Search: “pretraining”

Blind Men and the Elephant: Probing the Epistemic Myopia of LLMs under Long-Tail Divergent Knowledge

arXiv:2608.28478v1 Announce Type: new Abstract: Factual question answering (QA) typically assumes a single canonical answer, obscuring whether large language models (LLMs) retain divergent accounts of

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Research

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery

DGX agent

arXiv:2506.04970v2 Announce Type: replace Abstract: Information on trees at the individual level is crucial for monitoring forest ecosystems and planning forest management. Current monitoring methods

researcharxiv-cs-cv

31 Aug 2026

Class Incremental Continual Learning with Self-Organizing Maps and Synthetic Replay

arXiv:2508.21240v2 Announce Type: replace Abstract: This work introduces a novel generative continual learning framework based on self-organizing maps (SOMs), a brain-inspired natural computing model,

researcharxiv-cs-lg

DeicticVLA: Unifying Instruction Modes Based on Language and Deictic Gestures in a Single VLA

arXiv:2608.28108v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) allow users to specify manipulation tasks in natural language, but distinguishing a target or placement goal amon

safetyarxiv-cs-cv

Do Medical Vision Models Reason About Anatomy? Probing the Spatial Inductive Biases of Learned Visual Representations

arXiv:2608.28092v1 Announce Type: cross Abstract: Interpreting a CT scan means comparing structures on either side, judging how far apart organs sit, and knowing where each one belongs. Medical vision

Empowering Local Agriculture: A Deep Learning-Powered Web System for Identifying Bangladeshi Mango Varieties

arXiv:2608.28161v1 Announce Type: new Abstract: Mango variety identification in Bangladesh is challenging because closely related cultivars can have similar visual characteristics and images are often

local-aiarxiv-cs-cv

How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models

arXiv:2608.28404v1 Announce Type: new Abstract: Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cann

Initialization Is Critical: Advancing Federated Short-Term Load Forecasting under Load Heterogeneity via Model Initialization

arXiv:2608.27791v1 Announce Type: new Abstract: Short-term load forecasting (STLF) provides essential information for numerous applications in modern power systems. However, accurate STLF often relies

local-aiarxiv-cs-lg

Learning a Single Token to Replace Long System Prompts in LLMs

arXiv:2511.23271v2 Announce Type: replace Abstract: Long system prompts are widely used to steer Large Language Models (LLMs), but repeatedly processing them at inference time is inefficient and consu

Learning the Target Priors Before Image Translation: A Decoupled Training Paradigm for Cross-Modal Image Translation in Remote Sensing

arXiv:2608.28517v1 Announce Type: new Abstract: Cross-modal image translation in remote sensing must preserve source-observed content while matching the target-domain distribution. Existing methods jo

Leveraging a Foundation Model for the EEG-Based Diagnosis of Alzheimer's Disease

arXiv:2608.27719v1 Announce Type: new Abstract: Biological heterogeneity in Alzheimer's Disease (AD) poses a critical diagnostic challenge, particularly for traditional linear methods that fail to cap

safetyarxiv-cs-lg

Long Story Short: Story-level Video Understanding from 20K Short Films

arXiv:2406.10221v3 Announce Type: replace-cross Abstract: Recent developments in vision-language models have significantly advanced video understanding. Existing datasets and tasks, however, have nota

SUFLECA: Scaling Up Feature Learning for CAD-to-image Alignment

arXiv:2607.15058v2 Announce Type: replace Abstract: CAD-to-image alignment aims to estimate an object's 9D pose (rotation, translation, and anisotropic scale) from a single RGB image, with application

Token-Budget Distillation: Transferring Full-Token Semantics to Compressed Video Vision-Language Models

arXiv:2608.28138v1 Announce Type: new Abstract: Adapting video vision-language models (VLMs) is computationally expensive because video inputs produce a large number of visual tokens, making both fine

Training-Free Temporal Abstraction for General Video Understanding

arXiv:2608.27929v1 Announce Type: new Abstract: Videos are expensive to analyze frame by frame, yet many video understanding tasks depend on knowing where relevant moments occur. A system may need to

UniLipi: A Unified Multi-Script OCR for Historical Indic Manuscripts

arXiv:2608.28195v1 Announce Type: new Abstract: Optical character recognition (OCR) for handwritten Indic manuscripts is essential for large-scale digitization and computational access to manuscript h

A Framework for Low-Effort Training Data Generation for Urban Semantic Segmentation

arXiv:2510.11567v2 Announce Type: replace Abstract: Synthetic datasets are widely used for training urban scene recognition models, but even highly realistic renderings show a noticeable gap to real i

After Meta avocado we get watermelon, due in November

model-releasesr-localllama

Quote: ... developing a new A.I. model intended to be as powerful as Anthropic’s cutting-edge models. ... In July, while developing Watermelon, Meta paused and later resumed a stage of A.I. developmen

Decoupling Planning and Control for Instructable Agents

arXiv:2608.26788v1 Announce Type: new Abstract: Recent work shows that pre-trained, instruction-tuned vision-language models (VLMs) perform well at mapping from instructions and observations to high-l

safetyarxiv-cs-ai

Diffusion Policies for Short-Horizon Planning in Robot Crowd Navigation

model-releasesarxiv-cs-lg

arXiv:2608.27158v1 Announce Type: new Abstract: Robot crowd navigation requires safe and efficient decision-making under dense, dynamic, and multimodal human--robot interactions. Existing reinforcemen

EditaLive! Unified Character Video Editing for Live Streaming

arXiv:2608.27123v1 Announce Type: new Abstract: Conventional video editing primarily focuses on scene-level content, whereas live streaming places greater emphasis on the human subject. However, direc

Applications

HALO: A Heterogeneity-Aware Language-Aligned IMU Foundation Model for Open-Set Human Activity Recognition

arXiv:2608.27233v1 Announce Type: new Abstract: Human Activity Recognition (HAR) using inertial measurement units (IMUs) enables a wide range of applications, yet the field still lacks a unified model

applicationsarxiv-cs-lg

Applications

Hyperspectral Diffusion Equivariant Imaging (HyDiff-EI): A Self-supervised Framework for Hyperspectral Image Inpainting

arXiv:2608.26812v1 Announce Type: new Abstract: A novel Hyperspectral diffusion Equivariant Imaging (HyDiff-EI) framework for solving the hyperspectral image (HSI) inpainting problem has been presente

applicationsarxiv-cs-cv

LiveVVT: High-Fidelity Video Virtual Try-On in Real Time

arXiv:2608.26714v1 Announce Type: cross Abstract: Diffusion-based Video Virtual Try-On (VVT) achieves high visual fidelity through bidirectional spatio-temporal modeling, but complete-clip dependence

local-aiarxiv-cs-ai

LLaVAFlow: Preserving Latent Alignment Flow for Parameter-Efficient Multimodal Fine-Tuning

arXiv:2608.26820v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) exhibit strong generalization, visual instruction tuning for downstream tasks inevitably causes catastrop

Modular Expert Merging for Biomedical Retrieval

arXiv:2602.04731v2 Announce Type: replace Abstract: Adapting general-purpose LLMs into domain-specialized dense retrievers typically requires large-scale training on mixed-domain data. We show that me

MoganColBERT-TR: A Late-Interaction Multi-Vector Retrieval Model for Turkish

arXiv:2608.26344v1 Announce Type: new Abstract: We previously reported a ModernBERT encoder trained from scratch for Turkish (MoganBERT-TR) and a single-vector embedding model built on top of it (Moga

Parameter Efficient Continual Learning for Sparse Event-Based Transformers

arXiv:2608.26720v1 Announce Type: new Abstract: Robotic and edge intelligence systems operate in dynamic environments where data arrives continuously, requiring models to adapt while preserving previo

Predicting Consequences and Reinforcing Navigation Policies with Latent World Models

arXiv:2608.26190v1 Announce Type: new Abstract: World models enable agents to reason about future outcomes and learn policies from their knowledge of state transition, but existing approaches primaril

safetyarxiv-cs-ai

SimCast-S2S: An Efficient Generative Model for Subseasonal Precipitation Forecasting via Transfer Learning from Climate Simulations

arXiv:2608.26594v1 Announce Type: new Abstract: Subseasonal-to-seasonal (S2S) precipitation forecasting has substantial financial and societal impact, yet remains challenging because of weak predictiv

safetyarxiv-cs-lg

SpatialCrafter: Single Image World Modeling with Generative 3D Proxies

arXiv:2608.27073v1 Announce Type: new Abstract: Explorable image-to-scene generation is essential for applications in gaming, robotics, and virtual reality. Existing methods based on video diffusion m

SSMB: Self-Supervised Local Feature Detection under Motion Blur

arXiv:2608.27181v1 Announce Type: new Abstract: Keypoint detection under motion blur remains a significant challenge, as blur distorts local image structure and degrades the repeatability of feature l

safetyarxiv-cs-cv

Stack Trace-Based Crash Deduplication with Transformer Adaptation

arXiv:2508.19449v2 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer wo

safetyarxiv-cs-lg

Structured Evidence Routing for Incident Risk Prediction from Multimodal Longitudinal EHRs

arXiv:2608.26191v1 Announce Type: new Abstract: Incident risk prediction from longitudinal electronic health records (EHRs) is challenging because relevant signals are multimodal, weak in isolation, a

researcharxiv-cs-ai

Surgical Alignment in Knowledge Graph Training for Clinical Diagnosis with Large Language Models

arXiv:2608.26587v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) offer structured medical knowledge that can ground large language model (LLM) reasoning in clinical diagnosis applicat

local-aiarxiv-cs-cl

Agents

SWE-Prime: Fewer Trajectories, Better Performance

arXiv:2608.27449v1 Announce Type: cross Abstract: To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory d

agentsarxiv-cs-ai

TempJail: Temporal Jailbreak Attacks against Image-to-Video Generation Models

arXiv:2608.26971v1 Announce Type: new Abstract: In recent years, image-to-video (I2V) generation models have made remarkable progress in subject consistency and temporal coherence, enabling high quali

Tutorials

The BS-meter: Detecting Politics and Labour through ChatGPT's Language

arXiv:2411.15129v3 Announce Type: replace-cross Abstract: What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, w

tutorialsarxiv-cs-ai

Understanding Evolution Strategies for LLM Reasoning: Broader Reasoning Coverage than GRPO

model-releasesarxiv-cs-lg

arXiv:2608.27351v1 Announce Type: new Abstract: Evolution Strategies (ES) have recently emerged as a memory-efficient post-training paradigm for LLM reasoning. However, the optimization behavior of ES

Using VLM Reasoning to Constrain Task and Motion Planning

arXiv:2510.25548v3 Announce Type: replace Abstract: In task and motion planning, high-level task planning is done over an abstraction of the world to enable efficient search in long-horizon robotics p

researcharxiv-cs-ro

WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression

arXiv:2608.26239v1 Announce Type: new Abstract: Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, plannin

safetyarxiv-cs-ro

When Is Noise Response Universal? Tokenization as the Hidden Variable in Language Models

arXiv:2608.26319v1 Announce Type: new Abstract: The performance of textual neural models often degrades when their inputs are corrupted by noise such as typos, OCR errors, or dropped words. We study t

researcharxiv-cs-cl

4DStreamCtrl: Interactive Video Generation with Online 4D Control

arXiv:2608.25479v1 Announce Type: new Abstract: Generative video models now synthesize footage nearly indistinguishable from reality. Their promise as interactive tools hinges on fine-grained control

A General-Purpose Molecular Foundation Model Transfers Across Diverse Olfactory Tasks

model-releasesarxiv-cs-lg

arXiv:2608.25893v1 Announce Type: new Abstract: Foundation models have transformed molecular property prediction, yet it remains unclear whether a molecular foundation model, fine-tuned on a single ca

A Storage-Retrieval Gap in Parametric Knowledge Graph Memory

arXiv:2608.25489v1 Announce Type: cross Abstract: Graph retrieval-augmented generation places retrieved subgraphs into the model's context window at query time, paying a recurring token cost and expos

Hardware

BanglaMamba: Exploring State Space Models for Bangla Fake News Detection

arXiv:2608.25190v1 Announce Type: new Abstract: Fake news detection has become an important Natural Language Processing (NLP) task due to the rapid spread of misinformation through online news platfor

hardwarearxiv-cs-cl

Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?

arXiv:2608.25148v1 Announce Type: new Abstract: Frozen hematology foundation-model (FM) embeddings reach near-saturated in-domain white-blood-cell (WBC) accuracy, but clinical deployment demands relia

DeCO: Discriminative Evidence Composition for Fine-Grained Dataset Distillation

arXiv:2608.25480v1 Announce Type: new Abstract: Dataset distillation compresses a large training set into a compact synthetic set while preserving its downstream utility. However, existing methods pri