Search: “models”

Wasserstein bounds for denoising diffusion probabilistic models via the Follmer process

arXiv:2605.18069v1 Announce Type: cross Abstract: This paper studies sampling error bounds for denoising diffusion probabilistic models (DDPMs) in the 2-Wasserstein distance. Our contributions are thr

19 May 2026

Human

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Research

What Matters for Grocery Product Retrieval with Open Source Vision Language Models

DGX agent

arXiv:2605.18029v1 Announce Type: new Abstract: Multimodal product retrieval (MPR) underpins checkout-free retail and automated inventory systems, yet it demands fine-grained SKU discrimination that s

researcharxiv-cs-cv

19 May 2026

When Dynamics Shift, Robust Task Inference Wins: Offline Imitation Learning with Behavior Foundation Models Revisited

arXiv:2605.17017v1 Announce Type: cross Abstract: Behavior Foundation Models (BFMs) enable scalable imitation learning (IL) by pretraining task-agnostic representations that can be rapidly adapted to

safetyarxiv-cs-ai

19 May 2026

3 new models from @xai's Grok creative stack are live on OpenRouter: • Grok Imagine Image Quality: photoreal image generation and editing • …

3 new models from @xai's Grok creative stack are live on OpenRouter: • Grok Imagine Image Quality: photoreal image generation and editing • Grok Imagine Video: short clips from text, image, or referen

industryelon-musk--x

Attribute-Grounded Selective Reasoning for Artwork Emotion Understanding with Multimodal Large Language Models

arXiv:2605.15755v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can produce fluent artwork emotion explanations, but they often suffer from attribute flooding: they enumerate

agentsarxiv-cs-cv

BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models

arXiv:2602.04163v2 Announce Type: replace Abstract: Large language model inference is often bounded by memory footprint and bandwidth in resource-constrained deployments, making quantization fundament

DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation

arXiv:2605.16113v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on kno

safetyarxiv-cs-ai

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi

agentsarxiv-cs-lg

Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models?

arXiv:2605.15855v1 Announce Type: new Abstract: Despite strong image-generation performance, diffusion models' reconstruction objectives limit alignment with human preferences. RL enables such alignme

safetyarxiv-cs-cv

Embedding-perturbed Exploration Preference Optimization for Flow Models

arXiv:2605.15803v1 Announce Type: new Abstract: Recent advancements have established Reinforcement Learning (RL) as a pivotal paradigm for aligning generative models with human intent. However, group-

safetyarxiv-cs-cv

I believe on-prem and local AI - based on @huggingface open-source models - will be an important answer to the GPU shortages this year (beca…

I believe on-prem and local AI - based on @huggingface open-source models - will be an important answer to the GPU shortages this year (because they are cheaper, faster, safer than cloud APIs)! Great

local-aiclem-delangue--x

Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds

arXiv:2605.15822v1 Announce Type: new Abstract: Score-based generative models are trained in high-dimensional ambient spaces, yet many data distributions are supported on low-dimensional nonlinear str

Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution

arXiv:2605.15301v1 Announce Type: new Abstract: Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks att

agentsarxiv-cs-ai

Developers say Chinese AI labs lead US rivals in video generation, as ByteDance and Kuaishou train models on vast short-form video libraries from their own apps (Eleanor Olcott/Financial Times)

Eleanor Olcott / Financial Times: Developers say Chinese AI labs lead US rivals in video generation, as ByteDance and Kuaishou train models on vast short-form video libraries from their own apps — Chi

industrytechmeme

17 May 2026

Publicis agrees to acquire LiveRamp, which allows companies to share and build new data sets and models that can power agentic frameworks, for $2.2B in cash (Alison Weissbrot/Adweek)

Alison Weissbrot / Adweek: Publicis agrees to acquire LiveRamp, which allows companies to share and build new data sets and models that can power agentic frameworks, for 2.2B in cash — Publicis Groupe

agentstechmeme

17 May 2026

Hardware

A profile of AI video generation startup Runway, which is training models directly on observational data, is now valued at 5.3B, and added 40M in ARR in Q2 (Rebecca Bellan/TechCrunch)

Rebecca Bellan / TechCrunch: A profile of AI video generation startup Runway, which is training models directly on observational data, is now valued at 5.3B, and added 40M in ARR in Q2 — Every major A

hardwaretechmeme

BREAKING: The results are in for Slides Arena... @AnthropicAI and @Zai_org models continue to lead the way in soft-verifiable domains 1st: O…

BREAKING: The results are in for Slides Arena... @AnthropicAI and @Zai_org models continue to lead the way in soft-verifiable domains 1st: Opus 4.7 by @AnthropicAI 2nd: Opus 4.7 (Thinking) by @Anthrop

agentszhipu-ai--x

Exploring Geographic Relative Space in Large Language Models through Activation Patching

arXiv:2605.14535v1 Announce Type: new Abstract: The increased use of Large Language Models (LLMs) in geography raises substantial questions about the safety of integrating these tools across a wide ra

safetyarxiv-cs-lg

Graph of States: Solving Abductive Tasks with Large Language Models

arXiv:2603.21250v2 Announce Type: replace Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former

agentsarxiv-cs-ai

Image Restoration via Diffusion Models with Dynamic Resolution

arXiv:2605.14267v1 Announce Type: cross Abstract: Diffusion models (DMs) have exhibited remarkable efficacy in various image restoration tasks. However, existing approaches typically operate within th

MultiMat: Multimodal Program Synthesis for Procedural Materials using Large Multimodal Models

arXiv:2509.22151v3 Announce Type: replace Abstract: Material node graphs are programs that generate the 2D channels of procedural materials, including geometry such as roughness and displacement maps,

applicationsarxiv-cs-cv

TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models

arXiv:2602.04657v3 Announce Type: replace Abstract: Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most ex

local-aiarxiv-cs-cv

Are scaling laws finally working for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights in Apache 2.0 on @huggin…

Are scaling laws finally working for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights in Apache 2.0 on @huggingface. It's a family of open-weights TSFMs from 4M to 2.5B p

industryclem-delangue--x

Assessing the Creativity of Large Language Models: Testing, Limits, and New Frontiers

arXiv:2605.13450v1 Announce Type: new Abstract: Measuring the creativity of large language models (LLMs) is essential for designing methods that can improve creativity and for enhancing our scientific

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements t…

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements to caching for faster inference overall. Turn on Developer Mod

local-ailm-studio--x

CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large VIsion-Language Models

arXiv:2605.13178v1 Announce Type: cross Abstract: In large vision-language models, visual tokens typically constitute the majority of input tokens, leading to substantial computational overhead. To ad

DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models

arXiv:2605.12702v1 Announce Type: new Abstract: General-purpose safety benchmarks for large language models do not adequately evaluate disability-related harms. We introduce DisaBench: a taxonomy of t

safetyarxiv-cs-ai

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models

arXiv:2605.13156v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in bridging visual perception and natural language understanding, enabling a wid

researcharxiv-cs-cv

GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models

arXiv:2605.13375v1 Announce Type: cross Abstract: In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware

local-aiarxiv-cs-ai

Learning to See What You Need: Gaze Attention for Multimodal Large Language Models

arXiv:2605.13080v1 Announce Type: new Abstract: When humans describe a visual scene, they do not process the entire image uniformly; instead, they selectively fixate on regions relevant to their inten

local-aiarxiv-cs-cv

MILM: Large Language Models for Multimodal Irregular Time Series with Informative Sampling

arXiv:2605.13711v1 Announce Type: new Abstract: Multimodal irregular time series (MITS) consist of asynchronous and irregularly sampled observations from heterogeneous numerical and textual channels.

applicationsarxiv-cs-lg

Tutorials

Most teams can pick frontier models. Fewer can run them at production scale without hitting constraints in latency, throughput, and governan…

Most teams can pick frontier models. Fewer can run them at production scale without hitting constraints in latency, throughput, and governance. Fireworks AI on @Azure AI Foundry provides the inference

tutorialsfireworks-ai--x

Multitask Multimodal Fusion with Tabular Foundation Models for Peak and Durability Prediction of Pertussis Booster Response

arXiv:2605.12852v1 Announce Type: new Abstract: Pertussis booster vaccination produces immune responses that vary widely across individuals in both peak magnitude and long-term durability. These two p

On the Limits of Latent Reuse in Diffusion Models

arXiv:2605.13448v1 Announce Type: cross Abstract: Diffusion models are often trained in low-dimensional latent spaces, which are then reused for related but shifted datasets. In this work, we study wh

Pretraining Language Models with Subword Regularization: An Empirical Study of BPE Dropout in Low-Resource NLP

arXiv:2605.13436v1 Announce Type: cross Abstract: Subword regularization methods such as BPE dropout are typically applied only during fine-tuning, while pretraining is usually done with deterministic

safetyarxiv-cs-lg

SceneGraphVLM: Dynamic Scene Graph Generation from Video with Vision-Language Models

arXiv:2605.13667v1 Announce Type: new Abstract: Scene graph generation provides a compact structured representation for visual perception, but accurate and fast graph prediction from images and videos

researcharxiv-cs-cv

TimelineReasoner: Advancing Timeline Summarization with Large Reasoning Models

arXiv:2605.12518v1 Announce Type: cross Abstract: The proliferation of online news poses a challenge to extracting structured timelines from unstructured content. While recent studies have shown that

Toto 2.0 is here: Datadog AI's 5 open-weights forecasting models (4m-2.5B params) finally make scaling work for time series forecasting! #1 …

Toto 2.0 is here: Datadog AI's 5 open-weights forecasting models (4m-2.5B params) finally make scaling work for time series forecasting! #1 on BOOM, GIFT-Eval, and TIME. Weights/code Apache 2.0. 🔗 Rea

industryclem-delangue--x

Tools

Try Rime Mist v3 in voice finder directly: https://findtherightvoice.com/rime-labs--rime-mist-v3 Model pages: http://www.together.ai/models/…

Try Rime Mist v3 in voice finder directly: https://findtherightvoice.com/rime-labs--rime-mist-v3 Model pages: http://www.together.ai/models/rime-mist-v3 http://www.together.ai/models/rime-mist-v3-omni

toolstogether-ai--x

What to Ignore, What to React: Visually Robust RL Fine-Tuning of VLA Models

arXiv:2605.13105v1 Announce Type: new Abstract: Reinforcement learning (RL) fine-tuning has shown promise for Vision-Language-Action (VLA) models in robotic manipulation, but deployment-time visual sh

safetyarxiv-cs-ro

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

arXiv:2602.13215v2 Announce Type: replace Abstract: Recurrent-attention hybrids aim to combine the efficiency of recurrence with the expressivity of attention, but existing approaches typically apply

You can now power your Hermes Agent, if using OpenAI models, with codex as the runtime for the core tools that it offers, with the flip of a…

Nous Research announced that Hermes Agents powered by OpenAI models can now use Codex as the runtime for executing core tools, enabling improved tool execution capabilities with a simple configuration

agentsnous-research--x

A Survey of On-Policy Distillation for Large Language Models

arXiv:2604.00626v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) continue to grow in both capability and cost, transferring frontier capabilities into smaller, deployable stud

safetyarxiv-cs-cl

Cluster-Aware Neural Collapse Prompt Tuning for Long-Tailed Generalization of Vision-Language Models

arXiv:2605.11939v1 Announce Type: new Abstract: Prompt learning has emerged as an efficient alternative to fine-tuning pre-trained vision-language models (VLMs). Despite its promise, current methods s

safetyarxiv-cs-cv

Config, which is building a data layer for robotics foundation models, raised a 27M seed at a 200M+ valuation led by Samsung Venture Investment (Kate Park/TechCrunch)

Kate Park / TechCrunch: Config, which is building a data layer for robotics foundation models, raised a 27M seed at a 200M+ valuation led by Samsung Venture Investment — Asia's push into physical AI i

applicationstechmeme

Diffusion-State Policy Optimization for Masked Diffusion Language Models

arXiv:2602.06462v3 Announce Type: replace Abstract: Masked diffusion language models generate text through iterative masked-token filling, but terminal-only rewards on final completions provide coarse

safetyarxiv-cs-cl

Do Language Models Encode Knowledge of Linguistic Constraint Violations?

arXiv:2605.12055v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong linguistic performance, yet their internal mechanisms for producing these predictions remain unclear. We inv

researcharxiv-cs-cl

From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction

arXiv:2605.11774v1 Announce Type: new Abstract: By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction t

applicationsarxiv-cs-cl