Search: “tutorials”

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning

arXiv:2604.10455v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled promising progress in diagnosis prediction from electronic health records (EHRs). However,

tutorialsarxiv-cs-cl

Tutorials

Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation

DGX agent

arXiv:2510.10925v2 Announce Type: replace-cross Abstract: Training student models on synthetic data generated by strong teacher models is a promising way to distilling the capabilities of teachers. Ho

tutorialsarxiv-cs-cl

14 Apr 2026

GIF: A Conditional Multimodal Generative Framework for IR Drop Imaging in Chip Layouts

arXiv:2604.09999v1 Announce Type: new Abstract: IR drop analysis is essential in physical chip design to ensure the power integrity of on-chip power delivery networks. Traditional Electronic Design Au

Harnessing Photonics for Machine Intelligence

arXiv:2604.10841v1 Announce Type: cross Abstract: The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivatin

HECTOR: Human-centric Hierarchical Coordination and Supervision of Robotic Fleets under Continual Temporal Tasks

arXiv:2604.10892v1 Announce Type: new Abstract: Robotic fleets can be extremely efficient when working concurrently and collaboratively, e.g., for delivery, surveillance, search and rescue. However, i

tutorialsarxiv-cs-ro

Hey, does anyone know how to make it generate more detailed images?

This r/ChatGPT post is a community discussion where users share tips on prompting ChatGPT's image generation (via DALL·E) to produce more detailed outputs. The consensus across the community is that c

HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement

arXiv:2604.10675v1 Announce Type: new Abstract: We propose a method to learn explicit, class-conditioned spatial priors for object placement in natural scenes by distilling the implicit placement know

Hierarchical Textual Knowledge for Enhanced Image Clustering

arXiv:2604.11144v1 Announce Type: cross Abstract: Image clustering aims to group images in an unsupervised fashion. Traditional methods focus on knowledge from visual space, making it difficult to dis

tutorialsarxiv-cs-cl

HO-Flow: Generalizable Hand-Object Interaction Generation with Latent Flow Matching

arXiv:2604.10836v1 Announce Type: new Abstract: Generating realistic 3D hand-object interactions (HOI) is a fundamental challenge in computer vision and robotics, requiring both temporal coherence and

How to Bridge the Sim-to-Real Gap in Digital Twin-Aided Telecommunication Networks

arXiv:2507.07067v3 Announce Type: replace-cross Abstract: Training effective artificial intelligence models for telecommunications is challenging due to the scarcity of deployment-specific data. Real

How to Design a Compact High-Throughput Video Camera?

arXiv:2604.10619v1 Announce Type: new Abstract: High throughput video acquisition is a challenging problem and has been drawing increasing attention. Existing high throughput imaging systems splice hu

How to fix ChatGPT lag and freezing

This Reddit post likely covers common troubleshooting steps for resolving performance issues with ChatGPT, such as clearing browser cache and cookies, disabling browser extensions, and starting a new

How to get GPT to stop using the last generated image as a seed.

This Reddit post addresses a common ChatGPT image generation behavior where the model automatically carries over the seed from a previously generated image, causing new generations to visually resembl

How to Spin an Object: First, Get the Shape Right

arXiv:2412.10273v3 Announce Type: replace Abstract: Image-to-3D models increasingly rely on hierarchical generation to disentangle geometry and texture. However, the design choices underlying these tw

Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning

arXiv:2507.00748v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) perform well in single-image visual grounding but struggle with real-world tasks that demand cross-image re

INCRT: An Incremental Transformer That Determines Its Own Architecture

arXiv:2604.10703v1 Announce Type: new Abstract: Transformer architectures are designed by trial and error: the number of attention heads, the depth, and the head size are fixed before training begins,

Interpretable Alzheimer's Diagnosis via Multimodal Fusion of Regional Brain Experts

arXiv:2512.10966v2 Announce Type: replace-cross Abstract: Accurate and early diagnosis of Alzheimer's disease (AD) is critical for effective intervention and requires integrating complementary informa

I've spent years building AI prompt systems for real investment research with real money behind it. Here are the 5 failure modes I see investors make and how to fix every one of them.

A Reddit post from r/ChatGPT in which a practitioner claims experience building AI prompt systems for real-world investment research shares five common mistakes investors make when using AI for financ

KL Divergence Between Gaussians: A Step-by-Step Derivation for the Variational Autoencoder Objective

arXiv:2604.11744v1 Announce Type: new Abstract: Kullback-Leibler (KL) divergence is a fundamental concept in information theory that quantifies the discrepancy between two probability distributions. I

Language Reconstruction with Brain Predictive Coding from fMRI Data

arXiv:2405.11597v2 Announce Type: replace-cross Abstract: Many recent studies have shown that the perception of speech can be decoded from brain signals and subsequently reconstructed as continuous la

Learning and Enforcing Context-Sensitive Control for LLMs

arXiv:2604.10667v1 Announce Type: cross Abstract: Controlling the output of Large Language Models (LLMs) through context-sensitive constraints has emerged as a promising approach to overcome the limit

Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories

arXiv:2604.11365v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) has been widely used for automated reasoning data exploration, but current supervision extraction methods remain ineffici

Learning Long-term Motion Embeddings for Efficient Kinematics Generation

arXiv:2604.11737v1 Announce Type: new Abstract: Understanding and predicting motion is a fundamental component of visual intelligence. Although modern video models exhibit strong comprehension of scen

Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment

arXiv:2604.11306v1 Announce Type: cross Abstract: Robots must verbalize their past experiences when users ask 'Where did you put my keys?' or 'Why did the task fail?' Yet maintaining life-long episodi

LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape

arXiv:2604.02600v2 Announce Type: replace-cross Abstract: Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This r

MetaPrompting - The Art Of Teaching LLMs How to Prompt

tutorialsr-stablediffusion

This Reddit post from r/StableDiffusion discusses **metaprompting** — the practice of using LLMs to generate, refine, and optimize Stable Diffusion image prompts, rather than crafting them manually fr

MetroGS: Efficient and Stable Reconstruction of Geometrically Accurate High-Fidelity Large-Scale Scenes

arXiv:2511.19172v4 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to eff

MorphoFlow: Sparse-Supervised Generative Shape Modeling with Adaptive Latent Relevance

arXiv:2604.11636v1 Announce Type: new Abstract: Statistical shape modeling (SSM) is central to population level analysis of anatomical variability, yet most existing approaches rely on densely annotat

Multimodal Diffusion Forcing for Forceful Manipulation

arXiv:2511.04812v2 Announce Type: replace-cross Abstract: Given a dataset of expert trajectories, standard imitation learning approaches typically learn a direct mapping from observations (e.g., RGB i

Neural Surface Reconstruction from Sparse Views Using Epipolar Geometry

arXiv:2406.04301v3 Announce Type: replace Abstract: Reconstructing accurate surfaces from sparse multi-view images remains challenging due to severe geometric ambiguity and occlusions. Existing genera

NeuroPath: Practically Adopting Motor Imagery Decoding through EEG Signals

arXiv:2604.09654v1 Announce Type: cross Abstract: Motor Imagery (MI) is an emerging Brain-Computer Interface (BCI) paradigm where a person imagines body movements without physical action. By decoding

Not Your Stereo-Typical Estimator: Combining Vision and Language for Volume Perception

arXiv:2604.09886v1 Announce Type: cross Abstract: Accurate volume estimation of objects from visual data is a long-standing challenge in computer vision with significant applications in robotics, logi

🔐 One deployment, isolated data per user. Add custom auth so every user gets their own scoped threads, runs, and conversation history — wit…

tutorialsharrison-chase--x

🔐 One deployment, isolated data per user. Add custom auth so every user gets their own scoped threads, runs, and conversation history — with per-user data isolation and role-based access using any aut

PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation

arXiv:2604.09701v1 Announce Type: new Abstract: Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recy

Polymarket is auditing its Builders Program, which gives up to $2.5M in grants, after concerns that some participating startups are facilitating insider trading (Michael Roddan/The Information)

Michael Roddan / The Information: Polymarket is auditing its Builders Program, which gives up to $2.5M in grants, after concerns that some participating startups are facilitating insider trading — Pol

tutorialstechmeme

Predicting integers from continuous parameters

arXiv:2602.10751v2 Announce Type: replace Abstract: We study the problem of predicting numeric labels that are constrained to the integers or to a subrange of the integers. For example, the number of

Preventing Latent Rehearsal Decay in Online Continual SSL with SOLAR

arXiv:2604.10586v1 Announce Type: cross Abstract: This paper explores Online Continual Self-Supervised Learning (OCSSL), a scenario in which models learn from continuous streams of unlabeled, non-stat

Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching

arXiv:2604.11178v1 Announce Type: cross Abstract: Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neuro

Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning

arXiv:2604.11112v1 Announce Type: cross Abstract: Class-incremental learning (CIL) aims to continuously accumulate knowledge from a stream of tasks and construct a unified classifier over all seen cla

RAM guide: What model combinations actually fit on common Macs

This r/ollama community guide provides a practical breakdown of which AI language models (and combinations of models) can realistically fit within the unified memory constraints of common Apple Silico

tutorialsr-ollama

Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning

arXiv:2604.11407v1 Announce Type: cross Abstract: We revisit retrieval-augmented generation (RAG) by embedding retrieval control directly into generation. Instead of treating retrieval as an external

Ro-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation

arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en

tutorialsarxiv-cs-ro

Smart Paste: Automatically Fixing Copy/Paste for Google Developers

arXiv:2510.03843v4 Announce Type: replace-cross Abstract: Manually editing pasted code is a long-standing developer pain point. In internal software development at Google, we observe that code is past

Specificity-aware reinforcement learning for fine-grained open-world classification

arXiv:2603.03197v3 Announce Type: replace Abstract: Classifying fine-grained visual concepts under open-world settings, i.e., without a predefined label set, demands models to be both accurate and spe

Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation

arXiv:2604.10071v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities yet continue to suffer from hallucination, where generated

Structured State-Space Regularization for Compact and Generation-Friendly Image Tokenization

arXiv:2604.11089v1 Announce Type: new Abstract: Image tokenizers are central to modern vision models as they often operate in latent spaces. An ideal latent space must be simultaneously compact and ge

SVSR: A Self-Verification and Self-Rectification Paradigm for Multimodal Reasoning

arXiv:2604.10228v1 Announce Type: new Abstract: Current multimodal models often suffer from shallow reasoning, leading to errors caused by incomplete or inconsistent thought processes. To address this

Symmetry-Aware Generative Modeling through Learned Canonicalization

arXiv:2501.07773v3 Announce Type: replace Abstract: Generative modeling of symmetric densities has a range of applications in AI for science, from drug discovery to physics simulations. The existing g