Search: “models”

Theory-optimal Quantization Based on Flatness

arXiv:2605.18800v1 Announce Type: cross Abstract: Post-training quantization has emerged as a widely adopted technique for compressing and accelerating the inference of Large Language Models (LLMs). T

20 May 2026

What Makes Synthetic Data Effective in Image Segmentation

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DGX agent

arXiv:2605.19289v1 Announce Type: new Abstract: Driven by rapid advances in large-scale generative models, synthetic data has emerged as a promising solution for visual understanding. While modern dif

model-releasesarxiv-cs-cv

20 May 2026

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAMDelta Integration into Upcycled MoE

arXiv:2605.18083v1 Announce Type: new Abstract: Expanding Large Language Models~(LLMs) to new languages is a costly endeavor, demanding extensive Continued Pre-Training~(CPT) and data-intensive alignm

ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery

model-releasesarxiv-cs-lg

arXiv:2605.16902v1 Announce Type: new Abstract: Scientific artifacts such as models and datasets are foundations for research. With the rapid growth of platforms like HuggingFace, researchers now have

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling

arXiv:2605.17971v1 Announce Type: cross Abstract: Despite rigorous safety alignment, Large Language Models (LLMs) remain vulnerable to jailbreak attacks. Existing black-box methods often rely on heuri

Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision

arXiv:2505.03631v4 Announce Type: replace Abstract: Video quality assessment (VQA) is essential for quantifying perceptual quality in various video processing workflows, spanning from camera capture s

Context Memorization for Efficient Long Context Generation

arXiv:2605.18226v1 Announce Type: cross Abstract: Modern large language model (LLM) applications increasingly rely on long conditioning prefixes to control model behavior at inference time. While pref

Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting

arXiv:2508.04227v2 Announce Type: replace Abstract: Vision-language models (VLMs) and the recent surge of Multimodal Large Language Models (MLLMs) have revolutionized artificial intelligence with unpr

Agents

Data-driven and distributed governance of building facilities management using decentralized autonomous organization, digital twin, and large language models

arXiv:2605.16298v1 Announce Type: cross Abstract: While traditional AI and data-driven facilities management approaches have improved building operational efficiency, they remain constrained by centra

agentsarxiv-cs-ai

Tutorials

Diffusion Attention Expert Model for Predicting and Semi-automatic Localizing STAS in Lung Cancer Histopathological Images

arXiv:2605.16444v1 Announce Type: cross Abstract: Accurate intraoperative and postoperative diagnosis of spread through air spaces (STAS) is essential for guiding surgical decisions and postoperative

tutorialsarxiv-cs-ai

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning

arXiv:2605.16776v1 Announce Type: cross Abstract: Mitigating sensitive and harmful outputs is fundamental to ensuring safe deployment of LLMs. Existing approaches typically follow two paradigms: Knowl

Estimating Item Difficulty with Large Language Models as Experts

arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive learning. However, for newly created tasks, response d

Federated Martingale Posterior Samping

model-releasesarxiv-cs-lg

arXiv:2605.18554v1 Announce Type: new Abstract: Federated Bayesian neural networks require fixing a prior on the model parameters together with a likelihood. Eliciting meaningful priors on the weight

Graph Hierarchical Recurrence for Long-Range Generalization

arXiv:2605.18387v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) and Graph Transformers (GTs) are now a fundamental paradigm for graph learning, combining the representation-learning cap

KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science

arXiv:2605.17856v1 Announce Type: new Abstract: Process-based simulation models encode decades of scientific understanding across the Earth sciences, yet the communities most exposed to climate risk a

LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift

arXiv:2605.18541v1 Announce Type: new Abstract: Modeling hyperspectral imagery (HSI) across different sensors presents a fundamental challenge due to variations in wavelength coverage, band sampling,

Lever: Speculative LLM Inference on Smartphones

arXiv:2605.16786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly needed for interactive mobile applications, but high-quality models exceed the limited DRAM available on s

researcharxiv-cs-lg

Agents

Modelling Customer Trajectories with Reinforcement Learning for Practical Retail Insights

arXiv:2605.18449v1 Announce Type: cross Abstract: Understanding customer movement within retail spaces is essential for optimizing store layouts. Real-world trajectory data can provide highly accurate

agentsarxiv-cs-ai

Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels

arXiv:2509.02351v3 Announce Type: replace-cross Abstract: Labeled data is a fundamental component in training supervised deep learning models for computer vision tasks. However, the labeling process,

PanoWorld: A Generative Spatial World Model for Consistent Whole-House Panorama Synthesis

arXiv:2605.17916v1 Announce Type: new Abstract: Generating a consistent whole-house VR tour from a floorplan and style reference requires both photorealistic panoramas and cross-view spatial coherence

researcharxiv-cs-cv

PERL: Parameter Efficient Reasoning in CLIP Latent Space

arXiv:2605.18464v1 Announce Type: new Abstract: Contrastively trained vision-language models such as CLIP provide strong zero-shot transfer by aligning images and text in a shared embedding space. How

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation

arXiv:2605.18474v1 Announce Type: cross Abstract: The widespread deployment and redistribution of large language models (LLMs) have made model provenance tracking a critical challenge. While existing

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation

arXiv:2512.19134v2 Announce Type: replace Abstract: Dynamic Retrieval-Augmented Generation adaptively determines when to retrieve during generation to mitigate hallucinations in large language models

Tutorials

Reasoning Can Be Restored by Correcting a Few Decision Tokens

arXiv:2605.16874v1 Announce Type: new Abstract: Large reasoning models (LRMs) substantially outperform their base LLM counterparts on challenging reasoning benchmarks, yet it remains poorly understood

tutorialsarxiv-cs-ai

RIE-Greedy: Regularization-Induced Exploration for Contextual Bandits

model-releasesarxiv-cs-lg

arXiv:2603.11276v2 Announce Type: replace-cross Abstract: Real-world contextual bandit problems with complex reward models are often tackled with iteratively trained models, such as boosting trees. Ho

Tutorials

RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation

arXiv:2605.17522v1 Announce Type: new Abstract: Planning and acting in 3D environments is a fundamental capability for robotic manipulation in the real world. Although prior work has explored predicti

tutorialsarxiv-cs-ro

Sometin Beta Pass Notin (SBPN): Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation

arXiv:2605.17710v1 Announce Type: new Abstract: Although modern multilingual Automatic Speech Recognition (ASR) systems support several Nigerian languages, their performance consistently lags behind h

The MixCount Dataset: Bridging the Data Gap for Open-Vocabulary Object Counting

arXiv:2605.18063v1 Announce Type: new Abstract: Object counting is a foundational vision task with over a decade of dedicated research, yet state-of-the-art models still fail systematically in the mix

Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space

arXiv:2605.17704v1 Announce Type: new Abstract: The lottery ticket hypothesis posits that dense networks contain sparse subnetworks, ``winning tickets,'' that, when rewound to their initial weights an

researcharxiv-cs-lg

UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models

arXiv:2605.17285v1 Announce Type: cross Abstract: Node representation learning, such as Graph Neural Networks (GNNs), has emerged as a pivotal method in machine learning. The demand for reliable expla

researcharxiv-cs-ai

World Model-Enabled Causal Digital Twins for Semantic Communications in Physical AI Systems

arXiv:2605.16547v1 Announce Type: new Abstract: Semantic communication has emerged as a promising paradigm for enabling goal-oriented networking. However, most existing semantic communication solution

safetyarxiv-cs-lg

Fair outputs, Biased Internals: Causal Potency and Asymmetry of Latent Bias in LLMs for High-Stakes Decisions

arXiv:2605.15217v1 Announce Type: new Abstract: Instruction-tuned language models exhibit behavioural fairness in high-stakes decisions while retaining biased associations in their internal representa

GQA-{mu}P: The maximal parameterization update for grouped query attention

arXiv:2605.15290v1 Announce Type: cross Abstract: Hyperparameter transfer across model architectures dramatically reduces the amount of compute necessary for tuning large language models (LLMs). The m

Greedy or not, here I come: Language production under vocabulary constraints in humans and resource-rational models

arXiv:2605.15365v1 Announce Type: new Abstract: Communicating using only a limited vocabulary is a common but challenging cognitive phenomenon, requiring an ideal communicator to plan carefully to opt

applicationsarxiv-cs-cl

GRLO: Towards Generalizable Reinforcement Learning in Open-Ended Environments from Zero

arXiv:2605.15464v1 Announce Type: cross Abstract: Post-training has become a crucial step for unlocking the capabilities of large language models, with reinforcement learning (RL) emerging as a critic

Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification

arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence - reusing the same block repeatedly across layer

MAgSeg: Segmentation of Agricultural Landscapes in High-Resolution Satellite Imagery using Multimodal Large Language Models

arXiv:2605.16179v1 Announce Type: new Abstract: Agricultural landscape segmentation in the Global South is challenging as it is characterized by fragmented plots, high intra-class variance, and a scar

safetyarxiv-cs-cv

Agents

NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol

arXiv:2605.15227v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) have attracted increasing attention as a means of accelerating scientific discovery; however, developing SDL software r

agentsarxiv-cs-ai

Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance

arXiv:2508.08431v3 Announce Type: replace-cross Abstract: Spectral variability significantly impacts the accuracy and convergence of hyperspectral unmixing algorithms. Many methods address complex spe

applicationsarxiv-cs-cv

Second-Order Multi-Level Variance Correction for Modality Competition in Multimodal Models

arXiv:2605.16165v1 Announce Type: cross Abstract: Autoregressive next-token training offers a unified formulation for image generation and text understanding, but it also creates strong modality compe

STS: Efficient Sparse Attention with Speculative Token Sparsity

arXiv:2605.15508v1 Announce Type: cross Abstract: The quadratic complexity of attention imposes severe memory and computational bottlenecks on Large Language Model (LLM) inference. This challenge is p

Towards Trustworthy and Explainable AI for Perception Models: From Concept to Prototype Vehicle Deployment

arXiv:2605.16087v1 Announce Type: cross Abstract: Deep Neural Networks have become the dominant solution for Autonomous Driving perception, but their opacity conflicts with emerging Trustworthy AI gui

ClickRemoval: An Interactive Open-Source Tool for Object Removal in Diffusion Models

arXiv:2605.14461v1 Announce Type: new Abstract: Existing object removal tools often rely on manual masks or text prompts, making precise removal difficult for non-expert users in complex scenes and of

researcharxiv-cs-cv

Correctness-Aware Repository Filtering Under Maximum Effective Context Window Constraints

arXiv:2605.14362v1 Announce Type: cross Abstract: Context window efficiency is a practical constraint in large language model (LLM)-based developer tools. Paulsen [12] shows that all tested models deg

From Street View to Visual Network: Mapping the Visibility of Urban Landmarks with Vision-Language Models

arXiv:2505.11809v3 Announce Type: replace Abstract: Visibility analysis in urban planning has traditionally relied on line-of-sight (LoS) simulations, which capture geometric occlusion. However, these

applicationsarxiv-cs-cv

PacTure: Efficient PBR Texture Generation on Packed Views with Visual Autoregressive Models

arXiv:2505.22394v2 Announce Type: replace Abstract: We present PacTure, a novel framework for generating physically-based rendering (PBR) material textures for an untextured 3D mesh from a text descri

researcharxiv-cs-cv

TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA

arXiv:2510.04682v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely applied in real world scenarios, yet fine-tuning them comes with significant computational and storage

A Hybrid Tucker-LSTM Tensor Network Model for SOC Prediction in Electric Vehicles