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arXiv:2605.27750v1 Announce Type: cross Abstract: Recent work has shown that Vision-Language Models (VLMs) used for optical character recognition (OCR) can generate plausible but visually unsupported

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Model Releases

SIGMA: Bridging Structural and Distributional Gaps for Vision Foundation Model Adaptation

DGX agent

arXiv:2605.27893v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) have demonstrated impressive representational capabilities. However, adapting them to downstream tasks via full fine-tun

model-releasesarxiv-cs-cv

28 May 2026

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations

arXiv:2605.28149v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) extract interpretable features from Large Language Models, but standard variants enforce non-negativity, forcing separate lat

Soro: A Lightweight Foundation Model and Chatbot for Tajik

arXiv:2605.27379v1 Announce Type: new Abstract: We present Soro, a family of Tajik-specialized conversational large language models (LLMs) designed for real-world deployment under tight compute and co

Stop Rewarding Hallucinated Steps: Faithfulness-Aware Step-Level Reinforcement Learning for Small Reasoning Models

arXiv:2602.05897v2 Announce Type: replace Abstract: As large language models become smaller and more efficient, small reasoning models (SRMs) are crucial for enabling chain-of-thought (CoT) reasoning

researcharxiv-cs-cl

Tutorials

The Principles of Diffusion Models

arXiv:2510.21890v2 Announce Type: replace-cross Abstract: This book presents the core principles that have guided the development of diffusion models, tracing their origins and showing how diverse for

tutorialsarxiv-cs-ai

Tools

This tracks. 30 trillion tokens a day on our end, and open model share keeps climbing. Our partners @FactoryAI are seeing what we're seeing.

This tracks. 30 trillion tokens a day on our end, and open model share keeps climbing. Our partners @FactoryAI are seeing what we're seeing. Narrative violation: Open model use in Factory has more tha

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Applications

Toward Semantic-Agnostic and Shape-Aware Vision-Language Segmentation Models

arXiv:2605.28348v1 Announce Type: new Abstract: Vision-language segmentation models have recently achieved strong performance by leveraging high-level semantic object categories expressed in natural l

applicationsarxiv-cs-cv

AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesis

arXiv:2605.25763v2 Announce Type: replace Abstract: Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models

safetyarxiv-cs-cv

AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian

model-releasesarxiv-cs-cl

arXiv:2605.26954v1 Announce Type: new Abstract: Safety evaluation of Large Language Models (LLMs) has largely focused on high-resource languages, leaving low-resource languages critically underserved.

Aligning Few-Step Generative Models by Amortizing Sample-based Variational Inference

arXiv:2605.26552v1 Announce Type: cross Abstract: Aligning a few-step generative model is challenging, since existing alignment frameworks typically rely on restrictive assumptions: a tractable likeli

safetyarxiv-cs-ai

Are Video Models Zero-Shot Learners and Reasoners in Education? EduVideoBench, A Knowledge-Skills-Attitude Benchmark for Educational Video Generation

model-releasesarxiv-cs-cl

arXiv:2605.26918v1 Announce Type: new Abstract: Video generation models (VGMs) are rapidly entering classrooms, yet existing benchmarks evaluate only perceptual quality, intrinsic faithfulness, generi

BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback

model-releasesarxiv-cs-cl

arXiv:2509.21106v2 Announce Type: replace Abstract: Search-augmented large language models (LLMs) have advanced information-seeking tasks by integrating retrieval into generation, reducing users' cogn

Agents

Can Retrieval Heads See Images? Multimodal Retrieval Heads in Long-Context Vision-Language Models

arXiv:2605.27243v1 Announce Type: new Abstract: Large vision-language models increasingly rely on long-context modeling to reason over documents, hour-level videos, and long-horizon agent trajectories

agentsarxiv-cs-cv

EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning

arXiv:2601.03471v3 Announce Type: replace-cross Abstract: Reliable epidemiological reasoning requires synthesizing study evidence to infer disease burden, transmission dynamics, and intervention effec

Intelligent Detection and Mitigation of Carpet-Bombing DDoS Attacks in SDN Using Retrieval-Augmented Generation and Large Language Models

arXiv:2605.26307v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) provides flexible and programmable network management; however, its centralized control architecture remains highly

It's Not the Capability: Harness Sensitivity Is Non-Monotone Across LLM Agent Tiers

arXiv:2605.26731v1 Announce Type: new Abstract: A prevalent assumption in LLM agent deployment holds that more structured harnesses universally improve reliability, and that higher-capability models n

Krea is now built in to Hermes Agent as an image generation API provider, allowing your agent to use Krea 2: a new foundation model trained …

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Krea is now built in to Hermes Agent as an image generation API provider, allowing your agent to use Krea 2: a new foundation model trained from scratch to balance aesthetic quality and fine control,

Tutorials

Leveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking

arXiv:2605.26933v1 Announce Type: new Abstract: Unsupervised visual object tracking is a challenging task that requires following arbitrary targets in videos without training on ground-truth annotatio

tutorialsarxiv-cs-cv

Applications

Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study

arXiv:2502.06567v2 Announce Type: replace-cross Abstract: Quantizing machine learning models has demonstrated its effectiveness in lowering memory and inference costs while maintaining performance lev

applicationsarxiv-cs-lg

MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation

arXiv:2602.09878v2 Announce Type: replace Abstract: World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely im

safetyarxiv-cs-cv

Omanic: Towards Step-wise Evaluation of Multi-hop Reasoning in Large Language Models

arXiv:2603.16654v2 Announce Type: replace-cross Abstract: Evaluating the reasoning abilities of large language models (LLMs) solely from final answers can obscure failures in intermediate steps, espec

Agents

Real-Time Progress Prediction in Reasoning Language Models

arXiv:2506.23274v4 Announce Type: replace-cross Abstract: Recent reasoning language models, particularly those that employ long latent chains of thought, achieve strong performance on complex agentic

agentsarxiv-cs-ai

The Stability of Singular Distribution: A Spectral Perspective on the Two-Phase Dynamics of Language Model Pre-training

arXiv:2605.26489v1 Announce Type: new Abstract: Large language model pre-training typically exhibits a two-phase trajectory: a fast initial loss drop followed by a prolonged slow improvement. We ident

VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models

arXiv:2510.17759v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) extend large language models with visual reasoning, but their multimodal design also introduces new, underexplor

safetyarxiv-cs-cl

We've created the world's fastest PDF parser ⚡️ And it's more accurate than any other open-source, model-free PDF parser out there (pymupdf,…

model-releasesjerry-liu--x

We've created the world's fastest PDF parser ⚡️ And it's more accurate than any other open-source, model-free PDF parser out there (pymupdf, pypdf, markitdown, pdftotext, opendataloader, pymupdf4llm)

Authority Inversion in LLM-Mediated Ubiquitous Systems: When Models Trust Users Over Sensors

arXiv:2605.23938v1 Announce Type: new Abstract: Large language models (LLMs) increasingly fuse heterogeneous inputs in ubiquitous systems. Yet, how LLMs implicitly allocate authority when sensor measu

safetyarxiv-cs-ai

Agents

Back to Parsimonious Latents: Learning Task-Centric World Models from Visual Foundations

arXiv:2605.25620v1 Announce Type: new Abstract: World models enable agents to predict future dynamics conditioned on actions, making the choice of latent representation central to planning and control

agentsarxiv-cs-ai

BandVQ: Band-Wise Vector-Quantized EEG Foundation Model

arXiv:2605.24921v1 Announce Type: new Abstract: A central challenge in electroencephalography (EEG) foundation modeling is learning transferable representations across recordings with diverse tasks, m

researcharxiv-cs-lg

Bayesian Distributional Models of Executive Functioning

arXiv:2510.00387v3 Announce Type: replace Abstract: This study uses controlled simulations with known ground-truth parameters to evaluate how Distributional Latent Variable Models (DLVM) and Bayesian

Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models

arXiv:2605.24053v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly governed by probabilistic frameworks in which the sum of outcome probabilities is constrained to unity. T

researcharxiv-cs-ai

Local Ai

Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models

arXiv:2605.24799v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a wide range of vision language tasks. However, when applied to

local-aiarxiv-cs-ai

Fine-Tuning Language Models to Know What They Know

arXiv:2602.02605v2 Announce Type: replace-cross Abstract: Evaluating true metacognition in Large Language Models (LLMs) is difficult due to biases and heuristics. This paper presents a framework to me

Fusion Embedding for Pose-Guided Person Image Synthesis with Diffusion Model

arXiv:2412.07333v2 Announce Type: replace-cross Abstract: Pose-Guided Person Image Synthesis (PGPIS) aims to generate human images in specified poses while preserving the identity and appearance of a

Goal-driven Bayesian Optimal Experimental Design for Robust Decision-Making Under Model Uncertainty

arXiv:2605.26093v1 Announce Type: new Abstract: Bayesian optimal experimental design (BOED) selects experiments to maximize information gain about model parameters. However, in decision-critical setti

Hylos: Operability Contracts for Model-Native Spatial Intelligence

arXiv:2605.24728v1 Announce Type: new Abstract: Foundation models can increasingly describe, reconstruct, and generate 3D objects, assemblies, scenes, and environments, but visually plausible spatial

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models

arXiv:2605.25342v1 Announce Type: new Abstract: Aligning large language models (LLMs) with diverse and multifaceted user preferences is a fundamental challenge in personalized AI systems. Existing mul

safetyarxiv-cs-cl

Merge-Bench: Resolve Merge Conflicts with Large Language Models

arXiv:2605.25890v1 Announce Type: new Abstract: This paper applies machine learning to the difficult and important task of version control merging. (1) We constructed a dataset, Merge-Bench, of 7938 r

MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing

arXiv:2605.24973v1 Announce Type: cross Abstract: VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within

researcharxiv-cs-ai

On the Limits of Model Merging for Multilinguality in Pre-Training

arXiv:2605.25846v1 Announce Type: new Abstract: Endowing models with consistent multilingual performance can be achieved by mixing pre-training data, or post-training approaches such as language-speci

researcharxiv-cs-cl

PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization

arXiv:2605.06505v2 Announce Type: replace-cross Abstract: We introduce PACZero, a family of PAC-private zeroth-order mechanisms for fine-tuning large language models that delivers usable utility at I(

PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models

arXiv:2512.20063v3 Announce Type: replace Abstract: We introduce exttt{PairFlow}, a lightweight preprocessing step for training Discrete Flow Models (DFMs) to achieve few-step sampling without requiri

researcharxiv-cs-lg

Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis

arXiv:2605.25063v1 Announce Type: new Abstract: Reinforcement learning offers a promising approach for scan-order optimisation in laser additive manufacturing, where sequential scan decisions critical

Industry

🙏 Thank you all for the incredible love and support! Our latest Tencent Hunyuan translation models are on fire on Hugging Face: 🥰Hy-MT2-1.…

🙏 Thank you all for the incredible love and support! Our latest Tencent Hunyuan translation models are on fire on Hugging Face: 🥰Hy-MT2-1.8B ranks #1 🥰Hy-MT2-30B-A3B ranks #4 on the open-source model

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Industry

Today we’re releasing 1-bit and Ternary Bonsai Image 4B. A new family of image-generation models designed to run high-quality diffusion infe…

Hugging Face has released 1-bit and Ternary Bonsai Image 4B, a new family of lightweight image-generation models optimized for efficient diffusion inference. These models are designed to deliver high-

industryclem-delangue--x

Local Ai

Try out the models Below 👇 Nanobana Pro: https://links.comfy.org/4f5k5lN GPT Image 2: https://links.comfy.org/4dAi4Nq

ComfyUI promoted two AI models available for testing: Nanobana Pro and GPT Image 2, providing direct links for users to access and try out these models through their platform. This appears to be a soc

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A look at DeepSeek's model optimization to reduce HBM use, potentially enabling domestic memory, ASIC, and CPU makers to create a Chinese AI hardware ecosystem (@bookwormengr)

@bookwormengr: A look at DeepSeek's model optimization to reduce HBM use, potentially enabling domestic memory, ASIC, and CPU makers to create a Chinese AI hardware ecosystem — Have you ever wondered,

model-releasestechmeme

25 May 2026

Benchmarking Gaslighting Attacks Against Speech Large Language Models