tutorials

Don't Fix the Basis -- Learn It: Spectral Representation with Adaptive Basis Learning for PDEs

arXiv:2605.10451v1 Announce Type: new Abstract: Spectral neural operators achieve strong performance for PDE learning, but rely on fixed global bases that limit their ability to represent spatially he

Tutorials

DRIFT: Drift-Resilient Invariant-Feature Transformer for DGA Detection

DGX agent

arXiv:2605.10436v1 Announce Type: cross Abstract: Domain Generation Algorithms (DGAs) evolve continuously to evade botnet detection, posing a persistent challenge for dependable network defense. While

tutorialsarxiv-cs-lg

12 May 2026

Dual Tuning for Reasoning Efficacy-Driven Data Curation in Multimodal LLM Training

arXiv:2603.04415v2 Announce Type: replace Abstract: Reasoning post-training improves Large Language Models (LLMs) on complex tasks such as mathematics and coding, but its benefits across diverse multi

Dungeons & Desktops: Building a procedurally generated roguelike with GitHub Copilot CLI

Learn how one Hubber used GitHub Copilot CLI to build an extension that turns any codebase into a unique, roguelike dungeon. The post Dungeons & Desktops: Building a procedurally generated roguelike w

tutorialsgithub-ai-blog

EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution

arXiv:2505.05209v4 Announce Type: replace Abstract: Utilizing pre-trained Text-to-Image (T2I) diffusion models to guide Blind Super-Resolution (BSR) has become a predominant approach in the field. Whi

Efficient Estimation of Kernel Surrogate Models for Task Attribution

arXiv:2602.03783v2 Announce Type: replace-cross Abstract: Modern AI agents such as large language models are trained on diverse tasks -- translation, code generation, mathematical reasoning, and text

EFGCL: Learning Dynamic Motion through Spotting-Inspired External Force Guided Curriculum Learning

arXiv:2605.10063v1 Announce Type: new Abstract: Learning dynamic whole-body motions for legged robots through reinforcement learning (RL) remains challenging due to the high risk of failure, which mak

tutorialsarxiv-cs-ro

Emergent Semantic Role Understanding in Language Models

arXiv:2605.09187v1 Announce Type: new Abstract: Understanding how linguistic structure emerges in language models is central to interpreting what these systems learn from data and how much supervision

Falcon 9’s first stage lands on the Of Course I Still Love You droneship

SpaceX successfully landed the Falcon 9 first stage on the 'Of Course I Still Love You' autonomous droneship, demonstrating the company's reusable rocket technology and land-based recovery capability.

tutorialselon-musk--x

First, Do No Harm: AI Supervisor Scaffolds Novice Growth in Counselor Education

arXiv:2508.09042v3 Announce Type: replace Abstract: The most dangerous mistakes a novice counselor makes are not the obvious ones: they are utterances that sound caring while quietly violating profess

From Regression to Inference: Meta-Learning Predictors for Neural Architecture Search

arXiv:2605.09290v1 Announce Type: new Abstract: Prediction-based approaches are widely used in neural architecture search (NAS), where a predictor estimates the performance of candidate architectures

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

Generative Experiences for Digital Mental Health Interventions: Evidence from a Randomized Study

arXiv:2604.07558v2 Announce Type: replace-cross Abstract: Digital mental health (DMH) tools have extensively explored personalization of interventions to users' needs and contexts. However, this perso

GESR: A Genetic Programming-Based Symbolic Regression Method with Gene Editing

arXiv:2605.10685v1 Announce Type: new Abstract: Mathematical formulas serve as a language through which humans communicate with nature. Discovering mathematical laws from scientific data to describe n

HairGPT: Strand-as-Language Autoregressive Modeling for Realistic 3D Hairstyle Synthesis

arXiv:2605.08824v1 Announce Type: cross Abstract: Hair is a rich medium of visual and cultural expression, yet its digital modeling remains challenging due to the duality of fluidity and structure. Ma

Hierarchical Multi-Fidelity Learning for Predicting Three-Dimensional Flame Wrinkling and Turbulent Burning Velocity

arXiv:2605.08232v1 Announce Type: new Abstract: High-fidelity experimental characterization of turbulent premixed flames remains limited by the cost and complexity of advanced diagnostics, particularl

How to achieve truly serverless GPUs

This article explains how to implement and deploy GPU workloads in a truly serverless architecture, likely covering Modal's approach to abstracting away infrastructure management while providing GPU c

tutorialsmodal-blog

How to Convert Your ComfyUI Workflow into an APP Mode Workflow App Mode is a new way to view and run any ComfyUI workflow. When you enter Ap…

How to Convert Your ComfyUI Workflow into an APP Mode Workflow App Mode is a new way to view and run any ComfyUI workflow. When you enter App Mode, the node graph disappears and is replaced by a clean

tutorialscomfyui--x

HPGN: Hybrid Priors-Guided Network for Compressed Low-Light Image Enhancement

arXiv:2504.02373v3 Announce Type: replace-cross Abstract: In practical applications, low-light images are often compressed for efficient storage and transmission. Most existing methods disregard compr

Improving Generative Adversarial Networks with Self-Distillation

arXiv:2605.08577v1 Announce Type: new Abstract: In modern GANs, maintaining an Exponential Moving Average (EMA) of the generator's weights is a standard practice, as such an averaged model consistentl

Inductive Entity Representations from Text via Link Prediction

arXiv:2010.03496v4 Announce Type: replace-cross Abstract: Knowledge Graphs (KG) are of vital importance for multiple applications on the web, including information retrieval, recommender systems, and

Interactive Benchmarks

arXiv:2603.04737v2 Announce Type: replace Abstract: Existing reasoning evaluation paradigms suffer from different limitations: fixed benchmarks are increasingly saturated and vulnerable to contaminati

IntroLM: Introspective Language Models via Prefilling-Time Self-Evaluation

arXiv:2601.03511v2 Announce Type: replace-cross Abstract: A major challenge for the operation of large language models (LLMs) is how to predict whether a specific LLM will produce sufficiently high-qu

Learn the system

This article likely provides guidance on understanding how AI systems work, their underlying mechanisms, and best practices for effectively using or interacting with AI tools. Based on Ben's Bites' fo

tutorialsben-s-bites

Learning from Acceptance: Cumulative Regret in the Game of Coding

arXiv:2605.09754v1 Announce Type: cross Abstract: Classical coding-theoretic guarantees often rely on trust assumptions, such as requiring sufficiently many honest nodes compared with adversarial ones

Learning Pure Quantum States in Any Dimension (Almost) Without Regret

arXiv:2605.09019v1 Announce Type: cross Abstract: We extend quantum state tomography with minimal cumulative disturbance, first investigated in [arXiv:2406.18370], to arbitrary finite-dimensional pure

Learning to Learn the Macroscopic Fundamental Diagram using Physics-Informed and meta Machine Learning techniques

arXiv:2508.14137v2 Announce Type: replace Abstract: The Macroscopic Fundamental Diagram is a popular tool used to describe traffic dynamics in an aggregated way, with applications ranging from traffic

Learning Unified Representations of Normalcy for Time Series Anomaly Detection

arXiv:2605.09685v1 Announce Type: cross Abstract: The core challenge in unsupervised anomaly detection is identifying abnormal patterns without prior knowledge of their characteristics. While existing

LLM-Augmented Chemical Synthesis and Design Decision Programs

arXiv:2505.07027v2 Announce Type: replace Abstract: Retrosynthesis, the process of breaking down a target molecule into simpler precursors through a series of valid reactions, stands at the core of or

Markerless Head Tracking for Accurate and Accessible Neuronavigation

arXiv:2602.07052v2 Announce Type: replace Abstract: Neuronavigation is widely used in biomedical research and interventions to guide the precise placement of instruments around the head to support pro

MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training

arXiv:2602.02494v2 Announce Type: replace Abstract: Clinical brain-to-text interfaces are designed for paralysed patients who cannot provide extensive training recordings. Pre-training improves data-e

MUR: Momentum Uncertainty guided Reasoning

arXiv:2507.14958v2 Announce Type: replace Abstract: Current models have achieved impressive performance on reasoning-intensive tasks, yet optimizing their reasoning efficiency remains an open challeng

NICE FACT: Diagnosing and Calibrating VLMs in Quantitative Reasoning for Kinematic Physics

arXiv:2605.08452v1 Announce Type: new Abstract: The ability to derive precise spatial and physical insights is a cornerstone of vision-language models (VLMs), yet their poor performances in related sp

One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification

arXiv:2605.10179v1 Announce Type: cross Abstract: Neural Flows efficiently model irregular multivariate time series by directly learning ODE solution trajectories with neural networks, bypassing step-

Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems

arXiv:2602.02045v2 Announce Type: replace Abstract: Diffusion models have emerged as powerful learned priors for Bayesian inverse problems (BIPs). Diffusion-based solvers rely on a presumed likelihood

PaMoSplat: Part-Aware Motion-Guided Gaussian Splatting for Dynamic Scene Reconstruction

arXiv:2605.10307v1 Announce Type: new Abstract: Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based metho

Portable Active Learning for Object Detection

arXiv:2605.10349v1 Announce Type: cross Abstract: Annotating bounding boxes is costly and limits the scalability of object detection. This challenge is compounded by the need to preserve high accuracy

Predicting 3D structure by latent posterior sampling

arXiv:2605.10830v1 Announce Type: new Abstract: The remarkable achievements of both generative models of 2D images and neural field representations for 3D scenes present a compelling opportunity to in

PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models

arXiv:2605.10925v1 Announce Type: new Abstract: Large-scale pretraining has made Vision-Language-Action (VLA) models promising foundations for generalist robot manipulation, yet adapting them to downs

tutorialsarxiv-cs-ro

PruneTIR: Inference-Time Tool Call Pruning for Effective yet Efficient Tool-Integrated Reasoning

arXiv:2605.09931v1 Announce Type: cross Abstract: Tool-integrated reasoning (TIR) enables large language models (LLMs) to enhance their capabilities by interacting with external tools, such as code in

Quantile Geometry Regularization for Distributional Reinforcement Learning

arXiv:2605.08182v1 Announce Type: cross Abstract: Quantile-based distributional reinforcement learning methods learn return distributions through sampled quantile regression, but their bootstrapped ta

Quoting Mo Bitar

Now, if your CEO has never heard the phrase Ralph Loop, oh man, you are less than 30 days away from your next promotion. I'm not even exaggerating. Walk into his office, close the door, and say, hey c

tutorialssimon-willison

Reasoning Trajectories for Socratic Debugging of Student Code: From Misconceptions to Contradictions and Updated Beliefs

arXiv:2511.00371v2 Announce Type: replace Abstract: In Socratic debugging, instructors guide students towards identifying and fixing a bug on their own, instead of providing the bug fix directly. Most

Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation

arXiv:2502.06818v3 Announce Type: replace Abstract: Recent works modify CLIP to perform open-vocabulary semantic segmentation in a training-free manner (TF-OVSS). In vanilla CLIP, patch-wise image rep

SE-Bench: Benchmarking Self-Evolution with Knowledge Internalization

arXiv:2602.04811v2 Announce Type: replace-cross Abstract: True self-evolution requires agents to act as lifelong learners that internalize novel experiences to solve future problems. However, rigorous

Sign up if you're in LA!

Sign up if you're in LA! The last AI Agents Happy Hour was so fun, @jvedi and I are going to do it again. This time, co-hosted by @pinecone! We want to see what you're building and learn from your exp

tutorialspinecone--x

Signal from Structure: Exploiting Submodular Upper Bounds in Generative Flow Networks

arXiv:2601.21061v2 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets; GFNs) are a class of generative models that learn to sample compositional objects proportionally to their a pri

Sound on! This is pretty cool :D

tutorialsjeremy-howard--x

Sound on! This is pretty cool :D SolveIt is already an amazing environment for learning and exploring any topic, or for development/writing etc. But add in real-time conversational interaction too jus