Search: “models”

Minimax Additive Regression under Unknown Dependent Designs

arXiv:2609.39212v1 Announce Type: cross Abstract: We study additive regression under a potentially non-product random design on [0,1]^d, allowing the dimension d to grow with the sample size n. We int

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Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision

DGX agent

arXiv:2609.39525v1 Announce Type: cross Abstract: Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intract

local-aiarxiv-cs-lg

1 Oct 2026

Mitigating the Length-Scaling Tax with Online Distillation

arXiv:2609.38854v1 Announce Type: cross Abstract: Length scaling during reinforcement-learning (RL) post-training is often viewed as a sign of improved reasoning ability, especially on difficult probl

Tutorials

ModSec-Learn: Boosting ModSecurity with Machine Learning

arXiv:2406.13547v2 Announce Type: replace Abstract: ModSecurity is widely recognized as the standard open-source Web Application Firewall (WAF), maintained by the OWASP Foundation. It detects maliciou

tutorialsarxiv-cs-lg

NavHarness: Adaptive Goals for Agentic Vision-Language Navigation

arXiv:2609.39915v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents

local-aiarxiv-cs-cv

OccluDex: Hierarchical 3D Visuo-Tactile Representation Learning for Egocentric Dexterous Manipulation under Self-Occlusion

arXiv:2609.39017v1 Announce Type: new Abstract: Reliable dexterous manipulation requires continuous estimation of object geometry and hand-object contact throughout interaction. With egocentric sensin

researcharxiv-cs-ro

On the Off-Policy Teacher in On-Policy Distillation

arXiv:2609.38360v1 Announce Type: cross Abstract: On-policy distillation (OPD) has recently emerged as a promising post-training paradigm in which the student learns from trajectories generated by its

OPTS-TTPO: Enhancing Finite-Sample Policy-Gradient Learning with Tree Search

arXiv:2609.40035v1 Announce Type: new Abstract: The policy-gradient theorem gives the exact gradient under the current policy, but finite on-policy samples may miss rare high-return trajectories. We s

safetyarxiv-cs-cl

Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

arXiv:2609.39975v1 Announce Type: cross Abstract: This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluati

Passive Stiffness Shaping in Cable-Suspended Aerial Manipulation via Movable Compliant Anchors

arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica

local-aiarxiv-cs-ro

Persona and Persuasive Framing in AI Voice Agents: A 2imes2 Field Experiment with Children

arXiv:2609.38782v1 Announce Type: new Abstract: Conversational agents increasingly interact with children, yet evidence on how their design shapes children's susceptibility to persuasion comes almost

Policy-Conditioned AI-Use Detection: An Evidentiary Framework for Academic Publishing

arXiv:2609.38427v1 Announce Type: cross Abstract: Major venues now publish detailed rules about how authors, reviewers, and area chairs may use AI, and those rules differ by role, by task, and by what

Positive Ratings, Hidden Concerns: Employee Voice Disclosure in AI-Mediated Organizational Listening

arXiv:2609.38788v1 Announce Type: new Abstract: Organizations started listening to employees through conversational AI agents alongside structured surveys. Little is known about what these channels ch

PRICE the Action Chunks: Physical Relational Credit Assignment for Embodied Reinforcement Learning

arXiv:2609.38890v1 Announce Type: new Abstract: Outcome-based reinforcement learning (RL) post-trains vision--language--action policies using terminal success signals, but assigns the same trajectory-

researcharxiv-cs-ro

Tutorials

Pseudo-Label-Triggered Retraining from Forecast Errors for Online Time Series Forecasting

arXiv:2609.39789v1 Announce Type: cross Abstract: Real-world time series forecasting systems operate under non-stationary data streams, where forecasting performance may degrade over time. Although re

tutorialsarxiv-cs-ai

RAST: Resolution-Aware Privileged Structure Transfer for Low-Resolution Audio Activity Recognition

arXiv:2609.38780v1 Announce Type: cross Abstract: Audio is increasingly used for human activity recognition (HAR) because it captures object interactions, environmental events, and contextual cues in

local-aiarxiv-cs-ai

Applications

Reconstructing the Dynamic World: A Representation-Centric View of 4D Scene Reconstruction

arXiv:2609.39960v1 Announce Type: new Abstract: 4D scene reconstruction aims to recover the evolving geometry, appearance, and motion of dynamic environments from visual observations. Despite substant

applicationsarxiv-cs-cv

Reconstruction of cosmic-ray direction and energy in radio arrays using deep ensemble graph neural networks

arXiv:2602.23321v2 Announce Type: replace-cross Abstract: Using advanced machine learning techniques, we developed a method to reconstruct the arrival direction and energy of ultra-high-energy cosmic

Reinforcement Learning with Complex (valued) Memories

arXiv:2609.38598v1 Announce Type: new Abstract: Partially observable environments pose a fundamental challenge in deep reinforcement learning, requiring agents to compress temporal information from ob

ReSAIL: Mitigating Collapse in Iterative Agent Self-Distillation

arXiv:2609.39306v1 Announce Type: cross Abstract: Iterative self-distillation enables LLM agents to learn from successive deployments, offering a path toward recursive self-improvement (RSI). Yet our

ReTaCo: Residual-Target Control for On-Policy Distillation

arXiv:2609.39275v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own generated prefixes with token-level teacher feedback, but transmitting or storing the teacher's

Rethinking Legibility in Social Robot Hallway Navigation: Impact of Intent Representation and Human Distraction

arXiv:2609.40158v1 Announce Type: new Abstract: We focus on legible robot motion generation in social navigation settings. Legibility in human-robot interaction (HRI) is often described as the propert

safetyarxiv-cs-ro

Risk-Aware Adaptive Evaluation: Finding High-Impact Failures Under Limited Budgets

arXiv:2609.38914v1 Announce Type: new Abstract: Evaluating interactive agents is expensive. Agent behavior is stochastic, so reliability must be measured over repeated trials, but failures are rare an

RLTL;DR: Self-Improvement by Internalizing Self-Generated Feedback

The common paradigm of reinforcement learning with verifiable rewards (RLVR) is to let agents make multiple attempts at a task, and optimize towards the successful ones. This becomes problematic in th

safetyapple-ml-research

Schema: Discovering Unknown Environments via Agentic Program Induction

arXiv:2609.39140v1 Announce Type: new Abstract: Learning to complete tasks in unfamiliar environments with unknown rules remains a key challenge for LLM agents. Current LLM agents often record their d

SCIC: Scope- and Codebook-Aware Instruction Conditioning for Speaker-Adapted Expressive TTS

arXiv:2609.39088v1 Announce Type: cross Abstract: Long-form live-streaming TTS requires context-dependent prosody and paragraph-level coherence. However, many existing instruction-based TTS systems us

ShamAN-Q: Shampoo Augmented NanoQuant for Sub-1-bit LLM Weights

arXiv:2609.38521v1 Announce Type: cross Abstract: We introduce ShamAN-Q, a sub-1-bit post-training quantization method that extends NanoQuant by replacing each its diagonal reconstruction geometry wit

local-aiarxiv-cs-ai

STRATA: Self-Learning Through Role-Aligned Tiered Agents for Real-Time Strategy Games

arXiv:2609.38881v1 Announce Type: new Abstract: Real-time strategy (RTS) games require agents to coordinate economic development, production and construction, base defense, unit organization, and atta

SynIL: Leveraging Synergy for Offline Imitation Learning from Imperfect Demonstration Datasets

arXiv:2609.38225v1 Announce Type: cross Abstract: Imitation learning enables robots to acquire complex skills directly from massive demonstration datasets, but its performance degrades severely when d

Systematically Exploring the Capabilities of GPT-6 Astra as Embodied Policies

arXiv:2609.38537v1 Announce Type: new Abstract: GPT-6 Astra exhibits a remarkable ability to generate numerical robot actions, extending its role beyond high-level planning. To assess Astra's capabili

local-aiarxiv-cs-ro

The Row Normalization Puzzle in Muon

arXiv:2609.39114v1 Announce Type: new Abstract: This paper examines how row-wise renormalization affects Muon, focusing on the gap between NorMuon's worst-case guarantees and its practical performance

Applications

TO-mdiSPAs: Topology Optimization of multi-directional Soft Pneumatic Actuators

arXiv:2609.39618v1 Announce Type: new Abstract: Soft pneumatic actuators (SPAs) are highly promising and have been extensively explored within the field of soft robotics. Under pneumatic pressure load

applicationsarxiv-cs-ro

Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach

arXiv:2609.39397v1 Announce Type: cross Abstract: We study data-driven multi-period lost-sales inventory control under censored demand, where a stockout reveals only that demand exceeded the stocking

Towards Universal Wasserstein Barycenters through Flow Matching

arXiv:2609.38547v1 Announce Type: cross Abstract: Defining a weighted mean over probability measures under probability metrics is a central tool in probabilistic machine learning. Under the Wasserstei

Travel Time Prediction in Supply Chain Management Using Machine Learning

arXiv:2609.38190v1 Announce Type: cross Abstract: The purpose of this research is to find data and methods using machine learning and deep learning to correctly predict the estimated travel time for t

Tutorials

TripleFlow: Training-Free Video Object Removal by Bridging Residual Editing and Native Generation

arXiv:2609.39157v1 Announce Type: new Abstract: Video object removal presents a uniquely difficult editing challenge. Because a removal prompt specifies only what to erase rather than what to generate

tutorialsarxiv-cs-cv

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

Two-Step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real

arXiv:2512.15774v5 Announce Type: replace Abstract: The absence of large-scale masked face datasets challenges masked face detection and recognition. We propose a two-step generative data augmentation

researcharxiv-cs-cv

UGOD: Uncertainty-Guided Opacity and Dropout for Sparse-View 3D Gaussian Splatting

arXiv:2609.39089v1 Announce Type: new Abstract: Sparse-view 3D Gaussian Splatting is prone to overfitting because limited observations leave many Gaussian primitives weakly constrained, yet their cont

researcharxiv-cs-cv

Unapologetically Distributed: A Call for Decentralized Document Analysis

arXiv:2609.39684v1 Announce Type: new Abstract: Privacy has become an increasingly important concern in the Document Analysis community, to the extent that in many environments such as archives, gover

local-aiarxiv-cs-cv

Understanding Off- vs On-Policy Distillation: A Tale of Distinct Training Objectives

arXiv:2609.38666v1 Announce Type: cross Abstract: On-policy distillation (OPD) learns from teacher feedback on student-generated responses and has shown promise in reducing forgetting relative to supe

Industry

Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS

Generative AI makes it cheap to produce personalized content at scale, but which variation do you show each customer? Amazon Payments used a multi-objective contextual bandit on Amazon SageMaker AI to

industryaws-ml-blog

Variance-Corrected Multi-Asset Equity Simulation with Hybrid Hidden Markov Marginals

arXiv:2603.10202v3 Announce Type: replace-cross Abstract: Synthetic multi-asset equity data must reproduce each asset's return distribution and its relationship with the market. Reusing a generator fi

When Does a Spoken Agent Have Enough Evidence to Act? The PACT-SLM Contract Test

arXiv:2609.38232v1 Announce Type: cross Abstract: Streaming spoken agents may take an external action before the available speech supports it, yet final-turn scores do not reveal whether each observed

agentsarxiv-cs-cl

When Integral Meets Decomposition: A Signal-Level Self-Supervised Feature Decompose Paradigm for Multi-Modal Image Fusion

arXiv:2609.39004v1 Announce Type: new Abstract: Multimodal image fusion (MMIF) aims to integrate complementary information from different modalities into a high-quality fused image and support downstr

researcharxiv-cs-cv

Zero-Compute Cross-Lingual Transferability Estimation Using Typological Feature Proxies

arXiv:2609.39640v1 Announce Type: cross Abstract: Cross-lingual transfer describes how knowledge in a source language benefits a target language. Measuring it quantitatively requires broad multilingua

Achieving an O(1/N) Optimality Gap in Average-Reward Weakly-Coupled MDPs

arXiv:2609.38132v1 Announce Type: new Abstract: We study average-reward weakly-coupled Markov decision processes (WCMDPs), where a WCMDP consists of N smaller MDPs, called arms, that share multiple pe

30 Sept 2026

AdvMT: Adversarial Motion Transformer for Long-term Human Motion Prediction