Search: “models”

We will continue to offer Zero Data Retention for frontier models. As AI takes on longer, more autonomous work and delivers greater value to…

We will continue to offer Zero Data Retention for frontier models. As AI takes on longer, more autonomous work and delivers greater value to businesses, safety systems also need to identify risks acro

safetyopenai--x

19 Aug 2026

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Research

Why GPT-Style Models Do Not Directly Transfer to Symbolic Music: Compression in the Wrong Coordinate System

DGX agent

arXiv:2608.18025v1 Announce Type: cross Abstract: GPT-style models achieve strong performance by representing language with finite vocabularies of reusable discrete tokens. This success has motivated

researcharxiv-cs-ai

19 Aug 2026

Applications

A Plug-and-Play 2D Motion Interface for Real-World Motion Language Models

arXiv:2608.15984v1 Announce Type: new Abstract: Motion Language Models (MoLMs) typically understand human motions by tokenizing 3D motion and processing the resulting tokens using a language model. Ho

applicationsarxiv-cs-cv

ACTS-SQL: Agentic and Critic-Oriented Tree-Structured SQL Correctness with Large Language Models

arXiv:2608.15145v1 Announce Type: new Abstract: Large Language Models (LLMs) have been increasingly adopted in Text-to-SQL systems, yet SQL errors remain a major obstacle in real-world Text-to-SQL inf

Benchmarking Frontier Text-to-Image Models on Image-Description Prompts

model-releasesarxiv-cs-cv

arXiv:2608.14976v1 Announce Type: new Abstract: Text-to-image models are typically reported on average-case prompts, which understates the gap between systems on compositionally demanding requests inv

Benchmarking Quantum Machine Learning for Power-System Attack Detection: Evaluation Choices Decide the Outcome Before the Models Do

model-releasesarxiv-cs-lg

arXiv:2608.15617v1 Announce Type: new Abstract: Machine-learning detectors for power-system cyberattacks are themselves attack surfaces, and quantum machine learning has been proposed for them. We ben

Beyond Tokens: A Survey on Decoding Methods for Large Language and Vision-Language Models

arXiv:2608.14797v1 Announce Type: new Abstract: Large language models (LLMs) and large vision-language models (LVLMs) have demonstrated impressive generative capabilities, yet ensuring their outputs a

researcharxiv-cs-cl

Local Ai

EcoVLA: Energy-Efficient Device-Edge Co-Inference for Vision-Language-Action Models under Real-Time Constraints

arXiv:2608.15502v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a promising foundation for Embodied AI, but their high inference cost poses significant challenges f

local-aiarxiv-cs-ai

Evolving Executable Pipeline Programs for AutoML with Language Models

model-releasesarxiv-cs-lg

arXiv:2608.16416v1 Announce Type: new Abstract: Automated machine learning (AutoML) systems search for pipelines within a space of preprocessing operators, learners, and hyper-parameters specified in

OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models

arXiv:2602.18094v2 Announce Type: replace-cross Abstract: Existing Visual-Language Models (VLMs) have achieved significant progress by being trained on massive-scale datasets, typically under the assu

OpenCode overrides the samplers for Qwen models to the wrong values

model-releasesr-localllama

This is invisible with llama.cpp or derivatives, but ninfer helpfully logs the sampler settings on each request and auto-configures the correct ones for the model. Basically, OpenCode will always send

Seeing Before Answering: Training-Free Visual Layer Profiling for Vision-Language Models

arXiv:2608.16263v1 Announce Type: new Abstract: LLaVA-style Vision-Language Models (VLMs) pass visual tokens from a fixed late layer of the vision backbone, typically the penultimate one, to the langu

The Political Ideology of Large Language Models: Measurement, Inconsistency, and Persuasive Influence

arXiv:2505.04171v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the wor

safetyarxiv-cs-cl

The Quantum Shortcut: Complex Phase-State Dynamics Reduce the Optimization Steps of Sequence Models

arXiv:2608.14691v1 Announce Type: new Abstract: Sequence models are conventionally distinguished by their backbone, the mechanism that routes information across positions, such as attention or recurre

What Makes a Good Layer? Assessing the Layer-Wise Intrinsic Properties of Music Foundation Models

arXiv:2608.14819v1 Announce Type: cross Abstract: Music foundation models are commonly used as frozen audio feature extractors, yet selecting which layer to extract from remains largely heuristic. Cur

Content Based Video Narration of Gameplay with Vision Language Models

arXiv:2608.14016v1 Announce Type: cross Abstract: Live game commentary is scarce: it exists for professional esports broadcasts and almost nowhere else. We present a content-based video narration syst

Early Stopping for Large Reasoning Models via Confidence Dynamics

arXiv:2604.04930v2 Announce Type: replace-cross Abstract: Large reasoning models rely on long chain-of-thought generation to solve complex problems, but extended reasoning often incurs substantial com

From Passive Delegates to Strategic Negotiators: Reinforcing Social Reasoning in Small Language Models with SocialRL

arXiv:2608.13787v1 Announce Type: new Abstract: AI agents increasingly act on their users' behalf, handling tasks such as scheduling meetings, comparing offers, and haggling over prices. These princip

Stable Miscalibration in Large Language Models: A Practical View of High-Confidence Errors

arXiv:2608.13591v1 Announce Type: new Abstract: High-confidence errors in large language models are often treated as evidence of fragile internal inference. We study a different possibility: stable mi

Industry

Pathway, which is developing AI models based on what it calls its 'Post-Transformer' BDH architecture, raised a 30M seed at a 500M valuation (Antoine Tardif/Unite.AI)

Antoine Tardif / Unite.AI: Pathway, which is developing AI models based on what it calls its “Post-Transformer” BDH architecture, raised a 30M seed at a 500M valuation — AI research company Pathway ha

industrytechmeme

16 Aug 2026

Can Generalist Vision Language Models (VLMs) Rival Specialist Medical VLMs? Benchmarking and Strategic Insights

arXiv:2506.17337v5 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown promise in automating image diagnosis and interpretation in clinical settings. However, developing sp

Tutorials

Diagnosing JEPA World Models with Action-Conditioned Predictive Consistency

arXiv:2608.12939v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) learn world models that predict in a compact latent space rather than in pixels, reducing the pressure

tutorialsarxiv-cs-lg

How Good are Foundation Models in Longitudinal MRI Disease Progression Reasoning?

model-releasesarxiv-cs-cv

arXiv:2608.13309v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) interpretation is fundamental to clinical decision-making, requiring radiologists to integrate multi-view anatomical pl

neurosymbolic world models – exactly what I argued for in 2020 in the Next Decade in AI – for the win.

neurosymbolic world models – *exactly* what I argued for in 2020 in the Next Decade in AI – for the win. Jeremy's excellent work here is a great illustration of a very powerful type of approach: LLM-g

safetygary-marcus--x

Accelerating Time Series Foundation Models with Speculative Decoding

arXiv:2511.18191v2 Announce Type: replace Abstract: Time series forecasting drives operational decisions under tight latency budgets, and autoregressive time series foundation models (TSFMs) increasin

Better Slots, Better Worlds: Representation Quality & Robustness in Object-Centric World Models

arXiv:2608.12078v1 Announce Type: cross Abstract: Learning world models from offline trajectories enables agents to accomplish different tasks through planning. Object-centric (OC) representations, wh

safetyarxiv-cs-ai

Conflict and Congruency Effects in Large Language Models: In-Weight and In-Context Competition in a Verbal Conflict Task

arXiv:2608.11510v1 Announce Type: cross Abstract: Congruency effects, observed in conflict tasks such as Stroop and flanker tasks, have been investigated for nearly a century in psychology and neurosc

Applications

Dynamics Models for Offline Hyperparameter Selection in Real-World RL

arXiv:2608.11349v1 Announce Type: cross Abstract: A key obstacle to deploying reinforcement learning in real-world systems is hyperparameter selection, particularly when simulators are unavailable and

applicationsarxiv-cs-ai

ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models

arXiv:2608.11949v1 Announce Type: new Abstract: Roles provide an interpretable interface for organizing language-model agents, yet most multi-agent systems treat them as hand-written prompt labels dis

Program Semantic Inequivalence Game with Large Language Models

arXiv:2505.03818v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can achieve strong performance on everyday coding tasks, but they can fail on complex tasks that require non-triv

Thanks. The fact that it works so well for ARC is also a clue to the extent of generalization in these models. It was not at all obvious tha…

researchfrancois-chollet--x

Thanks. The fact that it works so well for ARC is also a clue to the extent of generalization in these models. It was not at all obvious that it would work originally because the model is never traine

Hardware

The Coachella of robotics, world models, and physical AI is Runway’s SF Summit, coming to the Bay Area on September 30. Speaker lineup: @Qua…

hardwarecristobal-valenzuela--x

The Coachella of robotics, world models, and physical AI is Runway’s SF Summit, coming to the Bay Area on September 30. Speaker lineup: @QuanVng from @physical_int, @liu_mingyu from @nvidia, @robertni

Local Ai

Understanding Why Foundation Models Work for Diffusion-Generated Image Detection

arXiv:2608.12155v1 Announce Type: new Abstract: Vision foundation models have recently emerged as powerful feature extractors for detecting AI-generated images, achieving strong generalization across

local-aiarxiv-cs-cv

Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?

arXiv:2603.02462v2 Announce Type: replace-cross Abstract: A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a give

Frozen Brain-MRI Foundation Models Are Site Fingerprints

arXiv:2608.10295v1 Announce Type: cross Abstract: Frozen foundation-model (FM) embeddings are increasingly used as off-the-shelf brain-MRI representations, on the assumption that they capture anatomy.

Generation-Step-Aware Framework for Cross-Modal Representation and Control in Multilingual Speech-Text Models

arXiv:2601.17387v3 Announce Type: replace Abstract: Multilingual speech-text models rely on cross-modal language alignment to transfer knowledge between speech and text, but it remains unclear whether

safetyarxiv-cs-cl

Grok 4.6 is now one of the top models in the world for agentic workflows It ranks #1 on the Artificial Analysis Agentic Index, tied with Cla…

model-releaseselon-musk--x

Grok 4.6 is now one of the top models in the world for agentic workflows It ranks #1 on the Artificial Analysis Agentic Index, tied with Claude Opus 5 Max Agentic AI is about more than answering quest

Learning in ImaginationLand: Omnidirectional Policies through 3D Generative Models (OP-Gen)

arXiv:2509.06191v2 Announce Type: replace-cross Abstract: Recent 3D generative models, which are capable of generating full object shapes from just a few images, now open up new opportunities in robot

MedUP: Awakening Unified Understanding and Perception in Medical Vision-Language Models

arXiv:2608.10635v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) excel at verbalizing visual content, yet precise visual perception, segmentation, and grounding remain chall

safetyarxiv-cs-ai

Multi-View Relational Distillation for Spatial Reasoning with Vision-Language Models

arXiv:2608.10864v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong image and video understanding, yet their visual-spatial representations remain geometrically fragile,

Applications

Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets

arXiv:2608.10657v1 Announce Type: cross Abstract: Leukemia cell image classification is challenged by real-world domain shifts from acquisition, staining, illumination, and site protocols, causing sin

applicationsarxiv-cs-cv

SynBoost: A Synergistic Framework for Fast Sampling of Diffusion Models

arXiv:2506.13058v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism r

Automated Generation of Complexity-Validated Decision Scenarios Using Large Language Models

arXiv:2608.08822v1 Announce Type: new Abstract: Cognitive decision-making research depends on diverse scenarios with carefully controlled complexity, yet manual production is slow, inconsistent, and b

Deployable Per-Instance Multi-Layer Activation Steering for Large Language Models

arXiv:2608.08829v1 Announce Type: cross Abstract: Activation steering edits the behaviour of a frozen language model by adding a learned vector to its residual stream, and current practice fixes the i

safetyarxiv-cs-ai

FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language Models

model-releasesarxiv-cs-cl

arXiv:2511.18852v2 Announce Type: replace Abstract: Content moderation filters are a critical safeguard against alignment failures in language models. Yet most existing filters focus narrowly on gener

FlowErase-OPD: Multi-Concept Erasure via Anchored On-Policy Distillation in Flow Matching Models

arXiv:2608.07620v1 Announce Type: new Abstract: Recent advances in flow matching models have substantially improved the quality of text-to-image generation, but have also raised increasing safety conc

From Uncertainty to Failure Attribution: Self-Diagnosing Models for Failure Attribution under Distribution Shift

arXiv:2608.07953v1 Announce Type: new Abstract: Distribution shift poses a significant challenge to the robustness of machine learning models, but the current solutions only aim to detect out-of-distr

How sensitive do we want AI to be? Socio-communicative competencies of large language models in healthcare

arXiv:2608.07511v1 Announce Type: cross Abstract: Background. Effective clinical practice relies heavily on the socio-communicative skills of medical professionals. Large language models (LLMs) have b