Search: “models”

Attention-based Hierarchical Variational Information Bottleneck for Robust Multi-Agent Communication under Variable Bandwidth

arXiv:2609.34860v1 Announce Type: new Abstract: Learning-based multi-agent communication under limited bandwidth does not only require deciding what to communicate, but also structuring messages so th

agentsarxiv-cs-lg

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Attribution Without a Second Pass: Inline Per-Sample Gradient Provenance at ~1% Overhead

DGX agent

arXiv:2609.32380v1 Announce Type: new Abstract: Data attribution methods used in practice (TRAK, LoGRA, EK-FAC) are post-hoc: after training they make a second pass over the training set to recompute

safetyarxiv-cs-lg

29 Sept 2026

Audit-First VAPO: Risk-Certified Selective Updates under Imperfect Verification

arXiv:2609.33662v1 Announce Type: cross Abstract: Imperfect verifiers can assign a harmful update direction even when clipping and regularization bound its magnitude. We introduce Audit-First VAPO, wh

Beyond Correctness: Evaluating Semantic Knowledge in Cross-Table Transfer

arXiv:2609.34098v1 Announce Type: new Abstract: Semantic knowledge is increasingly used to bridge heterogeneous schemas in tabular learning, but how much does that knowledge actually improve predictio

Beyond MSE: Rician Likelihood Denoising for Self-Supervised Cardiac T2 and T1rho MRI

arXiv:2609.31777v1 Announce Type: cross Abstract: Magnetic resonance imaging involves an inherent trade-off among spatial resolution, acquisition time, and noise. This trade-off contributes to long sc

Beyond Retrieval Relevance: Scene-Grounded Risk Entailment for Vision-Language Driving

arXiv:2609.34145v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) gives vision--language driving systems access to external safety knowledge, yet a retrieved risk rule may be releva

safetyarxiv-cs-ro

Beyond Sparsity: Weight Location and Network Context in Pruned MRI Reconstruction

arXiv:2609.31812v1 Announce Type: cross Abstract: Pruning reduces the number of weights in magnetic resonance imaging (MRI) reconstruction networks. Equal sparsity, however, can retain weights with di

Tutorials

Beyond the Training Horizon: Mechanisms and Limits of Length Generalization in Looped Transformers

arXiv:2609.33144v1 Announce Type: new Abstract: Looped Transformers can generalize to reasoning chains longer than those encountered during training, but the computations enabling this behavior and li

tutorialsarxiv-cs-lg

Brain-Conditioned Action Policies for Neural Motor Decoding

arXiv:2609.34561v1 Announce Type: new Abstract: Motor brain-computer interfaces (BCIs) aim to decode motor intention, enabling people with paralysis to control external devices. Neural motor decoding

🚨BREAKING: “Months before OpenAI's artificial intelligence went rogue, two employees raised an alarm with top executives. They were ignored…

🚨BREAKING: “Months before OpenAI's artificial intelligence went rogue, two employees raised an alarm with top executives. They were ignored….OpenAI executives told the employees that the tests needed

safetygary-marcus--x

Building Transformation Layers for Riemannian Neural Networks

arXiv:2609.35436v1 Announce Type: cross Abstract: Recently, deep neural networks on manifold-valued representations have garnered significant attention across various machine learning applications. On

Applications

Calibration-Free Surface Normals Estimation in Vision-Based Tactile Sensing using Universal Photometric Stereo

arXiv:2609.31754v1 Announce Type: new Abstract: Vision-based tactile sensors are a popular solution for capturing rich contact surface geometry. However, to obtain high-detail contact surface normals

applicationsarxiv-cs-cv

CARVE: Breaking Data Barriers in Chip Placement by Harnessing Reusable Expertise

arXiv:2609.33106v1 Announce Type: new Abstract: Pretrained macro-placement policies can reduce repeated optimization across circuits, but deployment often exposes them to unfamiliar designs when the o

CATSplat: Context-Aware Transformer with Spatial Guidance for Generalizable 3D Gaussian Splatting from A Single-View Image

arXiv:2412.12906v3 Announce Type: replace Abstract: Recently, generalizable feed-forward methods based on 3D Gaussian Splatting have gained significant attention for their potential to reconstruct 3D

CFCH: Coarse-Fine Collaborative Hierarchical Learning for Anterior Segment Disease Analysis

arXiv:2609.32559v1 Announce Type: new Abstract: Accurate classification of anterior segment diseases is crucial for ophthalmic screening and diagnosis. However, slit-lamp image analysis remains challe

CODEBLOCK: Learning to Supervise Code at the Right Granularity

arXiv:2606.18286v2 Announce Type: replace Abstract: Supervised fine-tuning of code LLMs typically applies uniform cross-entropy loss to all response tokens, implicitly assuming that every token provid

Collaborative Synthetic Data for Privacy-Preserving Financial Fraud Detection Across Organizational Silos

arXiv:2609.33754v1 Announce Type: new Abstract: Organizations seek analytical value from AI, yet relevant data are often fragmented across organizations and constrained by privacy. This is acute in fi

Conditioned Direct Feedback Alignment via Activity and Error Geometry

arXiv:2607.18574v2 Announce Type: replace Abstract: Direct feedback alignment (DFA) trains hidden layers with fixed random projections of the output error. Even when this feedback provides useful cred

🚨🔥 Congress (@RepJoshG @ValerieFoushee @tedlieu) to OpenAI, Anthropic, Google, Meta, SpaceX on their inadequate reporting of their inadequ…

🚨🔥 Congress (@RepJoshG @ValerieFoushee @tedlieu) to OpenAI, Anthropic, Google, Meta, SpaceX on their inadequate reporting of their inadequately-controlled agents: “Your companies have since notified t

agentsgary-marcus--x

Contextual Distributionally Robust Optimization with Causal and Continuous Structure

arXiv:2601.11016v3 Announce Type: replace-cross Abstract: We propose a framework for contextual distributionally robust optimization (DRO) that considers the causal and continuous structure of the und

Applications

Continuous-Time Trajectory Generation from Discrete Observations with Stochasticity

arXiv:2609.32026v1 Announce Type: cross Abstract: Physical systems evolve continuously in time, yet their states are typically observed only at discrete times. Generating trajectories consistent with

applicationsarxiv-cs-lg

ControlGS: Conditioning Neural Gaussians for Downstream-Processing-Aware XR Rendering

arXiv:2609.32038v1 Announce Type: new Abstract: Extended Reality (XR) users do not directly perceive the output of a rendering engine. Instead, rendered images pass through a post-processing pipeline

Tutorials

Copy the Same, Distill the Difference: Initializing Linear Vision Transformers

arXiv:2609.35745v1 Announce Type: new Abstract: Linear Vision Transformers (ViTs) are designed to replace the attention in Softmax ViTs with the linear-complexity attention operator for more efficient

tutorialsarxiv-cs-cv

CORTEX: A Verified Experience Layer for Generalist Agents

arXiv:2609.33260v1 Announce Type: cross Abstract: An agent can solve a task today and face the same task under new facts, tools, or governing knowledge tomorrow. Most agent systems can retrieve releva

could anything prove more decisively that Jensen Huang is a poor judge of character? his trust in OpenAI is entirely misplaced.

could anything prove more decisively that Jensen Huang is a poor judge of character? his trust in OpenAI is entirely misplaced. 🚨BREAKING: “Months before OpenAI's artificial intelligence went rogue, t

safetygary-marcus--x

Counterfactual Rollout Replay: Forkable Environments as Free Process Rewards for Software Engineering Agents

arXiv:2609.33875v1 Announce Type: cross Abstract: Outcome-only reinforcement learning gives software engineering (SWE) agents a terminal success signal but little direct guidance about intermediate de

Counterfactual Self-Evolving Agents for Evidence-Grounded Reasoning

arXiv:2609.32870v1 Announce Type: cross Abstract: Self-play proposer--solver methods improve reasoning by generating tasks and learning from verified solutions. However, for evidence-identifiable task

Cross-Modal Knowledge Distillation for Acoustic Pedestrian Detection

arXiv:2609.31785v1 Announce Type: cross Abstract: Audio-only pedestrian detection is attractive for urban sensing but limited by weak acoustic cues. An appealing strategy is cross-modal knowledge dist

Local Ai

Cross-Rollout Bellman Closure for Long-Horizon Agentic Reinforcement Learning

arXiv:2609.35082v1 Announce Type: new Abstract: Group-based reinforcement learning such as GRPO trains LLM agents by comparing rollouts sampled for each task, without a learned critic. In long-horizon

local-aiarxiv-cs-lg

cSVR: Convolutional Slice-to-Volume Reconstruction

arXiv:2601.07519v2 Announce Type: replace-cross Abstract: Unpredictable fetal motion during MRI scans can result in oblique 2D slices that are difficult to interpret and often leads to prolonged scan

D-JEPA: Design-Recoverable JEPA Representation with Swappable Physics Decoders

arXiv:2609.33110v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) provide a framework for learning compact representations without directly reconstructing high-dimension

De-biasing Skeleton-based Action Recognition with Convex Hull Adaptive Shift

arXiv:2609.32454v1 Announce Type: new Abstract: Skeleton sequences can represent both individual actions and multi-entity interactions, encompassing human bodies, hands, objects, and robots. Existing

safetyarxiv-cs-cv

DecFlowEdit: Self-Localized Flow-based Image Editing via Guidance Decoupling

arXiv:2609.34237v1 Announce Type: new Abstract: Flow-based image editing (FlowEdit) enables inversion-free semantic changes through the difference between source and target velocities. In this paper,

Decision-Sufficient State Representations: Measuring and Reducing Write-Time Regret

arXiv:2609.32805v1 Announce Type: cross Abstract: Long tasks produce more history than an LLM agent can hold in its context, and more than it uses reliably even when the history fits. A growing line o

agentsarxiv-cs-lg

Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speech

arXiv:2609.33060v1 Announce Type: new Abstract: Speech therapists often face difficulties diagnosing impairments due to the lack of efficient tools for transcribing speech into the International Phone

Denoising Multi-Robot Trajectories

arXiv:2609.35651v1 Announce Type: new Abstract: Multi-robot trajectory planning is a fundamental problem in multi-robot coordination but remains computationally challenging due to its nonconvex, multi

researcharxiv-cs-ro

Depth Laws for the Precision Floor of Trained Neural Networks: Amplification, Residual Scaling, and a Quantization-Aware Training Paradox

arXiv:2609.32060v1 Announce Type: new Abstract: How many bits does a network need before its accuracy collapses, and how does this grow with depth? We study the precision floor, the perturbation level

DexWeave: Learning Dexterous Humanoid Loco-Manipulation from Human Demonstrations

arXiv:2609.34724v1 Announce Type: new Abstract: Learning dexterous humanoid loco-manipulation from human demonstrations requires transferring not only human motion, but also the coordinated interactio

safetyarxiv-cs-ro

DiffMath: Symbol- and Graph-Aware Latent Diffusion Transformer for Handwritten Mathematical Expression Generation

arXiv:2606.19939v2 Announce Type: replace Abstract: Handwritten Mathematical Expression Generation (HMEG) is challenging due to the complex two-dimensional layouts and long-range structural dependenci

Tutorials

DiMoP: Diffusion-Driven Motion Representation Learning With Frame-Level Pseudo-Classification for Skeleton-Based Action Recognition

arXiv:2609.35444v1 Announce Type: new Abstract: Robust skeleton-based action recognition requires representations that capture a wide spectrum of motions, from subtle to moderate and strong ones. Exis

tutorialsarxiv-cs-cv

DirectUV: Image-Conditioned UV Texture Generation with Surface-Aware Positional Encoding

arXiv:2609.34651v1 Announce Type: new Abstract: Generating high-quality UV textures for 3D meshes remains challenging. Multi-view projection pipelines suffer from occlusion and view inconsistency, and

Discovering What You Can Control: Interventional Boundary Discovery for Reinforcement Learning

arXiv:2603.18257v3 Announce Type: replace Abstract: When an RL agent's observations contain distractors driven by the same confounders as its true state, observational data alone cannot identify which

agentsarxiv-cs-lg

Disentangle and Drop: Robust Universal Removal of Image Watermarks via Reconstructive Grayscale Residual Decomposition

arXiv:2609.31693v1 Announce Type: new Abstract: Invisible image watermarks are commonly evaluated against benign postprocessing operations such as compression, resizing, blur, and color changes. These

Do Not Cut When Uncertain: Rejectable and Calibrated Decision Heads for VLA Policies in Robotic Harvesting

arXiv:2609.35039v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies trained with behavior cloning or flow matching are optimized to output an action trajectory, but they cannot expre

researcharxiv-cs-ro

Does Joint-Embedding Predictive Architecture Pretraining Help Time Series Forecasting?

arXiv:2609.31680v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPA) have emerged as a promising self-supervised pretraining paradigm for time series, learning representatio

Does Native 3D Texture Generation Necessarily Require 3D Assets for Training?

arXiv:2609.34621v1 Announce Type: new Abstract: Native 3D texture generation synthesizes colors directly in 3D space for a given geometry, conditioned on multi-view reference images. It is generally b

Does Transolver really need a Transformer?

arXiv:2609.32525v1 Announce Type: new Abstract: The widely used Transolver family of neural operators is based on physics-attention, which softly assigns the points of an unstructured mesh to a small

Local Ai

DOHF: Online Diffusion Fine-tuning with Doob's h-transform Guidance

arXiv:2609.31882v1 Announce Type: new Abstract: Reward-based diffusion fine-tuning faces practical challenges when desirable outcomes are rare or conditioning corrections are costly to estimate. In th

local-aiarxiv-cs-lg