performance, they frequently suffer from localized, catastrophi

local-aiarxiv-cs-cv

A Competing-Hazards Systematization of Loss of Control in Autonomous Agents

arXiv:2609.38411v1 Announce Type: new Abstract: Leading AI developers have reported agents acting beyond their approved limits, which a United Nations panel described as an early warning of loss of hu

A Rank Graduation metric for Algorithmic fairness

arXiv:2609.39025v1 Announce Type: new Abstract: Fairness assessment in algorithmic decisions that affect individuals, such as credit scoring, often relies on parity measures calculated at the aggregat

Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization

arXiv:2501.18183v3 Announce Type: replace-cross Abstract: We introduce a novel framework for decentralized projection-free optimization, extending projection-free methods to a broader class of upper-l

Fast and Scalable Multi-Agent Distribution Matching via Partitioned Optimal Transport

arXiv:2609.38960v1 Announce Type: cross Abstract: This paper presents a scalable optimal-transport-based framework for terminal distribution matching in multi-agent systems. While optimal transport pr

agentsarxiv-cs-ro

Growing an Agent/Prover Interface: Evolutionary Tool Design for Cost-Efficient Theorem Proving in Rocq and Lean

arXiv:2609.39544v1 Announce Type: new Abstract: Recent achievements in AI-assisted mathematics require intensive interaction of agents with proof assistants to generate machine-checked proof certifica

agentsarxiv-cs-ai

JuryFlow: Disagreement-Guided Human-in-the-Loop Multi-Agent Evaluation

arXiv:2609.40103v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as automated judges for AI-generated content, yet a single judge is unreliable and even a panel o

agentsarxiv-cs-cl

Tutorials

Learn-Then-Differentiate Gradient Estimation

arXiv:2609.38842v1 Announce Type: cross Abstract: Learn-then-differentiate (LTD) estimates gradients by fitting a model to simulation outputs and differentiating it. We develop a unified framework exp

tutorialsarxiv-cs-lg

Learning to Build: Autonomous Robotic Assembly of Stable Structures Without Predefined Plans

arXiv:2602.23934v2 Announce Type: replace-cross Abstract: This paper presents a novel autonomous robotic assembly framework for constructing stable structures without relying on predefined architectur

Online Evolution Strategy for Flow-Matching VLA Policies via Self-Supervised Trajectory Distribution Optimization

model-releasesarxiv-cs-ai

arXiv:2609.38855v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models based on generative frameworks, such as Flow Matching, have recently achieved impressive performance in robotic ma

Applications

Reasoning Externalization for Faithful Large Language Model Narratives of Stock Return Predictions

arXiv:2609.38869v1 Announce Type: new Abstract: In finance, interpreting machine learning predictions is essential, yet the numerical outputs of explainable AI can be difficult for non-experts to unde

applicationsarxiv-cs-ai

Residual Wrench Certification and Margin-Aware Control Synthesis for Aerial Physical Interaction

arXiv:2609.38707v1 Announce Type: new Abstract: We develop a task-relative framework for certifying residual wrench authority after hover and contact loading in multirotors with bounded actuators. Usi

researcharxiv-cs-ro

SEPAL: Separated Expert Pairs with Answer-Level Fusion for Reliable LLM Collaboration

arXiv:2609.39645v1 Announce Type: cross Abstract: Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback. Yet shared discussion couple

agentsarxiv-cs-ai

Who Said What, and Will It Be Remembered? Evaluating Persistent Speaker Attribution Across Meetings

model-releasesarxiv-cs-ai

arXiv:2609.39344v1 Announce Type: cross Abstract: Speech transcripts used as long-term memory must preserve both words and stable speaker identities. Existing meeting-transcription metrics either igno

Bridging Semantic Gaps in RAG through Generated Context Knowledge Fusion

arXiv:2609.37171v1 Announce Type: new Abstract: Retrieval-Augmented Generation has established itself as a fundamental framework in natural language processing, seamlessly integrating information retr

safetyarxiv-cs-cl

Data Unlearning via Inverse Distillation

arXiv:2609.36099v1 Announce Type: new Abstract: Multi-step matching models, including flow and diffusion models, produce high-quality outputs but incur substantial inference costs and may reproduce un

Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs

model-releasesarxiv-cs-ai

arXiv:2609.36157v1 Announce Type: cross Abstract: Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task. This

Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions

arXiv:2609.36578v1 Announce Type: cross Abstract: Scheduling problems arise from repeatedly selecting one item from a set of candidates based on their states. These problems often reduce to assigning

Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest

arXiv:2609.37308v1 Announce Type: cross Abstract: This paper introduces a hybrid joint-selective optimization (HJSO) framework for large-scale numerical problems in which a small subset of trainable q

Tutorials

Passive-Dynamic-Walking-Inspired Dynamics Guidance for Energy-Efficient Humanoid Locomotion

arXiv:2609.35935v1 Announce Type: new Abstract: Learning energy-efficient humanoid locomotion requires discovering mechanically economical gait coordination, not merely reducing actuator effort. Reinf

tutorialsarxiv-cs-ro

Population Fidelity: Evaluating Population Representativeness in LLMs

arXiv:2609.36253v1 Announce Type: cross Abstract: Large language models (LLMs) show considerable potential in simulating human attitudes and preferences. Prior work finds that LLM-generated responses

Applications

ProAct-VLM: Pre-Failure Vision-Language Task Replanning with Continuous Perception Feedback

arXiv:2609.37681v1 Announce Type: new Abstract: Long-horizon robotic tasks are vulnerable to unexpected environmental changes that can render planned actions ineffective or unsafe. To address this, ro

applicationsarxiv-cs-ro

Admissible Diffusion for Multimodal Interventional Trajectories

arXiv:2609.34433v1 Announce Type: new Abstract: Generating a plausible clinical trajectory does not establish what would happen under a different treatment. We present ADMIT, a framework combining irr

Back-Tracking from Clarity: Self-Learning to See Text from Afar

arXiv:2609.32477v1 Announce Type: new Abstract: We propose a self-supervised framework designed to enhance the capability of scene text detectors in identifying and recognizing text in scenarios where

researcharxiv-cs-cv

Deep kernel hedging

arXiv:2609.34474v1 Announce Type: new Abstract: We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods. The he

End-to-end QP-based policies: A unified perspective on robust control and robot learning

arXiv:2609.31905v1 Announce Type: new Abstract: We present an end-to-end QP-based policy framework that enables systematic policy construction with minimal domain-specific design, while preserving the

safetyarxiv-cs-ro

Energy-aware frugal Bayesian optimization

arXiv:2609.31638v1 Announce Type: new Abstract: Modern design optimization frameworks aim first and foremost for models with the most accurate predictions without balancing computational overhead. It

FEAT: Free energy Estimators with Adaptive Transport

arXiv:2504.11516v4 Announce Type: replace-cross Abstract: We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across

Applications

In-Token Learning for High-Fidelity Image Restoration via Diffusion Transformers

arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C

applicationsarxiv-cs-cv

Inspector: Conversational and Lightweight Analyzer of Analog Circuit Layouts Using LLM and CNNs

arXiv:2609.34976v1 Announce Type: cross Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs)

researcharxiv-cs-cv

Look Before You Judge: Training-Free Region Mining for Grounded and Explainable Deepfake Detection

model-releasesarxiv-cs-cv

arXiv:2609.35536v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can explain deepfake verdicts in natural language, but such explanations are not necessarily visually grounded

MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis

arXiv:2609.31789v1 Announce Type: cross Abstract: In this work, we explore MammoClaw, a training-free agent framework that leverages frozen MLLMs for mammography analysis. To support agentic investiga

agentsarxiv-cs-cv

PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks

arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha

Industry

Prompt engineering fundamentals for Amazon Quick

Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusable frameworks (speci

industryaws-ml-blog

Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

arXiv:2609.35086v1 Announce Type: new Abstract: In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture

Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression

model-releasesarxiv-cs-cv

arXiv:2609.34834v1 Announce Type: new Abstract: Transform-based methods provide an effective framework for point cloud attribute compression by representing attributes as transform coefficients. Intro

ZeroBot: Learning from Scratch in Minutes with Generative Real2Sim

arXiv:2609.34010v1 Announce Type: cross Abstract: We present ZeroBot, a real2sim framework for learning a robot manipulation task from scratch in minutes under challenging conditions: zero human demon

safetyarxiv-cs-cv

Bayesian Uncertainty Quantification for fMRI Functional Connectivity via Simulation-Based Inference

arXiv:2609.30445v1 Announce Type: cross Abstract: Optimizing fMRI scan duration and spatial resolution is critical for experimental design, yet traditional correlation-based approaches cannot quantify

28 Sept 2026

Learning Vision-Based Agile Gap Traversal: Differentiable Simulation with a Warm-Started Critic

arXiv:2609.30696v1 Announce Type: new Abstract: Traversing narrow gaps is challenging for autonomous quadrotors, especially when control commands come directly from high-dimensional visual observation

safetyarxiv-cs-ro

28 Sept 2026

MDSkin-Net: Multi-Task Skin Lesion Analysis Driven by Pattern Analysis Priors and Spatial Alignment Regularization