All entries

Loop Dropout: Regularizing Shared Updates in Looped Language Models

arXiv:2609.34218v1 Announce Type: new Abstract: Looped language models separate computational depth from parameter count by repeatedly applying the same transformer block. Adapting these models requir

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

LoopLUT: 3D Lookup Tables with Progressive Region Refinement for Real-Time 4K Image Enhancement

DGX agent

arXiv:2609.33593v1 Announce Type: new Abstract: Color enhancement of 4K images must meet a quality target under a tight compute budget. Three-dimensional lookup tables (3D LUTs) dominate real-time enh

researcharxiv-cs-cv

29 Sept 2026

LoopTrack: A Simple Baseline for Parameter-Efficient Transformer Tracking

model-releasesarxiv-cs-cv

arXiv:2609.33306v1 Announce Type: new Abstract: Current Transformer-based tracking methods typically stack multiple Transformer blocks with separate parameters to model interactions between the target

Low-Confidence Remasking Traps Flexibility: Realizing Arbitrary-Order Potential for Diverse Rollouts in Diffusion LLMs

arXiv:2609.34509v1 Announce Type: new Abstract: Masked diffusion language models support arbitrary-order generation, suggesting a natural way to produce diverse outputs. However, recent work argues th

Low Cost Eye Tracking for Vision Screening

arXiv:2609.31941v1 Announce Type: new Abstract: This engineering study assesses gaze-assisted data acquisition during visual screening with a Gaze Quest implementation via webcam and GC308 near infrar

researcharxiv-cs-ro

Low-Rank Single-Index Bandits with Unknown Links: From Matrices to Tensors

arXiv:2609.33025v1 Announce Type: new Abstract: Low-rank matrix and tensor bandits exploit structured interactions but typically assume a known reward link. Recent single-index bandit methods accommod

Hardware

Lower the Cost of Building and Running Visual AI Agents with NVIDIA VSS Blueprint 3.3

NVIDIA released VSS Blueprint 3.3, a framework that stitches together vision‑language models (Cosmos), LLMs (Nemotron) and retrieval‑augmented generation to convert live or recorded video into natural

hardwarenvidia-developer

LQR-ArUco Fusion: Robust Hierarchical Control for Navigation and Asymmetric Manipulation in Two-Wheeled Robots

arXiv:2609.35700v1 Announce Type: new Abstract: We propose a hierarchical control framework to address severe dynamic instabilities and navigational drift that arise when a two-wheeled inverted pendul

researcharxiv-cs-ro

LRC-JEPA: Disentangling Dynamics and Residual Context for Efficient World Models

arXiv:2609.34375v1 Announce Type: new Abstract: Compact JEPA world models enable efficient latent-space planning, but low-dimensional representation trained under reward-free self-supervision must enc

LTV-CTDNet: Compositional Turning Decomposition for Short-Term Turning-Movement Forecasting

arXiv:2609.34014v1 Announce Type: new Abstract: Short-term turning-movement forecasts can support signal control and corridor operations, but unconstrained neural networks may produce physically impos

L{}ukasiewicz Neural Networks Extended: Residual Architectures and Crystallization Strategies for Interpretable Rule Extraction

arXiv:2609.33028v1 Announce Type: new Abstract: A feed-forward neural network whose weights are integers and whose activation is the truncated identity implements, neuron by neuron, the connectives of

LukeNet: A lightweight CNN integrated with an XAI model for Smart acute lymphoblastic leukemia detection and management

arXiv:2609.31736v1 Announce Type: new Abstract: Acute Lymphoblastic Leukemia (ALL) patients require early, accurate detection to enable timely treatment and effective patient management. A Convolution

Tutorials

LVMT: Video Mask Transformer for Long-term Video Segmentation

arXiv:2609.34895v1 Announce Type: new Abstract: Existing online video segmentation methods struggle to track objects in long, complex videos with long-term occlusions. We hypothesize that this limitat

tutorialsarxiv-cs-cv

M3-Score: Fidelity, Memorization and Coverage as Separate Axes for Evaluating Generative Radiology Image Models

arXiv:2609.33769v1 Announce Type: new Abstract: Quantitative evaluation of generative models for radiology remains challenging. Clinically relevant structures are often small and infrequent, feature s

M3OS: A Monte Carlo Graph Search-Orchestrated Multi-Agent LLM System for Evidence-Traced Molecular Optimization

arXiv:2609.34491v1 Announce Type: new Abstract: Small-molecule optimization integrates medicinal-chemistry reasoning and computational evidence through iterative, multi-objective decisions. When large

MA-JEPA: Joint-Embedding World Models for Multi-Agent Reinforcement Learning

arXiv:2609.33563v1 Announce Type: new Abstract: World models improve sample efficiency by training policies on imagined trajectories, but their usefulness depends on learning representations that capt

Machine learning for the LHC physics program: a 2025-2026 stocktake

arXiv:2609.32874v1 Announce Type: cross Abstract: The first sentence of this abstract--and the introduction to these proceedings--was authored by a human, but the bulk of this document was generated b

MAD-Guard: Controlled Study of Autoregressive Generation versus Direct Decision Interfaces for Closed Multimodal Forensic Tasks

arXiv:2609.33683v1 Announce Type: new Abstract: When should multimodal foundation models generate tokens, and when should they directly output a decision? We present MAD-Guard, a controlled study of o

MaD-RL: Matching Distributions for Calibrating LLMs with Reinforcement Learning

arXiv:2609.31644v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used in language-model post-training to maximize rewards assigned to individual model outputs, such as scores from

MAESTRO: a Multimodal Auditory-attention Egocentric Speech-TRacking Open corpus

arXiv:2609.31898v1 Announce Type: cross Abstract: Humans rely on gaze, head movements, and visual cues to attend to speakers in noisy environments, yet auditory attention decoding (AAD) has been studi

Maintaining Benchmarks Against Increasingly Capable Agents: Detection and Remediation of Unearned Passes

arXiv:2609.34262v1 Announce Type: cross Abstract: Agentic benchmarks guide model selection and training. Yet an agent can pass a task without demonstrating the intended capability. Such outcomes const

Making LLMs Truly Forget: Deep Unlearning by Searching, Selecting, and Severing Knowledge Paths

arXiv:2609.34442v1 Announce Type: new Abstract: While an unlearned language model may no longer recall a fact directly, the fact often remains recoverable through multi-hop reasoning over related know

MaLiang-Harness: A Programmable Path to Image and Video Generation

arXiv:2609.34309v1 Announce Type: new Abstract: Executable programs offer explicit control over how images and videos are constructed, but generating runnable code is only the beginning of visual crea

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

Tutorials

Managing Self-Learning Experts under Per-Round Budget Constraints

arXiv:2510.22654v3 Announce Type: replace Abstract: This paper addresses the problem of sequential decision-making under learning budget constraints. Such settings naturally arise in applications like

tutorialsarxiv-cs-lg

Manifold limit for the training of shallow graph convolutional neural networks

arXiv:2601.06025v2 Announce Type: replace-cross Abstract: We study the discrete-to-continuum consistency of the training of shallow graph convolutional neural networks (GCNNs) on proximity graphs of s

Manifold-Stable Flow Matching

arXiv:2609.35454v1 Announce Type: new Abstract: Flow matching (FM) learns generative dynamics through velocity regression. Geometric FM variants commonly assume a prior supported on the data manifold,

Many Eyes, One World: Feed-Forward 3D Reconstruction from Mixed Cameras

model-releasesarxiv-cs-cv

arXiv:2609.35658v1 Announce Type: new Abstract: Real-world capture is heterogeneous: perspective, fisheye, and 360^irc panoramic images can coexist within a single reconstruction task, yet most feed-f

MaPP: A Unified Marginalized Posterior-Predictive Framework for Data-Efficient RLVR

arXiv:2609.34990v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models but incurs substantial costs from rol

Marathoner: Ultra-Long-Horizon Autonomous Intelligence

arXiv:2609.34378v1 Announce Type: new Abstract: Humans naturally possess the ability to work persistently toward long-term goals. Given a challenging task, humans can continuously work for months or e

agentsarxiv-cs-cv

Hardware

MarsLab: A Martian Rover Simulator for Planetary Rover Autonomous Navigation

arXiv:2609.34702v1 Announce Type: new Abstract: Future Mars missions will require rover autonomy that can operate across unstructured terrain, changing illumination, atmospheric dust, and limited comm

hardwarearxiv-cs-ro

MASCIT: A Mask-Aware State Space Classifier for Naturally Irregular Time Series

arXiv:2609.34409v1 Announce Type: new Abstract: Naturally irregular time series combine asynchronous observations, missing values, unequal lengths, and nonuniform sampling, while dense adapters can di

Mask-Induced Displacement in Audio XAI via Logit Trajectory Decomposition

arXiv:2609.33486v1 Announce Type: cross Abstract: Perturbation-based XAI methods for audio classifiers often estimate feature importance by masking spectrogram regions and crediting output changes to

Mask2Restore: Self-Supervised Ultrasound Despeckling via Inpainting

arXiv:2609.32844v1 Announce Type: cross Abstract: Medical ultrasound (US) is inherently degraded by speckle, a granular interference pattern that is often treated as a complex form of noise in image r

safetyarxiv-cs-cv

MaskCoFT: Masked Co-Adaptive Fine-Tuning for Memory-Efficient MoE Inference

arXiv:2609.34077v1 Announce Type: new Abstract: Mixture-of-experts (MoE) language models often exceed the memory of a single GPU. Expert offloading keeps most experts in host memory and loads them on

Masking Frequent Tokens Sharpens Direct Preference Optimization

arXiv:2609.32445v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) aligns language models by optimizing over sequence-level sums of token-wise implicit reward differences. However,

MASTEST: A LLM-Based Multi-Agent System For Testing RESTful APIs

arXiv:2511.18038v2 Announce Type: replace-cross Abstract: Testing RESTful API is increasingly complicated but indispensable to quality assurance of cloud-native applications. This paper reports a mult

MDL-Calibrated Significance-Gain Pair Encoding: Replication-Aware Automatic Stopping for Subword Tokenization

model-releasesarxiv-cs-cv

arXiv:2609.31705v1 Announce Type: new Abstract: Byte-Pair Encoding (BPE) constructs subword vocabularies through greedy pair merging, but conventional BPE requires the number of merges or target vocab

Measure Learning at Steady State: A BIRD-SQL Formula 1 Case Study

arXiv:2609.31640v1 Announce Type: new Abstract: Continual Learning Bench scores learning as short-horizon gain versus a reset baseline and finds naive full-context ICL strongest among the memories it

Measurement Boundaries in LLM Financial Agent Evaluation: Fixed-Tape Execution and Multi-Defect Auditing

arXiv:2609.32379v1 Announce Type: new Abstract: What controls are needed to interpret execution performance and audit scores in LLM agent evaluations? We study two limits on these interpretations in a

Measurement-Error-Aware Causal Distributed-Lag Quantile Modeling of Indoor Air Pollution and Short-Term Lung-Function Deterioration

arXiv:2609.31646v1 Announce Type: cross Abstract: Low-cost indoor air-quality sensors could support personalized asthma prevention, but their nonlinear measurement error, delayed exposure effects, tim

Measurement-Gated Provenance Attenuation for Frozen EEG Representations

arXiv:2609.32889v1 Announce Type: new Abstract: Frozen EEG representations retain acquisition signatures as well as neural activity. Source predictability alone does not identify what should be remove

Measuring the evolution of camera distance across a century of film

arXiv:2609.31734v1 Announce Type: new Abstract: The rise of computer vision and artificial intelligence has made possible new forms of large-scale computational measurement. We apply these techniques

Mechanistic Interpretability Reveals Shared Causal Subspaces in Brain-to-Speech Decoders

arXiv:2609.31992v1 Announce Type: new Abstract: Decoding covert speech, such as mimed or imagined, from brain activity is harder than decoding vocalized speech. Cross-modal transfer, where information

MechBench: Can AI Scientific Agents Discover Mechanisms Beyond Phenomenal Laws?

arXiv:2609.35515v1 Announce Type: cross Abstract: Scientific discovery requires not only recovering mathematical laws that describe observable behavior, but also identifying the mechanisms that genera

Applications

Medium-Term Multi-Resolution Electric Load Forecasting using Economic Data and Foundation Model

arXiv:2609.31806v1 Announce Type: new Abstract: Accurate medium-term, from a few months to a few years, electricity load forecasts are crucial for informed decision-making in power plant maintenance s

applicationsarxiv-cs-lg

MegaGraph: Towards Efficient Training of Large-Scale Graph Transformers with Automated Hybrid Parallelism

arXiv:2609.34420v1 Announce Type: new Abstract: Graph Transformers (GTs) offer superior representation capabilities by overcoming the depth limitations and over-smoothing issues of traditional Graph N

Memory as a cache: Exact context reuse and deletion by construction

arXiv:2609.32395v1 Announce Type: cross Abstract: The KV cache of a transformer entangles every token's representation with its entire prefix: a passage encoded once cannot be reused under a different