Search: “pretraining”

AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages

arXiv:2606.12708v2 Announce Type: replace-cross Abstract: Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP

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Attention Sensitivity Is Not Enough: Dissociating Attention-Level and Behavioural In-Context Learning under Fine-Tuning

DGX agent

arXiv:2609.00064v1 Announce Type: cross Abstract: In-context learning (ICL) lets large language models adapt to new tasks from demonstrations, and fine-tuning can erode this behaviour. Many preservati

model-releasesarxiv-cs-ai

2 Sept 2026

Auditing Frozen-Encoder Anomaly Detection Across Mechanical Systems: Representation Provenance, Calibration, and Protocol Effects

model-releasesarxiv-cs-lg

arXiv:2601.11415v2 Announce Type: replace-cross Abstract: This version reports a reproducibility audit of the frozen-encoder experiments presented in version 1. The numerical discrimination results ar

Applications

Autoresearch for Marketplace Catalogs: From Legacy Forms to AI-Native Matching

arXiv:2609.00274v1 Announce Type: new Abstract: Two-sided service marketplaces are moving from deterministic request-form intake to AI-native probabilistic matching, enabled by large language models (

applicationsarxiv-cs-ai

Bandits in Prod: Hyperparameter Optimization at Inference Time

arXiv:2609.01335v1 Announce Type: cross Abstract: Many production systems can assess a configuration only by using it on live requests and observing noisy feedback. Modern agentic systems are a promin

safetyarxiv-cs-ai

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

arXiv:2609.00866v1 Announce Type: cross Abstract: The rapid advancement of vision-language models (VLMs) has accelerated progress in computational pathology; however, whole-slide image (WSI)-based pat

Bridging Lexical Divergence: LLM-Assisted, Cost-Efficient, Zero-shot Scientific Entity Linking

arXiv:2609.00228v1 Announce Type: new Abstract: Scientific domain entity linking (EL) differs from general domain EL because mentions and entity names often lack lexical overlap. Another challenge is

Conditional Flow Matching for Cross-Field MRI Harmonisation

arXiv:2609.00960v1 Announce Type: new Abstract: Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data acros

CWoMP: Morpheme Representation Learning for Interlinear Glossing

arXiv:2603.18184v2 Announce Type: replace Abstract: Interlinear glossed text (IGT) is a standard notation for language documentation which is linguistically rich but laborious to produce manually. Rec

researcharxiv-cs-cl

Differentially Private Paired Table-Image Multimodal Synthesis

arXiv:2609.00708v1 Announce Type: cross Abstract: Differentially private (DP) synthesis has been extensively studied for tabular and image data separately, yet many real-world datasets contain images

safetyarxiv-cs-ai

Agents

DNC-IMM: Early Lane-Change Intention Recognition via Neural Calibration Based on Driving Context Information

arXiv:2609.01120v1 Announce Type: cross Abstract: Early recognition of lane-change intention is essential for proactive decision-making in autonomous driving and advanced driver assistance systems. Th

agentsarxiv-cs-ai

Do Satellites See Commuters? A Critical Benchmark of Vision Foundation Models

arXiv:2609.00661v1 Announce Type: new Abstract: Satellite foundation models offer a globally available alternative to census data for commuting origin-destination (OD) generation, yet no study has sys

Applications

Efficiently Estimating Optimal Hyperparameter Scaling Laws through Power-Law Entropy Search

arXiv:2609.01431v1 Announce Type: cross Abstract: Optimal hyperparameter scaling laws describe how the best hyperparameters for large language model (LLM) training change with model and data scale, en

applicationsarxiv-cs-ai

Elite-Weighted Supervised Fine-tuning for Goal-Directed Molecular Optimization

model-releasesarxiv-cs-lg

arXiv:2609.00189v1 Announce Type: new Abstract: Goal-directed optimization is essential for steering molecular generators to propose candidates with desired properties. However, it is often implemente

Good Memory Has ECC: Evaluating the Memory of Vision-Language Models Beyond Accuracy

arXiv:2609.00103v1 Announce Type: cross Abstract: Memory is widely viewed as an important unsolved problem for LLMs and VLMs, and current benchmarks typically evaluate it by testing accuracy over long

H3-World: Turning Language Understanding into World Control

arXiv:2609.01560v1 Announce Type: cross Abstract: We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as

Lightweight Adaptation of EEG Foundation Models for Stroke Motor Imagery Decoding: Domain Shift and Subject-Level Robustness

model-releasesarxiv-cs-lg

arXiv:2609.00282v1 Announce Type: cross Abstract: Motor imagery (MI) electroencephalography (EEG) decoding could support post-stroke rehabilitation, but models developed on healthy cohorts may not tra

LLMPEDIA: Browsing, Verifying, and Comparing the Parametric Encyclopedic Knowledge of LLMs

arXiv:2609.01182v1 Announce Type: new Abstract: Flagship language models appear saturated on benchmarks like MMLU (Hendrycks et al., 2021), scoring above 90% - yet benchmarks test only what the experi

Local Reference Geometry Residual Augmentation for Imbalanced Time Series Classification

arXiv:2609.00093v1 Announce Type: new Abstract: Imbalanced time series classification is often addressed by changing the training distribution, objective, logits, or final threshold. These interventio

researcharxiv-cs-lg

Low-Quality Face Recognition using Center Aligned Representations and Local Margin Constraints

arXiv:2609.01014v1 Announce Type: new Abstract: Low-quality face recognition (LQFR) remains challenging due to the difficulty of matching degraded query (probe) images against low-quality (LQ) enrollm

Agents

Monocular Depth Estimation from a Single Image: Progress and Opportunities

arXiv:2609.01172v1 Announce Type: new Abstract: Monocular depth estimation has long stood as a fundamental challenge in computer vision, enabling a wide range of applications including 3D reconstructi

agentsarxiv-cs-cv

On the Design Fundamentals of Pixel Text Representation Learning

arXiv:2609.01147v1 Announce Type: cross Abstract: Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders strugg

safetyarxiv-cs-cl

Polish ModernBERT: The Long and Short of Polish Language Understanding

arXiv:2609.01379v1 Announce Type: new Abstract: Encoder-only Transformers remain effective for discriminative and representation-learning tasks, yet Polish encoders still largely rely on BERT/RoBERTa-

Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving

arXiv:2609.00111v1 Announce Type: new Abstract: We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of

ReBridge-Flow: Re-Coupling Posterior Bridges in Flow Matching for Image Restoration

arXiv:2609.00811v1 Announce Type: new Abstract: Flow Matching provides an efficient generative prior for image restoration by learning continuous transport between source and data distributions. Howev

researcharxiv-cs-cv

ReNFT: Repairing Mode Collapse in Reward Post-Training via Internal Probability-Mass Recalibration

arXiv:2609.00061v1 Announce Type: cross Abstract: Reward post-training of diffusion generators inevitably concentrates probability mass on a few reward-favored modes, a mode collapse that erases withi

safetyarxiv-cs-ai

Local Ai

Restrict, Don't Retrain: Inference-Time VLM Guidance for Zero-Shot Aerial Segmentation

arXiv:2609.00628v1 Announce Type: cross Abstract: Global welfare often depends on the correct interpretation of aerial and satellite imagery. Acting on such imagery (mapping flooded ground, crop exten

local-aiarxiv-cs-ai

Scaled Idempotence in Transformer Attention: Paired OV Geometry and Shared-Value Algebras

arXiv:2609.01129v1 Announce Type: new Abstract: We identify a recurrent algebraic regularity in Transformer attention: a sparse subset of effective OV operators T=OV^op nearly closes under composition

safetyarxiv-cs-lg

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

arXiv:2504.01547v3 Announce Type: replace Abstract: Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-s

Tutorials

Solving In-Table Prediction Problems by Deep Neural Networks with Performance Evaluation Using Synthetic Data

arXiv:2609.01262v1 Announce Type: new Abstract: Tabular deep learning (TDL) leverages neural networks (NN) to extract patterns from tabular data. Traditional TDL methods follow a supervised learning p

tutorialsarxiv-cs-lg

The Visual Insensitivity Gap: Diagnosing When Vision-Language Models Fail to Use Visual Evidence

arXiv:2609.00868v1 Announce Type: cross Abstract: Vision-language models are evaluated by aggregate accuracy on multimodal benchmarks, a practice that implicitly assumes the model uses its visual inpu

researcharxiv-cs-cl

Training-Free Inpainting Across Domains with a Frozen Text-to-Image Diffusion Model

arXiv:2609.00862v1 Announce Type: new Abstract: We show that a frozen generic text-to-image diffusion model can perform conditional inpainting across three evaluated natural-image domains with one fix

researcharxiv-cs-cv

Uncovering the Computational Ingredients of Human-Like Representations in LLMs

arXiv:2510.01030v2 Announce Type: replace Abstract: The human ability to translate diverse perceptual and linguistic inputs into structured behavior has been thought to rest on learning robust represe

Uncovering Understanding-Generation Synergy in Native Unified Multimodal Models: From Representation, Task to System

arXiv:2609.01607v1 Announce Type: new Abstract: While unified multimodal models (UMMs) jointly perform visual understanding and generation within a single model, functional unification does not guaran

safetyarxiv-cs-cv

Tutorials

Unmasking Face Embeddings: Reading, Rendering and Naming with Foundation Models

arXiv:2609.00411v1 Announce Type: new Abstract: Modern face recognition (FR) owes much of its success to deep neural networks that learn to extract compact identity embeddings from face images. These

tutorialsarxiv-cs-cv

Local Ai

A Simple Transformer Pipeline for Full-Key Side-Channel Attacks on Uncropped Datasets

arXiv:2608.30105v1 Announce Type: cross Abstract: Deep learning-based side-channel analysis has historically focused on single-byte targets and manually cropped traces, which risks discarding exploita

local-aiarxiv-cs-lg

ActiveAugment: Online Active Learning for Augmentation Selection in Deep Learning

arXiv:2608.28923v1 Announce Type: cross Abstract: Data augmentation is a cornerstone of deep learning pipelines, yet existing strategies treat it as a static, model-agnostic preprocessing step, either

AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization

model-releasesarxiv-cs-ro

arXiv:2608.29242v1 Announce Type: new Abstract: Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also

Applications

BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning

arXiv:2608.29553v1 Announce Type: new Abstract: Geospatial foundation models such as the AlphaEarth Foundation produce compact and globally consistent representations of the Earth's surface that trans

applicationsarxiv-cs-lg

Brain-Language-Action (BLA) Models: Language-Conditioned EEG for Robotics Control

arXiv:2608.28967v1 Announce Type: cross Abstract: Electroencephalography (EEG)-based robotic control is commonly formulated as a direct classification problem, in which electrical neural signals are m

researcharxiv-cs-lg

Can LLMs Take the Pulse of the Economy? A Real-Time Evaluation of LLM Nowcasts on Macroeconomic Indicators

arXiv:2608.30110v1 Announce Type: cross Abstract: Nowcasting headline macroeconomic indicators, i.e., estimating an indicator's value for the current reference period before its official release, is c

Capability-Stratified Degradation in Ternary Language Models

arXiv:2608.28809v1 Announce Type: new Abstract: Extreme low-bit inference offers a route toward smaller models and constrained deployment. Ternary language models restrict weights to {-1,0,+1}, approa

CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests

arXiv:2608.30149v1 Announce Type: new Abstract: Individual tree measurements derived from Light Detection and Ranging (LiDAR) mounted on Unmanned Aerial Vehicles (UAV) provide valuable information for

researcharxiv-cs-cv

Ceiling-Clipped Acceptance Histograms Indicate Stranded Speed-up in Block-Diffusion Speculative Decoding

arXiv:2608.30427v1 Announce Type: new Abstract: Speculative decoding speeds up generation with an efficient draft model (drafter) that proposes tokens for a target model to verify in one pass, preserv

Local Ai

CheXGround: Anatomical Region Tokens for Grounded Longitudinal Chest X-ray Interpretation

arXiv:2608.30758v1 Announce Type: new Abstract: Recent radiology multi-modal language models have made substantial progress in chest X-ray report generation, visual question answering, and temporal re

local-aiarxiv-cs-cv

CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification

arXiv:2502.18176v3 Announce Type: replace-cross Abstract: In this paper, we aim to build an adversarially robust zero-shot image classifier. We ground our work on CLIP, a vision-language pre-trained e

Tutorials

Denoising as Projection: Constrained Optimization with Gradient-Guided Diffusion

arXiv:2608.29507v1 Announce Type: cross Abstract: Diffusion models are increasingly used not only for sampling from learned data distributions, but also for generating samples that optimize task-speci

tutorialsarxiv-cs-ai

DocIntent: Answerability-Guided Agentic Restoration for Real-World Document Visual Question Answering

arXiv:2608.29037v1 Announce Type: cross Abstract: Real-world degradations such as blur, shadow, distortion, and moire patterns severely impair the document question-answering capabilities of Multimoda