tutorials

arXiv:2510.22138v3 Announce Type: replace Abstract: We show how to replace the O(2^n) coalition enumeration over n features behind Shapley values and Shapley-style interaction indices with a few-evalu

arXiv:2606.01457v1 Announce Type: new Abstract: Bayesian optimization is a popular way to optimize expensive systems, where every experiment, simulation, or intervention costs time or money. In its st

Travelers Insurance has deployed an AI system powered by OpenAI technology across its operations nationwide to streamline and improve claims processing. The implementation leverages OpenAI's capabilit

arXiv:2606.01000v1 Announce Type: cross Abstract: Weak-to-strong generalization studies how to improve a strong student using supervision from a weaker teacher when reliable labels are scarce. We view

Verification is the hidden bottleneck for knowledge work agents, especially in legal AI — complex, long-horizon work is graded by rubrics with dozens of strict criteria. In new research with @LangChai

arXiv:2510.17045v2 Announce Type: replace-cross Abstract: Video reasoning using Large Multimodal Models (LMMs) relies on costly reinforcement learning (RL) and verbose chain-of-thought, resulting in s

arXiv:2509.15394v3 Announce Type: replace Abstract: Accurate electricity demand forecasting is challenging due to the strong multi-periodicity of real-world demand series, which makes effective modeli

arXiv:2606.02106v1 Announce Type: new Abstract: We present a single classification pipeline that combines an Equiangular Tight Frame (ETF) preprocessing stage with a tabular foundation model for in-co

arXiv:2603.00133v2 Announce Type: replace-cross Abstract: Generative models have been shown to 'memorize' certain training data, leading to verbatim or near-verbatim generating images, which may cause

6 months ago I said I won't stop until I have Kimi at home, after 10+ botched REAPs I finally have it Needs benchmarking of course. - 45 tok/s decode - 954 tok/s prefill no cache - 95k+ tok/s cached p

arXiv:2605.31340v1 Announce Type: cross Abstract: The appropriateness of empathy in AI has emerged as a critical concern, as excessive empathy risks seeming manipulative while insufficient empathy app

arXiv:2605.31152v1 Announce Type: cross Abstract: This paper studies how efficiently deep ReLU neural networks can approximate and learn smooth functions. When the error is measured in L^p([0,1]^d) no

arXiv:2605.30912v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves vision-language models (VLMs) by optimizing outcome rewards derived from final answers.

arXiv:2602.16305v2 Announce Type: replace-cross Abstract: Probing is widely adopted in computer vision to faithfully evaluate self-supervised learning (SSL) embeddings, as finetuning may misrepresent

arXiv:2510.20853v2 Announce Type: replace-cross Abstract: Electrophysiological (ExG) signals offer valuable insights into human physiology, yet building foundation models that generalize across everyd

arXiv:2605.30610v1 Announce Type: new Abstract: Adapting generative foundation models, in particular diffusion and flow models, to optimize given reward functions (e.g., binding affinity) while satisf

arXiv:2605.30553v1 Announce Type: new Abstract: I present diffusion models as part of a family of machine learning techniques that withhold information from a model's input and train it to guess the w

arXiv:2605.31147v1 Announce Type: cross Abstract: User Experience Research (UXR) Points of View (POVs) distil complex and often fragmented research evidence into actionable perspectives that guide how

arXiv:2605.31138v1 Announce Type: cross Abstract: User Experience Research (UXR) in a legal and regulatory contexts presents unique challenges that require specialised approaches to protect vulnerable

arXiv:2605.31563v1 Announce Type: new Abstract: Human disagreement is ubiquitous and well-known in labeling. However, variation in explanations, captured through token-level human rationales, remains

arXiv:2605.30876v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive models, offering competitive performance whil

arXiv:2605.30992v1 Announce Type: new Abstract: Sparse Mixture of Experts (SMoE) architectures improve the training efficiency of Large Language Models (LLMs) by routing input tokens to a selected sub

arXiv:2506.01928v4 Announce Type: replace Abstract: Diffusion-based language models offer a compelling alternative to autoregressive (AR) models by enabling parallel and controllable generation. Withi

arXiv:2605.30819v1 Announce Type: new Abstract: Most text-driven 3D indoor scene synthesis methods generate rooms from object-centric prompts, asking what furniture should be placed rather than how th

arXiv:2603.16123v2 Announce Type: replace-cross Abstract: Neural networks often learn the parts of a task but fail on novel combinations of those parts. We argue that this failure is architectural: a

arXiv:2603.09936v2 Announce Type: replace Abstract: Generative Modeling via Drifting~itep{deng2026drifting} has recently achieved state-of-the-art one-step image generation through a kernel-based drif

arXiv:2605.30866v1 Announce Type: cross Abstract: Many practically relevant applications of quantum machine learning involve classical data, for which performance depends critically on how inputs are

great overview of deepagents! what it is, how we made it great at complex tasks, how to take it to production here's a quick overview of a) what is deepagents b) what makes deepagents good at complex

arXiv:2605.31162v1 Announce Type: new Abstract: Unconditional diffusion models offer powerful generative priors, yet steering them toward aesthetically enhanced outputs remains largely unexplored. We

arXiv:2605.31352v1 Announce Type: new Abstract: Robotics manipulation usually assumes that the shape and pose of the object are known to the robot prior to motion planning. However, precise geometric

DeepAgents are AI systems designed to handle complex tasks through advanced reasoning and planning capabilities. The post outlines the key features that enable DeepAgents to excel at complicated probl

arXiv:2605.31503v1 Announce Type: new Abstract: Humans easily determine which color belongs to which shape in multi-object scenes, an ability known as concept binding. Vision-language embedding models

I find debates over whether companies find AI useful to be odd at this point I talk to leadership teams at lots of big firms, and it is pretty universal that they are getting obvious and real value. T

arXiv:2605.30596v1 Announce Type: new Abstract: Independently trained neural models typically converge to incompatible latent representations, creating a fundamental barrier to highly modular AI syste

arXiv:2605.31508v1 Announce Type: new Abstract: Video Object-Centric Learning (OCL) aims to represent objects as extit{slot} vectors and maintain their consistency across frames. Slot-Slot Contrastive

arXiv:2605.31304v1 Announce Type: cross Abstract: Deep neural networks (DNNs) are widely used, but interpreting what they actually learn remains difficult. A major obstacle is that individual neurons

arXiv:2605.30622v1 Announce Type: cross Abstract: Open radio access network (O-RAN) architectures enable near real-time, software-driven control of network slicing through programmable xApps deployed

Just saving this here to document a story and as a self reflection on whether AI is really making me more productive Yesterday morning I found a way to complete the new HVM approach, that is much fast

'Just use AI' can be useful (I call it The Crowd in my informal framework I gave in my post below), but you also need a Lab where people can go with their ideas and Leadership to make decisions about

arXiv:2605.31099v1 Announce Type: cross Abstract: Science news is an important medium to communicate discoveries between the research communities and the public. Yet, most metrics for generated or sum

Latest latentspace pod is excellent. @EthanHe_42 really gets it and lays out a lot of the thinking that led us to Flipbook and how to think about the future of generative UI agents 🤝 video gen 🤝 users

arXiv:2510.00419v2 Announce Type: replace Abstract: Zeroth-order optimizers have recently emerged as an attractive approach for fine-tuning large language models (LLMs), as they avoid backpropagation

arXiv:2410.19153v2 Announce Type: replace Abstract: In neuroscience, numerous studies conduct sensory or behavioral experiments under multiple conditions to acquire neural responses in the form of hig

arXiv:2605.30432v1 Announce Type: cross Abstract: Social systems consist of networks of individuals who influence one another through social interactions. Studying how processes evolve on these networ

arXiv:2605.31276v1 Announce Type: new Abstract: Accurately modeling crop response to Nitrogen (N) fertilization is a fundamental challenge in precision agriculture, as it impacts both economic returns

arXiv:2605.30812v1 Announce Type: new Abstract: Accurately modeling the macroscopic dynamics of high-dimensional microscopic systems is of broad interest across the sciences. Many data-driven approach