Search: “models”

arXiv:2605.27920v1 Announce Type: new Abstract: Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between

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Local Ai

Reverse Probing: Supervised Token-level Uncertainty Quantification for Large Language Models in Clinical Text

DGX agent

arXiv:2605.28740v1 Announce Type: cross Abstract: As large language models are increasingly deployed for clinical text, ensuring they can reliably signal their own uncertainty becomes critical. Most e

local-aiarxiv-cs-ai

28 May 2026

Routing-Aligned Fine-Tuning for Multilingual Downstream Tasks in Mixture-of-Experts Models

arXiv:2605.28306v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have emerged as a dominant paradigm for efficient LLM scaling, yet adapting them to non-English downstream tasks remai

Agents

Self-Improving Language Models with Bidirectional Evolutionary Search

arXiv:2605.28814v1 Announce Type: new Abstract: Search has been proposed as an effective method for self-improving language models and agentic systems, both for post-training sample generation and for

agentsarxiv-cs-cl

.@ylecun making his usual impassioned case for LLMs and RL 🍒 for world models ... just kidding 🤓 Thanks Yann for the thought-provoking tal…

Yann LeCun discusses his perspectives on large language models (LLMs) and reinforcement learning (RL) as approaches for developing world models, presenting arguments he frequently advocates for in the

researchyann-lecun--x

Tools

10/ The bigger point: your product is the best RL environment you'll ever have. Frontier labs ship models that are good at everything. The o…

10/ The bigger point: your product is the best RL environment you'll ever have. Frontier labs ship models that are good at everything. The opportunity is a model that's great at your thing. Product, u

toolsfireworks-ai--x

🎙️@alexrives on 'AI for Science' with @latentspacepod breaking down our world model of protein biology: ESMFold2, ESMC, and ESM Atlas. http…

Alex Rives discusses advanced AI models for protein biology on the Latent Space podcast, including ESMFold2 (an improved protein structure prediction tool), ESMC (a protein language model), and ESM At

researchyann-lecun--x

Align & Invert: Solving Inverse Problems with Diffusion and Flow-based Models via Representation Alignment

arXiv:2511.16870v3 Announce Type: replace Abstract: Enforcing alignment between the internal representations of diffusion or flow-based generative models and those of pretrained self-supervised encode

safetyarxiv-cs-cv

🆕Biohub’s Protein World Model: ESMC-6B, ESMFold2, 6.8B proteins, 1.1B structures, antibody design, SAEs, & the bitter lesson for biology ht…

🆕Biohub’s Protein World Model: ESMC-6B, ESMFold2, 6.8B proteins, 1.1B structures, antibody design, SAEs, & the bitter lesson for biology https://www.latent.space/p/esmfold2 @biohub Head of Science @al

tutorialsswyx--x

Co-folding model guided by structural proteomics

arXiv:2605.26192v1 Announce Type: cross Abstract: Protein structure generative models excel at predicting single protein static structures from sequence, but routinely fail to capture the correct conf

Corrected Samplers for Discrete Flow Models

arXiv:2601.22519v2 Announce Type: replace-cross Abstract: Discrete flow models (DFMs) have been proposed to learn the data distribution on finite state space, offering a flexible framework as an alter

tutorialsarxiv-cs-lg

Generating realistic global precipitation fields from modelled atmospheric circulation

arXiv:2504.00307v2 Announce Type: replace Abstract: Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially o

researcharxiv-cs-lg

How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning

arXiv:2605.27310v1 Announce Type: new Abstract: Cross-view spatial reasoning remains a weak spot for vision-language models (VLMs): they often reason in language and lose the fine-grained geometry nee

tutorialsarxiv-cs-cv

Jailbreak susceptibility prediction and mitigation via the behavioral geometry of models

arXiv:2605.26409v1 Announce Type: cross Abstract: Evaluating and mitigating a generative system's susceptibility to jailbreak attacks is critical to its safe deployment. Given the number of deployable

Model discovery for dynamical systems with complex-valued product units

model-releasesarxiv-cs-cv

arXiv:2605.27158v1 Announce Type: new Abstract: Discovering the governing equations of a dynamical system from observed trajectories provides deeper insight into its structure than mere prediction of

Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models

arXiv:2605.27101v1 Announce Type: cross Abstract: A key capability for video understanding is reliably linking subjects to events across time, yet whether Video Large Language Models (VideoLLMs) actua

researcharxiv-cs-cl

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications

arXiv:2605.26133v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become the predominant paradigm in NLP, advancing both research and industry. As model sizes and pretraining data gr

PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design

model-releasesarxiv-cs-lg

arXiv:2605.26502v1 Announce Type: new Abstract: The inverse problem of multilayer thin-film optical coatings design represents a complex combinatorial-continuous optimization challenge. We present PRI

Sleep-stage efficient classification using a lightweight self-supervised model

arXiv:2605.26295v1 Announce Type: new Abstract: Accurate classification of sleep stages is crucial for diagnosing sleep disorders and automating this process can significantly enhance clinical assessm

researcharxiv-cs-cv

The Attribution Blind Spot: Detecting When Language Models Rely on Memory Rather Than Retrieved Context

arXiv:2605.26778v1 Announce Type: new Abstract: Retrieval-augmented generation promises to ground language model outputs in external evidence, yet the field has no reliable way to verify whether retri

Local Ai

This Week In AI Models and Workflows https://x.com/i/broadcasts/1wxWjjRqABkJQ

This is a live broadcast or discussion from ComfyUI's X (Twitter) account covering recent developments and updates in AI models and workflows. The content likely showcases new features, model releases

local-aicomfyui--x

Unified Panoramic Geometry Estimation via Multi-View Foundation Models

arXiv:2605.26368v1 Announce Type: cross Abstract: Geometry estimation from perspective images has greatly advanced, maturing to the point where off-the-shelf foundation models are able to reconstruct

What does JEPA actually learn? We can finally prove it 🌍 So excited to share our theory of identifiable World Models: LeJEPA recovers the l…

What does JEPA actually learn? We can finally prove it 🌍 So excited to share our theory of identifiable World Models: LeJEPA recovers the latent variables of the world. Plan in the learned World Model

tutorialsyann-lecun--x

When Does Demographic Information Help? Data and Modeling Regimes for Perspective-Aware Hate Speech Detection

arXiv:2605.27313v1 Announce Type: new Abstract: Demographic information is often used to model annotator perspectives in subjective tasks such as hate speech detection, but its benefit is inconsistent

researcharxiv-cs-cl

A general tensor-structured compression scheme for efficient large language models

arXiv:2605.25344v1 Announce Type: cross Abstract: Large language models (LLMs) are dominated by dense linear transformations, whose storage, memory and computational overheads hinder efficient adaptat

A governance horizon for ethical-use constraints in open-weight AI models

arXiv:2605.24383v1 Announce Type: new Abstract: Ethical constraints on open-weight AI models are both a reflection of societal concerns and a foundation for AI governance policy. They are expected to

A World Model of Radiologist Reading for Medical Image Representation Learning

arXiv:2605.23992v1 Announce Type: cross Abstract: Radiologist eye-tracking data provide a rich record of how experts search, compare, and accumulate evidence during image reading; yet, existing method

AgentGrounder: Zero-Shot 3D Visual Pointcloud Grounding using Multimodal Language Models

model-releasesarxiv-cs-ro

arXiv:2605.25901v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) is an essential capability for embodied AI, requiring agents to localize objects in 3D scenes based on natural language des

An Interpretable CF-RL-TOPSIS Fusion Model for Skills-Aware Talent Recommendation

arXiv:2605.24155v1 Announce Type: cross Abstract: Effective skills-aware talent recommendation must balance behavioral transition patterns, trajectory-sensitive adaptation, and inspectable occupation-

AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation

arXiv:2601.03191v3 Announce Type: replace-cross Abstract: Multimodal medical large language models have shown substantial progress in chest X-ray interpretation but continue to face challenges in spat

Applications

Assessing the Operational Viability of Foundation Models for Time Series Forecasting

arXiv:2605.24381v1 Announce Type: cross Abstract: Time series forecasting drives operational decisions in areas like finance, transportation, and energy. While supervised learning approaches achieve s

applicationsarxiv-cs-ai

Agents

Attested Tool-Server Admission: A Security Extension to the Model Context Protocol

arXiv:2605.24248v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) standardizes how a large-language-model (LLM) agent and an external tool server exchange messages, but not trust: a h

agentsarxiv-cs-ai

AVBench: Human-Aligned and Automated Evaluation Benchmark for Audio-Video Generative Models

arXiv:2605.24652v1 Announce Type: new Abstract: Rapid advances in audio-video (AV) generation have enabled high-fidelity synthesis with synchronized sound, particularly for human-related scenarios inv

Local Ai

Credit Assignment with Resets in Language Model Reasoning

arXiv:2605.25507v1 Announce Type: new Abstract: Contemporary reinforcement learning with verifiable reward methods post-train language models on multi-step reasoning by assigning a single outcome rewa

local-aiarxiv-cs-ai

ECHO: Terminal Agents Learn World Models for Free

arXiv:2605.24517v1 Announce Type: cross Abstract: CLI agents are the closest thing language models have to an embodied setting: the model emits commands, the terminal executes them, and the returned s

safetyarxiv-cs-cl

Filtered Posterior Mean Collections: A Unified Framework for Analytical Models of Diffusion Generalization

arXiv:2605.24192v1 Announce Type: cross Abstract: The neural-network denoising functions which form the backbone of image diffusion models are remarkably consistent in their generalization behaviour a

FLoRIST: Singular Value Thresholding for Efficient and Accurate Federated Fine-Tuning of Large Language Models

arXiv:2506.09199v2 Announce Type: replace-cross Abstract: Integrating Low-Rank Adaptation (LoRA) into federated learning offers a promising solution for parameter-efficient fine-tuning of Large Langua

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay

arXiv:2605.26097v1 Announce Type: new Abstract: Models trained on a new task typically degrade on prior tasks, a phenomenon known as forgetting. Traditionally, mitigating forgetting has required repla

researcharxiv-cs-lg

FOUND-IT: Foundation-model-first Task-driven 3D Scene Graphs with Granularity on Demand

model-releasesarxiv-cs-ro

arXiv:2605.25371v1 Announce Type: new Abstract: We present the first approach to build hierarchical task-driven 3D scene graphs of arbitrary indoor or outdoor environments using an uncalibrated monocu

Industry

I think folk are underestimating how much of AI models are actually engineering at scale versus breakthrough research. See how @cursor_ai ca…

I think folk are underestimating how much of AI models are actually engineering at scale versus breakthrough research. See how @cursor_ai caught up to Anthropic / OpenAI models run at a fraction of th

industryemad-mostaque--x

Inference-Time Alignment of Diffusion Models via Trust-Region Iterative Twisted Sequential Monte Carlo

arXiv:2605.25123v1 Announce Type: cross Abstract: We study inference-time alignment for diffusion-based generative models, aiming to steer a base model toward high-reward outputs without updating its

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models

arXiv:2510.01389v2 Announce Type: replace-cross Abstract: Recent Vision-Language-Action (VLA) models show strong generalization capabilities, yet they lack introspective mechanisms for anticipating fa

Learning Concepts, Not Tokens: Self-Supervised Semantic Alignment for Language Models

arXiv:2603.29123v2 Announce Type: replace Abstract: The next-token prediction (NTP) objective trains language models to predict a single token at each step, even though many continuations can express

safetyarxiv-cs-cl

Logic-Guided Socially-aware Robot Navigation World Model

arXiv:2510.23509v2 Announce Type: replace Abstract: Social robot navigation increasingly relies on large language models for reasoning, path planning, and enabling movement in dynamic human spaces. Ho

researcharxiv-cs-ro

Hardware

MathOptAI.jl: Embed trained machine learning predictors into JuMP models

arXiv:2507.03159v2 Announce Type: replace Abstract: We present exttt{MathOptAI.jl}, an open-source Julia library for embedding trained machine learning predictors into a JuMP model. exttt{MathOptAI.jl

hardwarearxiv-cs-lg

Applications

Membership Inference Attacks on Tokenizers of Large Language Models

arXiv:2510.05699v4 Announce Type: replace-cross Abstract: Membership inference attacks (MIAs) are widely used to assess the privacy risks associated with machine learning models. However, when these a

applicationsarxiv-cs-ai

Neural Stochastic Differential Equations on Compact State Spaces: Theory, Methods, and Application to Suicide Risk Modeling

arXiv:2508.17090v4 Announce Type: replace-cross Abstract: Ecological Momentary Assessment (EMA) studies enable the collection of high-frequency self-reports of suicidal thoughts and behaviors (STBs) v

researcharxiv-cs-lg

PEDESTRIANQA: A Benchmark for Vision-Language Models on Pedestrian Intention and Trajectory Prediction

arXiv:2605.24562v1 Announce Type: cross Abstract: Pedestrian intention and trajectory prediction are critical for the safe deployment of autonomous driving systems, directly influencing navigation dec