tutorials

Probing the 3D Object-Level Understanding of Pre-Trained Detection Transformers

arXiv:2608.01495v1 Announce Type: new Abstract: Detection transformer models, including DETR and its extensions, learn to output a set of object-level embeddings that can be simultaneously decoded int

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Randomized Algorithms for Learning Partitions with Near Optimal Query Complexity in Constant Rounds

DGX agent

arXiv:2608.02176v1 Announce Type: cross Abstract: We study the round complexity of learning a hidden partition P of an n-element universe using PAIR queries: PAIR(x,y) tells us whether x and y belong

tutorialsarxiv-cs-lg

4 Aug 2026

Restore Text First, Enhance Image Later: Two-Stage Scene Text Image Super-Resolution with Glyph Structure Guidance

arXiv:2510.21590v3 Announce Type: replace Abstract: Current image super-resolution methods show strong performance on natural images but distort text, creating a fundamental trade-off between image qu

Scikit-fingerprints: Python library for scikit-learn compatible molecular fingerprints and chemoinformatics

arXiv:2608.02027v1 Announce Type: new Abstract: We present scikit-fingerprints, a comprehensive, fully scikit-learn compatible library for molecular machine learning in Python, based on RDKit. Molecul

UniqueSplat: View-conditioned 3D Gaussian Splatting for Generalizable 3D Reconstruction

arXiv:2608.02145v1 Announce Type: new Abstract: In this paper, we propose UniqueSplat, a view-conditioned feed-forward 3D Gaussian Splatting model to reconstruct customized 3D radiance fields for each

Unleashing the Power of Text: Text-Guided Flow Matching for Image Fusion under Complex Degradations

arXiv:2608.00530v1 Announce Type: new Abstract: Infrared-visible image fusion under realistic degradation scenarios is a challenging task, as degradations not only cause a loss of reliable modality-sp

When Differential Privacy Meets Wireless Federated Learning: An Improved Analysis for Privacy and Convergence

arXiv:2603.19040v2 Announce Type: replace Abstract: Differentially private wireless federated learning (DPWFL) is a promising framework for protecting sensitive user data. However, foundational questi

A user's guide to PINNs in geometric analysis: lessons from the asymptotic Plateau problem

arXiv:2607.28733v1 Announce Type: cross Abstract: This proceedings contribution elaborates on the findings of arXiv:2605.26234v2: a joint work with Marco Usula, where we introduced a machine learning

Contrastive Learning for Image Complexity Representation

arXiv:2408.03230v2 Announce Type: replace Abstract: Quantifying and evaluating image complexity can be instrumental in enhancing the performance of various computer vision tasks. Supervised learning c

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

DualDiT: A Conditional Dual-Output Diffusion Transformer for Joint OCT Image and Segmentation Mask Generation

arXiv:2607.29337v1 Announce Type: cross Abstract: Background and Objective: Generating realistic medical images with anatomically accurate segmentation masks helps address the shortage of annotated da

Fast Feature Field (ext{F}^3): A Predictive Representation of Events

arXiv:2509.25146v2 Announce Type: replace-cross Abstract: This paper develops a mathematical argument and algorithms for building representations of data from event-based cameras, that we call Fast Fe

FBFM: A Training-Free Asynchronous Feedback Mechanism for Flow-Matching in World-Action Models Execution

arXiv:2607.29235v1 Announce Type: cross Abstract: Although world-action models (WAMs) enhance long-horizon robot control by predicting visual evolution before acting, long-horizon reliability demands

Group-wise Supervision with Focal-Dice Loss for Long-Tailed Indoor Semantic Occupancy Prediction

arXiv:2607.28935v1 Announce Type: new Abstract: Recently, 3D semantic occupancy prediction has garnered increasing attention for understanding the indoor scene. However, unlike structured outdoor envi

'I ran my own benchmarks on it' seems to be pretty common comment around here. How about dedicating a thread for this and sharing?

Of course, the concern is that in the end, this thread will be fed into the models' training data, but I feel benchmarking isn't so open and very fragmented. submitted by /u/jinnyjuice [link] [comment

tutorialsr-localllama

Maximum Entropy Behavior Exploration for Sim2Real Zero-Shot Reinforcement Learning

arXiv:2603.25464v2 Announce Type: replace-cross Abstract: Zero-shot reinforcement learning (RL) algorithms aim to learn a family of policies from a reward-free dataset, and recover optimal policies fo

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation

arXiv:2607.29180v1 Announce Type: cross Abstract: Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to

MOSAIC: Masked Outsourcing of Secure AI Computations

arXiv:2607.29221v1 Announce Type: cross Abstract: We address the challenge of securely and efficiently outsourcing AI computations from a trusted but computationally weak client to an untrusted but po

PaletteID: Prototype-Composed Semantic Identifiers for Multimodal CTR Prediction

arXiv:2607.29000v1 Announce Type: cross Abstract: Multimodal information can improve the accuracy of click-through rate (CTR) prediction and effectively alleviate item cold-start and long-tail problem

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces

arXiv:2308.08794v4 Announce Type: replace Abstract: Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems. For instance, i

To Facilitate or not to Facilitate: Human and LLM Facilitator Tendencies in Online Discussions

arXiv:2607.28643v1 Announce Type: cross Abstract: Automating facilitation in online discussions is a long-standing social concern given the increasing time we spend on online spaces and the failure of

TOOD: Task-Aware Out-of-Distribution Score Calibration for Continual Learners

arXiv:2607.29592v1 Announce Type: new Abstract: The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly impor

TransMem: Transforming Hidden States into Memory for Large Language Models

arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting

UniPolymer: A Unified Framework for Property Prediction, Structure Recommendation, and Evaluation in Polyimide Design

arXiv:2607.29256v1 Announce Type: new Abstract: Designing polyimide structures with specific glass transition temperatures (Tg) is highly challenging. Existing methods primarily focus on target-condit

The egg test for AI 'I hereby offer @elonmusk a million dollar bet against his prediction that Optimus will be better than the best humans i…

The egg test for AI 'I hereby offer @elonmusk a million dollar bet against his prediction that Optimus will be better than the best humans in surgery by the end of the decade.' ~ @GaryMarcus Haha. I'm

tutorialsgary-marcus--x

2 Aug 2026

Kimi K3 has set a new bar for OSS model intelligence! 2.8T params, 1M context, OpenAI-compatible API. Complete guide to running Kimi K3 on T…

Kimi K3 has set a new bar for OSS model intelligence! 2.8T params, 1M context, OpenAI-compatible API. Complete guide to running Kimi K3 on Together AI 👇 👏👏 @Kimi_Moonshot 👏👏 https://www.together.ai/bl

tutorialstogether-ai--x

Kimi K3: The Complete Developer Guide

tutorialstogether-ai-blog

**Kimi K3 is Moonshot AI’s 2.8‑trillion‑parameter open‑weight language model—the largest ever released—designed for frontier tasks such as long‑horizon coding and deep reasoning.** Its architecture us

Our Twitch streams with @Cohere_Labs are #1 in the tech category⚡️ Cohere Labs' free ML Summer School series has brought together viewers fr…

Our Twitch streams with @Cohere_Labs are #1 in the tech category⚡️ Cohere Labs' free ML Summer School series has brought together viewers from 20+ countries to learn about everything from NLP in LLMs

tutorialscohere--x

There's no 'one weird trick” for prompting Krea 2 art styles—just many guidelines [WF included]

tutorialsr-stablediffusion

TLDR: There is no one prompting trick that will result in Krea 2 Turbo giving you exactly the style you want and across the whole image. Instead, if you are trying to achieve styles without the use of

AuricularWorld: Hierarchical Action-Guided World Modeling for Fine-Grained Auricular Structure Segmentation from CT Scans

arXiv:2607.28487v1 Announce Type: new Abstract: Fine-grained segmentation of auricular structures in CT is challenging because the ear occupies a small image region, cartilage boundaries are highly ir

AutoPref: Automatic Discovery of Task-Specific Preference Objectives for Neural Combinatorial Optimization

arXiv:2607.27953v1 Announce Type: new Abstract: Combinatorial optimization problems (COPs) underpin many real-world decisions, but their exponentially large search spaces make high-quality solutions c

Backbone-Agnostic Stochastic Perturbation Learning for End-to-End Real-World Image Dehazing

arXiv:2607.11623v3 Announce Type: replace Abstract: Real-world paired image dehazing remains challenging because haze degradation is spatially non-uniform, illumination-dependent, and physically ambig

Bridging the Gap in Ophthalmic AI: MM-Retinal-Reason Dataset and OphthaReason Model toward Dynamic Multimodal Reasoning

arXiv:2508.16129v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have recently demonstrated remarkable reasoning abilities with reinforcement learning paradigm. Although se

Can Large Language Models Execute Parent Orders?

arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution

CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising

arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving

Chatgpt may have saved my life

I got a fever and cough and assumed that this is some viral infection that will just go away on its own. I wear a Fitbit watch which measures my heart rate. Just out of curiosity I posted my symptoms

tutorialsr-chatgpt

Deep R Programming

arXiv:2301.01188v5 Announce Type: replace-cross Abstract: Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambiti

Dynamically Scaled Activation Steering

arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat

Enhancing Scene Transition Awareness in Video Generation via Post-Training

arXiv:2507.18046v2 Announce Type: replace Abstract: Recent advances in AI-generated video have shown strong performance on text-to-video tasks, particularly for short clips depicting a single scene. H

FedOGL: Combating Catastrophic Forgetting in Federated Open-World Multimodal Graph Learning

arXiv:2607.27665v1 Announce Type: new Abstract: Federated graph learning enables collaborative training over decentralized graph data without sharing raw graph information. As such risks evolve, clien

Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently

arXiv:2607.28571v1 Announce Type: new Abstract: Operational Earth observation increasingly calls for answering queries such as ``find the image pairs where a new building appeared.'' This means search

FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection

arXiv:2607.27969v1 Announce Type: new Abstract: Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at

Guarding Organizations Against Malware Risk: A Novel Graph-Based Malware Detection Method

arXiv:2607.26634v1 Announce Type: cross Abstract: Organizational digitalization expands cybersecurity risks, making cybersecurity an increasingly important research area in Information Systems (IS). A

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model

arXiv:2607.10285v2 Announce Type: replace Abstract: We study how unsupervised autoencoders trained on microscopic spin configurations from the Ising model learn macroscopic, theory-relevant variables

Isolating to Harness: Cross-Division Distillation for Fully Unsupervised Anomaly Detection

arXiv:2508.18007v2 Announce Type: replace Abstract: Fully Unsupervised Anomaly Detection (FUAD) addresses the practical scenario where training data is contaminated with unlabeled anomalies. This sett

Latent Matters: Learning Deep State-Space Models

arXiv:2602.23050v2 Announce Type: replace Abstract: Deep state-space models (DSSMs) enable temporal predictions by learning the underlying dynamics of observed sequence data. They are often trained by

Learning to Detect Cyber Attacks: Neural Anomaly Detection for Cybersecurity with Theoretical Insights

arXiv:2409.08521v2 Announce Type: replace-cross Abstract: In cybersecurity practice, new forms of cyberattacks continuously emerge, deliberately designed to evade defense systems that rely on previous

Learning to Understand Body Language from Flight through Robust 3D Avatar Placing

arXiv:2607.27865v1 Announce Type: new Abstract: Perceiving human motion and intent at long range is a prerequisite for socially intelligent aerial robots, yet the data to learn it barely exists. We in