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more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI

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more demos on Interaction Models collaboratively doing system design, reading papers, fact-checking with live generative UI 1. (System design) - The Interaction Models see your screen and collaborates

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ReAD: Reinforcement-Guided Capability Distillation for Large Language Models

DGX agent

arXiv:2605.11290v1 Announce Type: new Abstract: Capability distillation applies knowledge distillation to selected model capabilities, aiming to compress a large language model (LLM) into a smaller on

researcharxiv-cs-cl

13 May 2026

Scalable Token-Level Hallucination Detection in Large Language Models

arXiv:2605.12384v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable capabilities, but they still frequently produce hallucinations. These hallucinations are diffi

Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey

arXiv:2304.10891v2 Announce Type: replace-cross Abstract: Transformer-based models are becoming a central paradigm in autonomous driving because they can capture long-range spatial dependencies, multi

safetyarxiv-cs-cv

We’re training models wrong and it’s due to chatGPT. Even the modern coding agents used daily still use message-based exchanges: They send m…

We’re training models wrong and it’s due to chatGPT. Even the modern coding agents used daily still use message-based exchanges: They send messages to users, to themselves (CoT) and to tools, and rece

agentsjeremy-howard--x

Active Testing of Large Language Models via Approximate Neyman Allocation

arXiv:2605.10075v1 Announce Type: new Abstract: Large language models (LLMs) require reliable evaluation from pre-training to test-time scaling, making evaluation a recurring rather than one-off cost.

ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

arXiv:2605.10819v1 Announce Type: cross Abstract: Vision-language-action (VLA) models remain constrained by the scarcity of action-labeled robot data, whereas action-free videos provide abundant evide

safetyarxiv-cs-ai

Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models

arXiv:2512.03706v2 Announce Type: replace-cross Abstract: Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dyn

researcharxiv-cs-lg

Dimensional Coactivation for Representational Consistency in Frozen Vision Foundation Models

arXiv:2605.08249v1 Announce Type: new Abstract: Frozen vision foundation models do not merely extract features; they organize images through a learned coordinate system. We ask whether that coordinate

Empty SPACE: Cross-Attention Sparsity for Concept Erasure in Diffusion Models

arXiv:2605.10198v1 Announce Type: cross Abstract: Erasing specific concepts from text-to-image diffusion models is essential for avoiding the generation of copyrighted and explicit content. Closed-for

Local Ai

ExecuTorch -- A Unified PyTorch Solution to Run AI Models On-Device

arXiv:2605.08195v1 Announce Type: new Abstract: Local execution of AI on edge devices is important for low latency and offline operation. However, deploying models on diverse hardware remains fragment

local-aiarxiv-cs-lg

FactoryNet: A Large-Scale Dataset toward Industrial Time-Series Foundation Models

arXiv:2605.09081v1 Announce Type: cross Abstract: We introduce the first universal pretraining corpus for industrial time-series data: FactoryNet. 51M datapoints across 23k end-to-end task executions

Tutorials

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models

arXiv:2605.09949v1 Announce Type: new Abstract: Understanding how chemical language models (CLMs) learn chemical meaning from molecular string representations, rather than only surface-level string pa

tutorialsarxiv-cs-lg

Learning stochastic multiscale models through normalizing flows

arXiv:2605.09718v1 Announce Type: cross Abstract: Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influe

researcharxiv-cs-lg

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale

arXiv:2605.10886v1 Announce Type: cross Abstract: Recent GPU generations deliver significantly higher FLOPs using lower-precision arithmetic, such as FP8. While successfully applied to large language

hardwarearxiv-cs-ai

MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction

arXiv:2605.08094v1 Announce Type: cross Abstract: Accurate clinical diagnosis requires extensive domain knowledge and complex clinical reasoning capabilities. Although large language models (LLMs) hol

PermuQuant: Lowering Per-Group Quantization Error by Reordering Channels for Diffusion Models

arXiv:2605.09503v1 Announce Type: new Abstract: Large-scale visual generative models have achieved remarkable performance. However, their high computational and memory costs make deployment challengin

hardwarearxiv-cs-cv

Applications

Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Models

arXiv:2605.09666v1 Announce Type: cross Abstract: Multiple Sclerosis (MS) is a chronic autoimmune disease that can significantly reduce the quality of life of a patient. Existing treatment options can

applicationsarxiv-cs-ai

Tutorials

Sparse Reward Subsystem in Large Language Models

arXiv:2602.00986v2 Announce Type: replace Abstract: Recent studies show that LLM hidden states encode reward-related information, such as answer correctness and model confidence. However, existing app

tutorialsarxiv-cs-cl

Supervised Guidance Training for Infinite-Dimensional Diffusion Models

arXiv:2601.20756v2 Announce Type: replace Abstract: Score-based diffusion models have recently been extended to infinite-dimensional function spaces, with uses such as inverse problems arising from pa

researcharxiv-cs-lg

TinySSL: Distilled Self-Supervised Pretraining for Sub-Megabyte MCU Models

arXiv:2605.08241v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has transformed representation learning for large models, yet remains unexplored for microcontroller (MCU)-class models

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse

model-releasesarxiv-cs-cv

arXiv:2605.09965v1 Announce Type: new Abstract: The real world unfolds along a single set of physics laws, yet human intelligence demonstrates a remarkable capacity to generalize experiences from this

Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models

arXiv:2605.08128v1 Announce Type: cross Abstract: Gene Regulatory Network (GRN) inference is essential for understanding complex cellular mechanisms, rendered tractable through single-cell transcripto

Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlo

model-releasesarxiv-cs-lg

arXiv:2605.09125v1 Announce Type: cross Abstract: Preliminary low-thrust spacecraft mission design is a global search problem characterized by a complex solution landscape, multiple objectives, and nu

We published new research on how we serve post-trained Qwen3 235B models on NVIDIA GB200 NVL72 Blackwell racks. GB200 is a major step up ove…

We published new research on how we serve post-trained Qwen3 235B models on NVIDIA GB200 NVL72 Blackwell racks. GB200 is a major step up over Hopper for high-throughput inference on large MoE models,

hardwareperplexity--x

You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models

arXiv:2510.03761v2 Announce Type: replace-cross Abstract: The widespread use of preprint repositories such as arXiv has accelerated the communication of scientific results but also introduced overlook

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models

arXiv:2605.06829v1 Announce Type: cross Abstract: We survey continuous-time generative modeling methods based on transporting a simple reference distribution to a data distribution via stochastic or d

Dealing with quirks introduced by switching models doesn't have to be hard -- we recently introduced a 'harness profile' API in Deep Agents …

Dealing with quirks introduced by switching models doesn't have to be hard -- we recently introduced a 'harness profile' API in Deep Agents as a solution. Profiles adjust system prompts, tool descript

agentsharrison-chase--x

DiffRetriever: Parallel Representative Tokens for Retrieval with Diffusion Language Models

arXiv:2605.07210v1 Announce Type: cross Abstract: PromptReps showed that an autoregressive language model can be used directly as a retriever by prompting it to generate dense and sparse representatio

Local Ai

Distributional simplicity bias and effective convexity in Energy Based Models

arXiv:2605.07844v1 Announce Type: new Abstract: Energy-based learning is a powerful framework for generative modelling, but its training is inherently non-convex, leading potentially to sensitivity to

local-aiarxiv-cs-lg

Local Ai

Emergent Manifold Separability during Reasoning in Large Language Models

arXiv:2602.20338v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly improves reasoning in Large Language Models, yet the temporal dynamics of the underlying representati

local-aiarxiv-cs-lg

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

arXiv:2512.20974v3 Announce Type: replace-cross Abstract: Bayesian Reinforcement Learning (BRL), a subclass of Meta-Reinforcement Learning (Meta-RL), provides a principled framework for generalisation

safetyarxiv-cs-ai

Tutorials

Human-like fleeting memory improves language learning but impairs reading time prediction in transformer language models

arXiv:2508.05803v2 Announce Type: replace Abstract: Human memory is fleeting. As words are processed, the exact wordforms that make up incoming sentences are rapidly lost. Cognitive scientists have lo

tutorialsarxiv-cs-cl

Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models

arXiv:2605.07514v1 Announce Type: cross Abstract: World Action Models (WAMs) enable decision-making through imagined rollouts by predicting future observations and actions. However, the reliability of

safetyarxiv-cs-cv

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation

arXiv:2605.07640v1 Announce Type: cross Abstract: Remote sensing lithology interpretation is fundamental to geological surveys, mineral exploration, and regional geological mapping. Unlike general lan

Miner:Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models

arXiv:2601.04731v2 Announce Type: replace Abstract: Current critic-free RL methods for large reasoning models suffer from severe inefficiency when training on positive homogeneous prompts (where all r

safetyarxiv-cs-ai

PSK@EEUCA 2026: Fine-Tuning Large Language Models with Synthetic Data Augmentation for Multi-Class Toxicity Detection in Gaming Chat

arXiv:2605.07201v1 Announce Type: cross Abstract: This paper describes our system for the EEUCA 2026 Shared Task on Understanding Toxic Behavior in Gaming Communities. The task involves classifying Wo

Render, Don't Decode: Weight-Space World Models with Latent Structural Disentanglement

arXiv:2605.06298v2 Announce Type: replace-cross Abstract: Training world models on vast quantities of unlabelled videos is a critical step toward fully autonomous intelligence. However, the prevailing

hardwarearxiv-cs-ai

Applications

Script Sensitivity: Benchmarking Language Models on Unicode, Romanized and Mixed-Script Sinhala

arXiv:2601.14958v3 Announce Type: replace-cross Abstract: The performance of Language Models (LMs) on low-resource, morphologically rich languages like Sinhala remains largely unexplored, particularly

applicationsarxiv-cs-ai

Sparser, Faster, Lighter Transformer Language Models

arXiv:2603.23198v2 Announce Type: replace-cross Abstract: Scaling autoregressive large language models (LLMs) has driven unprecedented progress but comes with vast computational costs. In this work, w

hardwarearxiv-cs-cl

This seems like a critical reason to open up about AI use in academia. Scholars are using old AI models, badly, and not talking about it. Ne…

This seems like a critical reason to open up about AI use in academia. Scholars are using old AI models, badly, and not talking about it. New models hallucinate very few citations, and good agentic ha

agentsethan-mollick--x

ai coding is getting expensive use more open models!

ai coding is getting expensive use more open models! Kimi K2.6 on @baseten is ~5x cheaper than Opus 4.7 For a large majority of tasks, it's roughly the same performance If you want to use open models

agentsharrison-chase--x

8 May 2026

ArtiFixer: Enhancing and Extending 3D Reconstruction with Auto-Regressive Diffusion Models

arXiv:2603.00492v2 Announce Type: replace Abstract: Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-o

Counter-Dyna: Data-Efficient RL-Based HVAC Control using Counterfactual Building Models

arXiv:2605.04555v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) offers a promising approach for data-efficient energy management in buildings, combining the strengths of pred

safetyarxiv-cs-lg

Detecting Hallucinations in Large Language Models via Internal Attention Divergence Signals

arXiv:2605.05025v1 Announce Type: new Abstract: We propose a lightweight and single-pass uncertainty quantification method for detecting hallucinations in Large Language Models. The method uses attent

From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models

arXiv:2605.04678v1 Announce Type: cross Abstract: Latent actions serve as an intermediate representation that enables consistent modeling of vision-language-action (VLA) models across heterogeneous da

Implicit Representations of Grammaticality in Language Models

arXiv:2605.05197v1 Announce Type: new Abstract: Grammaticality and likelihood are distinct notions in human language. Pretrained language models (LMs), which are probabilistic models of language fitte

Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis

arXiv:2605.04063v1 Announce Type: new Abstract: Alzheimer's Dementia (AD) is a progressive neurodegenerative disease marked by irreversible decline, making reliable modeling of its progression essenti

safetyarxiv-cs-lg