Search: “pretraining”

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

model-releasesarxiv-cs-cl

arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and

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Research

Self-Indexing Attention for Compression-Compatible Sparse Long-Context LLM Inference

DGX agent

arXiv:2609.13205v1 Announce Type: cross Abstract: Sparse long-context inference requires efficient token retrieval in both prefill and decode. Existing methods often use different retrieval strategies

researcharxiv-cs-cl

15 Sept 2026

Single-step Diffusion-based Video Coding with Semantic-Temporal Guidance

arXiv:2512.07480v2 Announce Type: replace Abstract: While traditional and neural video codecs (NVCs) have achieved remarkable rate-distortion performance, improving perceptual quality at low bitrates

Small Object Detection in Drone Aerial Imagery with LAF-YOLOv10

arXiv:2609.14560v1 Announce Type: new Abstract: General-purpose object detectors lose accuracy on UAV footage, where targets span only a handful of pixels and onboard compute is limited. Prior work co

SomBench: Benchmark Dataset for Advancing Machine Learning in Lunar Science

arXiv:2609.13277v1 Announce Type: new Abstract: Lunar orbital missions, such as Lunar Reconnaissance Orbiter, Kaguya/SELENE, Gravity Recovery and Interior Laboratory, and Lunar Prospector, among other

StereoPatch: Patch-Aligned RGB-Depth Fusion for Spatial Perception in Robot Manipulation

arXiv:2609.15509v1 Announce Type: new Abstract: Recent advances in robot imitation learning have produced visuomotor policies that predict actions directly from visual observations. Yet visually simil

safetyarxiv-cs-ro

Synthetic Leprosy Image Generation Using Mask-Conditioned Latent Diffusion and Transfer Learning from Large Chronic Wound Datasets

arXiv:2609.13226v1 Announce Type: new Abstract: Machine learning for neglected tropical diseases is limited by data, not algorithms: public annotated image sets for leprosy (Hansen's disease) number i

Task-Based CT Protocol Optimization Using Reinforcement Learning and Virtual Imaging Trials

arXiv:2609.13309v1 Announce Type: cross Abstract: Protocol optimization in computed tomography (CT) aims to improve diagnostic image quality while reducing radiation dose, but the interdependence of a

safetyarxiv-cs-ai

Through the Eyes of the Beholder: Biometric and Demographic Conditioning for Multimodal Sexism Detection

model-releasesarxiv-cs-ai

arXiv:2609.15608v1 Announce Type: cross Abstract: Detecting sexism on the internet is a fundamentally subjective task; our team, VANGUARD, addresses this challenge in the EXIST 2026 Task 2 by proposin

To Each Language Its Tokenizer: Modular Tokenizers for Efficient Multilingual LLMs

arXiv:2609.15528v1 Announce Type: new Abstract: Multilingual Large Language Models (LLMs) traditionally rely on a single vocabulary shared by all supported languages, which can lead to uneven compress

safetyarxiv-cs-cl

Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2601.04260v2 Announce Type: replace Abstract: Understanding how Large Language Models (LLMs) perform logical reasoning internally remains a fundamental challenge. While prior mechanistic studies

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

researcharxiv-cs-ai

When Edit Localization Amplifies Relative Selection Bias: Gradient Geometry, Target Mismatch, and Importance Weighting

arXiv:2609.13709v1 Announce Type: new Abstract: Human corrections identify editable spans, but the examples receiving corrections may come from a selective feedback channel. We analyze this interactio

safetyarxiv-cs-cl

Tutorials

Aligning Language Models with Observational Data: Opportunities and Risks from a Causal Perspective

arXiv:2506.00152v2 Announce Type: replace Abstract: Large language models are being widely used across industries to generate text that contributes directly to key performance metrics, such as medicat

tutorialsarxiv-cs-lg

Beyond Argmax: A Mechanistic Study of Semantic Retention in Frozen Foundation-Model Composition for Generalized Few-Shot 3D Segmentation

arXiv:2609.12099v1 Announce Type: new Abstract: Classical classifier-combination work distinguishes score-level fusion from hard decision-level voting. We revisit this distinction where independently

Bridging Vision Foundation Model Priors with CLIP for Spatial-aware Few-shot Anomaly Detection in Medical Images

arXiv:2609.12454v1 Announce Type: new Abstract: Vision-Language Models such as CLIP enable effective few-shot medical anomaly detection (AD) via strong image-text semantic alignment. However, their gl

Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

arXiv:2609.12994v1 Announce Type: new Abstract: Heavy-tailed empirical spectral densities of neural-network weight matrices are widely used as diagnostics of implicit self-regularization, but the step

DRDN: Decoupled Representation Dynamic Network for From-Scratch ViT Class-Incremental Learning

arXiv:2607.01630v2 Announce Type: replace Abstract: Dynamic expansion methods for class-incremental learning (CIL) protect task-specific knowledge by growing dedicated tokens or subnetworks, yet our a

Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration

arXiv:2609.11995v1 Announce Type: new Abstract: Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains chall

Fixed State, Long Reach: What a Constant-Size Cache Buys Block Diffusion at Scale

arXiv:2609.11998v1 Announce Type: new Abstract: Diffusion language models decode tokens in parallel, but their bidirectional denoiser rules out the naive key--value (KV) cache behind fast autoregressi

safetyarxiv-cs-lg

I Am No One: Style-Aware Paraphrasing for Text Anonymization

arXiv:2609.12341v1 Announce Type: new Abstract: Authorship attribution models can re-identify users from seemingly anonymized text by exploiting stable stylistic fingerprints, even after explicit iden

researcharxiv-cs-cl

Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging

arXiv:2606.14957v4 Announce Type: replace Abstract: Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic an

LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification

arXiv:2609.12915v1 Announce Type: new Abstract: Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of

researcharxiv-cs-cl

Nonlinear Dimensionality Reduction Techniques for Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2510.15435v2 Announce Type: replace-cross Abstract: Bayesian optimisation (BO) enables sample-efficient global optimisation of expensive black-box functions but remains challenging in high dimen

Predicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion

arXiv:2609.12223v1 Announce Type: new Abstract: Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation. Prediction is challenging f

Tutorials

Representation-based Masked Diffusion Model

arXiv:2609.12382v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) have emerged as a compelling paradigm for language modeling, offering the capability for efficient parallel text generati

tutorialsarxiv-cs-cl

Residual Vector-based Reconstruction as Long-Context Recall Regardless of Context Window Size

model-releasesarxiv-cs-cl

arXiv:2609.12686v1 Announce Type: cross Abstract: Large language models (LLMs) process long contexts, including long documents and lengthy conversations, but face token-level memory usage that increas

RunningTensor: Generalizing Linear Attention to Higher-Order Recurrent States

arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi

Sampling via Decision-Flow: Training-Free Extraction of Improved Latent Reasoning Paths in Large Language Models

arXiv:2609.12317v1 Announce Type: new Abstract: A central question in LLM reasoning is whether reinforcement learning (RL) instills genuinely new capabilities or merely reshapes how existing knowledge

Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning

model-releasesarxiv-cs-lg

arXiv:2502.07250v3 Announce Type: replace Abstract: Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many

Applications

UniLayDiff: A Unified Diffusion Transformer for Content-Aware Layout Generation

arXiv:2512.08897v2 Announce Type: replace Abstract: Content-aware layout generation is a critical task in graphic design automation, focused on creating visually appealing arrangements of elements tha

applicationsarxiv-cs-cv

Hardware

Characterizing Job Power Elasticity for Power-Flexible AI Training

arXiv:2609.11542v1 Announce Type: new Abstract: Large language model (LLM) training is among the fastest-growing sources of electricity demand in modern data centers, and power availability is a prima

hardwarearxiv-cs-ai

12 Sept 2026

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

model-releasesarxiv-cs-ai

arXiv:2609.11859v1 Announce Type: new Abstract: How does a language model's dependence on query-routing information and target knowledge change as it answers a question? We study this question through

12 Sept 2026

Adaptive Diffusion Freezing: Privacy-preserving Diffusion Models Against Membership Inference Attacks

arXiv:2609.10608v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in generative tasks across various areas, however their training process raises significant privacy

safetyarxiv-cs-lg

Local Ai

BruNet: A Cross-Domain Transfer Framework for Bruise Segmentation

arXiv:2609.11463v1 Announce Type: new Abstract: Segmenting bruises is a challenging task in medical imaging due to limited data and annotations, diffuse boundaries, and highly variable appearance. In

local-aiarxiv-cs-cv

Applications

Combining Synthetic and Real Data for Low-Resource Historical OCR: A Manchu Case Study

arXiv:2609.11495v1 Announce Type: new Abstract: Manchu, now critically endangered, was one of the principal languages of the Qing empire (1636-1912), and its extensive archival record is increasingly

applicationsarxiv-cs-lg

Detectable Only Where It Is Confounded: What Verified Duplication Counts Say About Membership Evidence in Language Models

arXiv:2609.10830v1 Announce Type: new Abstract: When a language model finds a sentence unusually cheap to predict, it is tempting to conclude that the sentence was in its training data. Almost every p

researcharxiv-cs-cl

E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets

model-releasesarxiv-cs-cl

arXiv:2609.11334v1 Announce Type: new Abstract: Natural Language Inference processes pairs of sentences to extract their semantic relations. NLI has been a hot research topic, integrated as a main com

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

arXiv:2609.11872v1 Announce Type: cross Abstract: Continuous glucose monitoring (CGM) provides high-frequency measurements of glucose dynamics and enables short-term glucose forecasting for diabetes m

Agents

ExpTest: Loss-Curve Hypothesis Testing for Autonomous Learning-Rate Selection in Deep Neural Networks

arXiv:2411.16975v2 Announce Type: replace Abstract: Hyperparameter tuning remains a significant challenge in the training of deep neural networks (DNNs), requiring manual search or time-intensive grid

agentsarxiv-cs-lg

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

model-releasesarxiv-cs-ro

arXiv:2609.11445v1 Announce Type: new Abstract: Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring

GRADE: Single-Frame Generative Radar Depth Estimation Under Visual Degradation

arXiv:2609.10756v1 Announce Type: new Abstract: Dense 3D depth perception fails under smoke, fog, and darkness because optical sensors cannot penetrate airborne particulates. mmWave radar remains usab

HiPerViT: A Hierarchical Perceiver-Vision Transformer Architecture for Multi-Scale Texture Recognition

arXiv:2609.10917v1 Announce Type: new Abstract: Texture recognition remains challenging for modern vision models because discriminative evidence is often carried by higher-order spatial statistics rat

InstantHDR: Single-forward Gaussian Splatting Initialization for HDR 3D Reconstruction

arXiv:2603.11298v3 Announce Type: replace Abstract: High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR

Logit Refiner: Improving Visual Autoregressive Models via Intra-Scale Dependency Modeling

arXiv:2609.11804v1 Announce Type: new Abstract: Visual Autoregressive Models (VAR) generate images through next-scale prediction, producing all tokens within each scale in parallel. We show that this

Measuring the Value of World-Model Updates: A Counterfactual Utility Protocol for Continual Adaptation

arXiv:2609.10954v1 Announce Type: new Abstract: Continual world models must decide whether new data justify changing the model. Fixed replay schedules and prediction-error triggers specify when to upd

Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

arXiv:2609.11842v1 Announce Type: new Abstract: Diffusion and flow-matching schedules control the signal and noise coefficients that mix data and noise along affine probability paths. Minimizing a kin

Overpainting: Localized Context-aware Diffusion Image Editing

arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t