Search: “pretraining”

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

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

DGX agent

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

1 Sept 2026

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

DREAM: Deployment-Time Demonstration Generation via Real-to-Sim for Scalable Policy Adaptation

arXiv:2608.29078v1 Announce Type: new Abstract: Vision-language-action (VLA) models have made strong progress in language-conditioned robot manipulation, but improving their performance in a new works

safetyarxiv-cs-ro

Efficient JPEG Restoration in the Wavelet Domain via Mean Flows

arXiv:2608.28730v1 Announce Type: cross Abstract: Latest JPEG restoration systems achieve strong quality with large models, yet often remain too slow and expensive for efficient on-device deployment.

Efficient Language-to-Vision Feature Injection for Referring Single-Object Tracking

arXiv:2608.29126v1 Announce Type: new Abstract: Referring single-object tracking enables language-grounded target initialization and subsequent tracking by jointly leveraging semantic cues and visual

safetyarxiv-cs-cv

Elastic Token Compression for Pixel-Space Diffusion Transformers

arXiv:2608.29281v1 Announce Type: new Abstract: Natural images concentrate their detail in a small fraction of the frame, yet diffusion models spend a full token on every patch, in every layer and at

Enhancing Low-Resource Language Reasoning via High-Resource Language Feature Transfer

arXiv:2608.30462v1 Announce Type: cross Abstract: Large language models exhibit substantial performance variation across languages, even when solving semantically equivalent tasks. Existing analyses o

Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection

arXiv:2608.29802v1 Announce Type: new Abstract: Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Pres

GAFT: Geo-Anchored Fine-Tuning for Hazard Identification from Rare Failures

arXiv:2608.30858v1 Announce Type: cross Abstract: Off-road navigation can fail when physical structures induce irrecoverable states such as high-centering or entrapment, requiring human interventions.

GarmentWeaver: Schema-Aware Structured Synthesis for Multimodal Sewing Patterns

arXiv:2608.30550v1 Announce Type: new Abstract: Multimodal Sewing pattern generation aims to infer executable sewing patterns from design cues such as sketches and textual descriptions. As an interpre

local-aiarxiv-cs-ai

GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models

arXiv:2608.29395v1 Announce Type: new Abstract: Vision-language models such as CLIP and SigLIP provide strong zero-shot recognition, but their predictions can degrade when deployed on target data that

GeoRay: Gauge-Aware Feed-Forward Satellite 3D Reconstruction in the Geodetic Frame

arXiv:2608.29680v1 Announce Type: new Abstract: Feed-forward 3D foundation models reconstruct perspective scenes in one pass. Satellite photogrammetry needs a different product, one that domain adapta

HSRM: Hidden-State Reward Models for Test-Time Verification

arXiv:2608.30841v1 Announce Type: new Abstract: Large language models can often generate plausible mathematical reasoning traces, but reliably identifying the correct solution among multiple candidate

Hyper-Fold: Exploring the Expressive Limit of Sequence-Geometry Learning for Proteins via Hypergraph Modeling

arXiv:2608.29207v1 Announce Type: new Abstract: Protein structure modeling rests on a single computational primitive: the interaction between what a residue is (sequence content) and where it sits (th

Identity-Conditioned Latent Consistency Distillation for Face Synthesis

arXiv:2608.31053v1 Announce Type: new Abstract: Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation comput

Agents

Language-Guided Tuning: Configuration Optimization for Automated ML Research

arXiv:2508.15757v2 Announce Type: replace Abstract: Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strat

agentsarxiv-cs-ai

Agents

Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey

arXiv:2508.13073v3 Announce Type: replace-cross Abstract: Robotic manipulation, a key frontier in robotics and embodied AI, requires precise motor control and multimodal understanding, yet traditional

agentsarxiv-cs-cv

Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification

arXiv:2607.10851v2 Announce Type: replace Abstract: Medical image classification models are ideally expected to identify diagnostically relevant regions while making predictions, yet standard classifi

local-aiarxiv-cs-cv

Learning to infer and manipulate through distributed whole-arm interaction in a soft robot

arXiv:2608.30773v1 Announce Type: new Abstract: In animals such as elephants and octopuses, acquiring non-visual information about an object and physically engaging with it are inseparable processes m

local-aiarxiv-cs-ro

Applications

LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation

arXiv:2608.30935v1 Announce Type: cross Abstract: Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodi

applicationsarxiv-cs-ai

Loci Similes: A Benchmark for Extracting Intertextualities in Latin Literature

arXiv:2601.07533v3 Announce Type: replace-cross Abstract: Tracing connections between historical texts is an important part of intertextual research, enabling scholars to reconstruct the virtual libra

Low-Resource Preference Adaptation of LLMs via Activation-Based Label Propagation

arXiv:2608.30902v1 Announce Type: new Abstract: Adapting large language models to user-specific preferences is often constrained by the cost of human annotation, making preference optimisation impract

safetyarxiv-cs-cl

Manaca-1B: An Open, Reproducible Brazilian-Portuguese Language Model and a Tokenizer-Aware, Paired Evaluation

arXiv:2608.30114v1 Announce Type: new Abstract: Brazilian Portuguese remains under-served by open language models, and the few that exist are difficult to reproduce and are often compared without meas

Medical Foundation Model Features as Perceptual Loss for Brain MRI Contrast Dose Simulation

arXiv:2608.28773v1 Announce Type: cross Abstract: Perceptual losses are widely used in medical image synthesis because they encourage agreement in high-level structure beyond voxel-wise intensity simi

Tutorials

MEOM: Multi-View Expected-OKS Maximization for Human Pose Triangulation

arXiv:2608.30521v1 Announce Type: new Abstract: Conventional algebraic triangulation solves 3D human pose estimation (HPE) from multi-view 2D keypoints. The typical approach, decoding 2D keypoints fro

tutorialsarxiv-cs-cv

NBS: No Bias Stereo

arXiv:2608.28933v1 Announce Type: new Abstract: Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias.

safetyarxiv-cs-cv

Normalized Low-Rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2608.31036v1 Announce Type: new Abstract: While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effecti

On the Design of Qwen3.8-Next Architecture: Evaluation, Efficiency, and Training Stability

arXiv:2608.30320v1 Announce Type: new Abstract: We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B parameters, 6B activated per token, and ad

One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning

arXiv:2608.31096v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires a model to incrementally learn tasks that contain new classes without accessing earlier training data while pr

Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion

arXiv:2603.03485v4 Announce Type: replace-cross Abstract: Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often strugg

Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training

arXiv:2608.30609v1 Announce Type: cross Abstract: Large language models are increasingly capable in general, but their utility can remain modest in niche or understudied areas. One approach to address

Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions

arXiv:2608.29109v1 Announce Type: new Abstract: Large language models often answer structurally unanswerable questions, such as computing cot(-540{eg}) or evaluating (1).startswith('1'), instead of ab

safetyarxiv-cs-cl

RegionFM: Interpretable Region-Based Brain MRI Classification Using Foundation Model Embeddings

arXiv:2607.16325v2 Announce Type: replace Abstract: Foundation models provide powerful representations for brain MRI analysis, but their predictions remain difficult to interpret in anatomically meani

Robustness of Vision Language Models Against Split-Image Harmful Input Attacks

arXiv:2602.08136v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are now a core part of modern AI. Recent work proposed several visual jailbreak attacks using single/ holistic i

safetyarxiv-cs-ai

Tutorials

SePArate: Segmenting Patterns from Defects in Wafer Manufacturing Using Weak Supervision

arXiv:2608.30410v1 Announce Type: cross Abstract: In semiconductor manufacturing, defect analysis is essential, but manual inspection cannot scale. However, existing automated inspection methods remai

tutorialsarxiv-cs-ai

SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification

arXiv:2512.15052v4 Announce Type: replace-cross Abstract: Disclaimer: Samples in this paper may be harmful and cause discomfort. Multimodal large language models (MLLMs) enable multimodal understandin

SGPDFuse: Semantically-Guided Physics-Disentanglement General Multi-Modal Image Fusion

arXiv:2608.29220v1 Announce Type: new Abstract: Multimodal image fusion (MMIF) aims to integrate complementary sensor data into a single representation that preserves intrinsic scene reality while eli

safetyarxiv-cs-cv

Sketch2Inspire: Structure-Sensitive Evaluation for Product Retrieval

arXiv:2608.29364v1 Announce Type: new Abstract: Early-stage product design retrieval often requires more than category recognition: designers may need reference examples that match both a short semant

Subtraction-Based Tumor Segmentation and Lesion-Centered pCR Prediction for the MAMA-MIA Challenge

arXiv:2608.29162v1 Announce Type: cross Abstract: We describe the submission of team FME to the MAMA-MIA Challenge, which evaluated primary tumor segmentation and prediction of pathological complete r

safetyarxiv-cs-ai

SynCrash: A Multi-Stage Pipeline for Zero-Shot Accident Detection and Localization in Traffic Surveillance Video

arXiv:2608.29759v1 Announce Type: cross Abstract: We present SynCrash, a multi-stage pipeline for zero-shot accident detection, spatial localization, and collision-type classification in fixed-view CC

local-aiarxiv-cs-ai

Temporal Forcing: 4D Representation Alignment for Vision-Language-Action Models

arXiv:2608.30643v1 Announce Type: new Abstract: Recent vision-language-action (VLA) methods improve manipulation performance by aligning their representations with 3D scene geometry. However, these me

safetyarxiv-cs-ro

The Illusion of Replacement: Rethinking Specialized Machine Learning Models in the Foundation Model Era

arXiv:2608.28980v1 Announce Type: cross Abstract: Can the specialized architectures that machine learning has traditionally built for structured data be replaced by language-based models? This questio

Tracing distinguishability through transformer processing with stochastic LayerNorm

model-releasesarxiv-cs-lg

arXiv:2608.30720v1 Announce Type: new Abstract: Representational similarity is foundational to analyses of deep networks, yet distances between point-valued representations are not intrinsically tied

Applications

TSPFN: A Temporal Tabular Foundation Model for Physiological Time Series Classification

arXiv:2608.31013v1 Announce Type: cross Abstract: Designing models that generalize effectively in low- to medium-data regimes remains a primary challenge in medical machine learning, particularly for

applicationsarxiv-cs-cv

When to Adapt: Conditional Memory Adapters for Retention-Preserving Domain Specialization

arXiv:2608.29327v1 Announce Type: new Abstract: Large language models deployed in specialized domains must improve in-domain performance without sacrificing general capabilities. Existing parameter-ef