Ai Human Computer Interaction | AI Final Year Project Report

Complete Technical Paper Content — Ai Human Computer Interaction

1. Executive Abstract, Problem Formulation & Background

Awesome Human-AI Interaction Awesome HAI is a collection of academic materials related to the topic of Human-AI interaction. We include both research papers that discuss challenges and opportunities in interaction design with general AI from the Human-Computer Interaction (HCI) perspective and that specifically discuss how advances in Deep Learning can address interactive challenges from the AI perspective. We also include Human-AI Interaction courses from universities worldwide. The collection is maintained by a community of volunteered students, make a pull request if you want to contribute :) Table of Contents Research Papers Courses Research Papers ACM Conference on Human Factors in Computing Systems (CHI) Year Paper 2020 Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI 2020 Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design 2020 What is AI Literacy? Competencies and Design Considerations 2020 Questioning the AI: Informing Design Practices for Explainable AI User Experiences 2020 Mental Models of AI Agents in a Cooperative Game Setting 2020 Reinforcement Learning for the Adaptive Scheduling of Educational Activities 2020 Predicting Mid-Air Interaction Movements and Fatigue Using Deep Reinforcement Learning 2020 Enemy Within: Long-term Motivation Effects of Deep Player Behavior Models for Dynamic Difficulty Adjustment 2020 OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Camera 2020 A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy 2020 Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods 2020 EarBuddy: Enabling On-Face Interaction via Wireless Earbuds 2020 "Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans 2020 Novice-AI Music Co-Creation via AI-Steering Tools for Deep Generative Models 2020 EmoG: Supporting the Sketching of Emotional Expressions for Storyboarding 2020 Affective State Prediction Based on Semi-Supervised Learning from Smartphone Touch Data 2020 Automated Class Discovery and One-Shot Interactions for Acoustic Activity Recognition 2020 Optimizing User Interface Layouts via Gradient Descent 2020 AL: An Adaptive Learning Support System for Argumentation Skills 2020 Studying the Effects of Cognitive Biases in Evaluation of Conversational Agents 2019 Guidelines for Human-AI Interaction 2019 Caring for Vincent: A Chatbot for Self-compassion 2019 Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes 2019 What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents 2019 Metaphoria: An Algorithmic Companion for Metaphor Creation 2019 Implicit Communication of Actionable Information in Human-AI teams 2019 AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness 2019 Designing Theory-Driven User-Centric Explainable AI 2019 Will You Accept an Imperfect AI? Exploring Designs for Adjusting End-user Expectations of AI Systems 2019 ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning 2019 Resilient Chatbots: Repair Strategy Preferences for Conversational Breakdowns 2019 In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound 2019 Beyond Dyadic Interactions: Considering Chatbots as Community Members 2019 An Exploration of Speech-Based Productivity Support in the Car 2019 Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes 2019 SmartEye: Assisting Instant Photo Taking via Integrating User Preference with Deep View Proposal Network 2019 Hands Holding Clues for Object Recognition in Teachable Machines 2019 QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge 2019 Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models 2019 Automation Accuracy Is Good, but High Controllability May Be Better 2018 All Work and No Play? Conversations with a Question-and-Answer Chatbot in the Wild 2018 Cognitive Load Estimation in the Wild 2018 Emotional Dialogue Generation using Image-Grounded Language Models 2018 DeepWriting: Making Digital Ink Editable via Deep Generative Modeling 2018 Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time 2018 RecipeScape: An Interactive Tool for Analyzing Cooking Instructions at Scale 2018 ExtVision: Augmentation of Visual Experiences with Generation of Context Images for a Peripheral Vision Using Deep Neural Network 2018 HindSight: Enhancing Spatial Awareness by Sonifying Detected Objects in Real-Time 360-Degree Video 2018 Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns 2018 Predicting Human Performance in Vertical Menu Selection Using Deep Learning 2018 Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda 2018 Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media 2018 Mapping Machine Learning Advances from HCI Research to Reveal Starting Places for Design Innovation 2018 Analysis and Modeling of Grid Performance on Touchscreen Mobile Devices 2018 “Trust Us”: Mobile Phone Use Patterns Can Predict Individual Trust Propensity 2018 Norms Matter: Contrasting Social Support Around Behavior Change in Online Weight Loss Communities 2017 UX Design Innovation: Challenges for Working with Machine Learning as a Design Material 2017 A New Chatbot for Customer Service on Social Media 2017 Multimodal Classification of Moderated Online Pro-Eating Disorder Content 2017 People with Visual Impairment Training Personal Object Recognizers: Feasibility and Challenges 2016 Augur: Mining Human Behaviors from Fiction to Power Interactive Systems 2016 “Like Having a Really bad PA”: The Gulf between User Expectation and Experience of Conversational Agents ACM User Interface and Software Technology Symposium (UIST) Year Paper 2020 Decoding Surface Touch Typing from Hand-Tracking 2020 MonoEye: Multimodal Human Motion Capture System Using A Single Ultra-Wide Fisheye Camera 2020 DeepFisheye: Near-Surface Multi-Finger Tracking Technology Using Fisheye Camera 2020 Rescribe: Authoring and Automatically Editing Audio Descriptions 2020 C-Face: Continuously Reconstructing Facial Expressions by Deep Learning Contours of the Face with Ear-mounted Miniature Cameras 2020 Interactive Exploration and Refinement of Facial Expression using Manifold Learning 2020 Brain Relevance Feedback for Interactive Image Generation 2020 Predicting Visual Importance Across Graphic Design Types 2020 Back-Hand-Pose: 3D Hand Pose Estimation for a Wrist-worn Camera via Dorsum Deformation Network 2020 Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training 2019 Mallard: Turn the Web into a Contextualized Prototyping nvironment for Machine Learning 2019 Type, Then Correct: Intelligent Text Correction Techniques for Mobile Text Entry Using Neural Networks 2019 Learning Cooperative Personalized Policies from Gaze Data 2018 Ubicoustics: Plug-and-Play Acoustic Activity Recognition 2018 Lip-Interact: Improving Mobile Device Interaction with Silent Speech Commands 2018 The Exploratory Labeling Assistant: Mixed-Initiative Label Curation with Large Document Collections 2018 Adasa: A Conversational In-Vehicle Digital Assistant for Advanced Driver Assistance Features 2017 Everyday Eye Contact Detection Using Unsupervised Gaze Target Discovery 2017 Learning Visual Importance for Graphic Designs and Data Visualizations 2017 Rico: A Mobile App Dataset for Building Data-Driven Design Applications 2016 Interacting with Soli: Exploring Fine-Grained Dynamic Gesture Recognition in the Radio-Frequency Spectrum ACM Annual Meeting of the Intelligent User Interfaces Community (IUI) Year Paper 2019 When People and Algorithms Meet: Assessing User-reported Problems to Inform Support in Intelligent Everyday Applications 2019 What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play 2019 SearchLens: Composing and Capturing Complex User Interests for Exploratory Search 2019 Proactive Information Retrieval by Capturing Search Intent from Primary Task Context 2019 A Review of User Interface Design for Interactive Machine Learning 2019 BigBlueBot: Teaching Strategies for Successful Human-Agent Interactions 2019 The Effect of Explanations and Algorithmic Accuracy on Visual Recommender Systems of Artistic Images 2019 To Explain or not to Explain: the Effects of Personal Characteristics when Explaining Music Recommendations 2018 AlterEgo: A Personalized Wearable Silent Speech Interface 2018 Creative Writing with a Machine in the Loop: Case Studies on Slogans and Stories 2018 Detecting Memory-Based Interaction Obstacles with a Recurrent Neural Model of User Behavior 2018 User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction 2018 Every Little Movement Has a Meaning of Its Own: Using Past Mouse Movements to Predict the Next Interaction 2018 An Active Tangible User Interface Framework for Teaching and Learning Artificial Intelligence ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) Year Paper 2018 Fact or Fiction 2018 Data-Driven Proactive Policy Assurance of Post Quality in Community q&a Sites 2018 By the Community & For the Community: A Deep Learning Approach to Assist Collaborative Editing in Q&A Sites ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/UbiComp) Year Paper 2019 TurnsMap: Enhancing Driving Safety at Intersections with Mobile Crowdsensing and Deep Learning 2019 AdaRF: Adaptive RFID-based Indoor Localization Using Deep Learning Enhanced Holography 2019 Deep Multi-Task Learning Based Urban Air Quality Index Modelling 2018 What Will You Do for the Rest of the Day? An Approach to Continuous Trajectory Prediction 2018 GymCam: Detecting, Recognizing and Tracking Simultaneous Exercises in Unconstrained Scenes 2018 Crowd-AI Camera Sensing in the Real World 2018 DeepType: On-Device Deep Learning for Input Personalization Service with Minimal Privacy Concern 2018 Performance Characterization of Deep Learning Models for Breathing-based Authentication on Resource-Constrained Devices 2018 Online Deep Ensemble Learning for Predicting Citywide Human Mobility 2018 Deep Room Recognition Using Inaudible Echos 2018 SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework 2018 DeActive: Scaling Activity Recognition with Active Deep Learning 2018 Deep ROI-Based Modeling for Urban Human Mobility Prediction 2017 Multimodal Deep Learning for Activity and Context Recognition 2017 RDeepSense: Reliable Deep Mobile Computing Models with Uncertainty Estimations 2017 Mitigating Bystander Privacy Concerns in Egocentric Activity Recognition with Deep Learning and Intentional Image Degradation 2017 Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations 2017 Ensembles of Deep LSTM Learners for Activity Recognition using Wearables 2016 A weakly supervised activity recognition framework for real-time synthetic biology laboratory assistance 2016 SpotGarbage: smartphone app to detect garbage using deep learning ACM International Symposium on Wearable Computers (ISWC) Year Paper 2018 Understanding and improving recurrent networks for human activity recognition by continuous attention 2018 On attention models for human activity recognition 2018 Deepauth: in-situ authentication for smartwatches via deeply learned behavioural biometrics 2017 CNN-based sensor fusion techniques for multimodal human activity recognition 2016 Deep convolutional feature transfer across mobile activity recognition domains, sensor modalities and locations IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE InfoVis, VAST, SciVis) Year Paper 2020 CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization 2020 explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning 2019 DeepVID: Deep Visual Interpretation and Diagnosis for Image Classifiers via Knowledge Distillation 2019 SANVis: Visual Analytics for Understanding Self-Attention Networks 2019 Seq2seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models 2019 Evaluating 'Graphical Perception' with CNNs 2019 InkPlanner: Supporting Prewriting via Intelligent Visual Diagramming 2019 Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations 2018 DQNViz: A Visual Analytics Approach to Understand Deep Q-Networks 2018 Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers 2018 LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks 2018 GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation 2017 ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models Computer Graphics Forum (Proceedings of EuroVis and EuroGraphics) Year Paper 2020 Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning 2020 DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) Year Paper 2018 Achieving Fairness through Adversarial Learning: an Application toRecidivism Prediction Association for the Advancement of Artificial Intelligence (AAAI) Year Paper 2019 Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff 2019 Zero Shot Learning for Code Education:Rubric Sampling with Deep Learning Inference Neural Information Processing Systems (NeurIPS) Year Paper 2019 On the Utility of Learning about Humans for Human-AI Coordination 2015 Deep Knowledge Tracing International Conference on Machine Learning (ICML) Year Paper 2015 Learning Program Embeddings to Propagate Feedback Educational Data Mining (EDM) Year Paper 2015 Tuning Peer Grading Proceedings of the National Academy of Sciences (PNAS) Year Paper 2019 Agency plus automation: Designing artificial intelligence into interactive systems 2019 Scaling up analogical innovation with crowds and AI 2019 Citizen science frontiers: Efficiency, engagement, and serendipitous discovery with human–machine systems Communications of the ACM (CACM) Year Paper 2018 The Challenge of Crafting Intelligible Intelligence Distill Year Paper 2019 AI Safety Needs Social Scientists 2017 Using Artificial Intelligence to Augment Human Intelligence arXiv Year Paper 2020 GNNVis: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks 2017 Machine Teaching: A New Paradigm for Building Machine Learning Systems Courses There are also some awesome course resources discussing Intelligent User Interface/ Human-AI interaction School Course Lecturer Carnegie Mellon University Human-AI Interaction Jeff Bigham and Joseph Seering Carnegie Mellon University Software Engineering for AI-Enabled Systems (SE4AI) Christian Kaestner Aalto University Intelligent User Interfaces Studio Kashyap Todi and Sunjun Kim Penn State University Crowdsourcing & Crowd-AI Systems Kenneth Huang University of Colorado Boulder Human-centered Machine Learning Chenhao Tan Stanford University Designing AI to Cultivate Human Well-Being Jennifer Aaker and Fei-Fei Li Georgia Tech Data and Visual Analytics Columbia University Intelligent Decision Support: History, Paradigms, Applications Lena Mamykina Curators The repo is jointly contributed by researchers from different institutions, please refer to the contributor page . License

Awesome HAI is a collection of academic materials related to the topic of Human-AI interaction.

There are also some awesome course resources discussing Intelligent User Interface/ Human-AI interaction

The repo is jointly contributed by researchers from different institutions, please refer to the contributor page .

oliviazzzu / minimal-embodiment Star 281 A minimal hardware-software architecture giving large language models a closed-loop physical embodiment with self-perception loops. esp32 hci embodied-ai human-ai-interaction large-language-models self-perception Updated Aug 26, 2026 C++

A minimal hardware-software architecture giving large language models a closed-loop physical embodiment with self-perception loops.

PKU-Alignment / ProAgent Star 109 AAAI24(Oral) ProAgent: Building Proactive Cooperative Agents with Large Language Models language-model cooperative human-ai overcooked human-ai-interaction cooperative-ai llm-agent Updated Mar 4, 2025 JavaScript

AAAI24(Oral) ProAgent: Building Proactive Cooperative Agents with Large Language Models

brandeis-machine-learning / awesome-ml-fairness Star 74 Papers and online resources related to machine learning fairness machine-learning awesome papers research-paper fairness fairness-ai fairness-ml trustworthy-machine-learning human-ai-interaction Updated May 11, 2023

ai-swiss / base Star 63 BASE is an open framework and proposed standard for shaping AI through conversation—turning the way you work into a durable, portable method you control across tools and models. markdown cli open-source swiss framework ai mcp governance knowledge-management human-in-the-loop ai-agents vendor-neutral digital-sovereignty local-first human-ai-interaction llm human-ai-collaboration cognitive-sovereignty Updated Oct 29, 2026 JavaScript

BASE is an open framework and proposed standard for shaping AI through conversation—turning the way you work into a durable, portable method you control across tools and models.

BirkhoffG / Explainable-ML-Papers Star 53 A list of research papers of explainable machine learning. machine-learning awesome research paper academic survey human-in-the-loop interpretability human-in-the-loop-machine-learning explanations interpretable-ml explainable-ml xai explainability counterfactual-explanations interpretable-models recourse trustworthy-machine-learning human-ai-interaction Updated Jun 25, 2021

2. Related Work, Literature Survey & Algorithmic Foundations

UKPLab / llm-roleplay Star 51 LLM Roleplay: Simulating Human-Chatbot Interaction python natural-language-processing dataset-generation dialogue-systems conversational-ai chatbot-development human-ai-interaction Updated Aug 22, 2025 Python

lorenz-liu / awesome-hai Star 51 All about human-AI interaction (HCI + AI). human-computer-interaction human-ai-interaction Updated Feb 25, 2024

Stunspot / stunspots-guide-to-ai-systems Star 48 Operational doctrine for practical AI systems design. ai-agents rag ai-engineering human-ai-interaction prompt-engineering ai-governance llmops ai-architecture agentic-systems knowledge-systems llm-systems ai-evals Updated Aug 30, 2026 PowerShell

See-Sol-Lab / ai-companion-time-anchor Star 38 给AI伴侣增强时间感的小器官（电脑端专用） memory emotional-intelligence codex ai-agents claude long-term-memory human-ai-interaction chatgpt llm-agents ai-companion ai-companions claude-code-plugin codex-plugin agent-continuity Updated Oct 13, 2026 Python

nefelibata5136-code / deepseek-harness-digital-life Star 31 基于 DeepSeek Harness 的多数字生命系统 | Multi Digital Life: native agents, independent life workers, durable communication and owner-bound private services. self-hosted multi-agent digital-life digital-persona long-term-memory local-first autonomous-agent ai-agent human-ai-interaction deepseek ai-companion agent-memory persistent-agent long-running-agent deepseek-harness Updated Oct 20, 2026 JavaScript

基于 DeepSeek Harness 的多数字生命系统 | Multi Digital Life: native agents, independent life workers, durable communication and owner-bound private services.

dinesh-git17 / claudehome Sponsor Star 30 An architectural persistence experiment for large language models. Claude’s Home gives an AI time, memory, and place by combining scheduled execution with a durable filesystem, allowing one continuous instance to reflect, create, and evolve across sessions. ai-experiments human-ai-interaction ai-observability llm-architecture experimental-ai ai-persistence Updated Jul 23, 2026 TypeScript

An architectural persistence experiment for large language models. Claude’s Home gives an AI time, memory, and place by combining scheduled execution with a durable filesystem, allowing one continuous instance to reflect, create, and evolve across sessions.

l1veIn / rambledesk Star 28 Generative UI for working with coding agents. Review, annotate, brainstorm, and give feedback through task-specific desktop workbenches. markdown rust image-annotation annotation feedback mcp svelte web-annotation code-review brainstorming human-in-the-loop ai-agents tauri document-review human-ai-interaction visual-feedback generative-ui coding-agents Updated Oct 12, 2026 TypeScript

Generative UI for working with coding agents. Review, annotate, brainstorm, and give feedback through task-specific desktop workbenches.

phillipclapham / neuroweaver Star 27 A work of meta-recursive experiential fiction exploring the boundaries between truth, perception, consciousness, and reality. pattern-recognition personal-development problem-solving collective-intelligence computational-thinking metacognition systems-thinking knowledge-synthesis cognitive-enhancement human-ai-interaction prompt-engineering productivity-enhancement ai-interaction-strategies ai-collaboration learning-frameworks emergent-learning innovation-methods generative-thinking mind-enhancement cognitive-frameworks Updated Apr 2, 2025 HTML

A work of meta-recursive experiential fiction exploring the boundaries between truth, perception, consciousness, and reality.

3. Dataset Ingestion, Preprocessing & Stochastic Augmentations

jorge-martinez-gil / ci-component Star 24 Component for Collaborative Intelligence within the project AIREDGIO5.0 collaborative-intelligence human-ai-teaming human-ai-interaction industry-5 best-paper-award Updated Jul 30, 2026 HTML

thellmwhisperer / human.md Star 20 A framework for healthy human-agent collaboration. Tell your AI coding agent when to stop helping you. ai developer-tools mental-health ai-safety human-ai-interaction constitutional-ai claude-code Updated Apr 10, 2026 Python

A framework for healthy human-agent collaboration. Tell your AI coding agent when to stop helping you.

AmirhosseinHonardoust / Mobile-AI-Satisfaction-Behavior-Aanalysis Star 19 Deep behavioral and machine learning analysis explaining why mobile users systematically report lower satisfaction with AI systems. Includes SHAP explainability, cognitive load modeling, device-context effects, interaction metadata analysis, and end-to-end reproducible research code and visuals. python data-science machine-learning random-forest mobile-analytics data-visualization hci feature-engineering user-experience model-interpretation explainable-ai ux-research shap behavioral-analytics human-ai-interaction behavioral-science cognitive-load interaction-analysis satisfaction-modeling context-aware-ml Updated Dec 7, 2025

Deep behavioral and machine learning analysis explaining why mobile users systematically report lower satisfaction with AI systems. Includes SHAP explainability, cognitive load modeling, device-context effects, interaction metadata analysis, and end-to-end reproducible research code and visuals.

AmirhosseinHonardoust / AI-Assistant-Satisfaction-Prediction-Engine Star 18 A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard. data-science machine-learning random-forest data-visualization feature-engineering model-evaluation classification-model explainable-ai shap ml-pipeline ml-ops streamlit ux-analytics user-satisfaction behavioral-analysis time-series-features human-ai-interaction behavioral-modeling ai-analytics prediction-engine Updated Jul 4, 2026 Python

A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.

Stanford-ILIAD / Conventions-ModularPolicy Star 15 PyTorch implementation for "On the Critical Role of Conventions in Adaptive Human-AI Collaboration", ICLR 2021 conventions collaboration multiagent-reinforcement-learning modular-networks human-ai-interaction Updated Mar 9, 2021 Python

PyTorch implementation for "On the Critical Role of Conventions in Adaptive Human-AI Collaboration", ICLR 2021

Mohil-Wankar / meetai Star 14 MeetAI is an AI-powered conversational platform that enables real-time voice interactions with context-aware agents using modern web technologies and scalable cloud infrastructure. react typescript ai nextjs web-app postgresql saas artificial-intelligence openai conversational-ai realtime-api voice-ai openai-api human-ai-interaction inngest drizzle-orm agentic-ai Updated Jun 6, 2026 TypeScript

MeetAI is an AI-powered conversational platform that enables real-time voice interactions with context-aware agents using modern web technologies and scalable cloud infrastructure.

ymetz / rlhfblender Star 14 RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback react python reinforcement-learning experimentation human-ai-interaction reinforcement-learning-from-human-feedback Updated Oct 23, 2026 Python

4. Neural Network Backbone, Layer Specifications & Loss Formulations

RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback

To associate your repository with the human-ai-interaction topic, visit your repo's landing page and select "manage topics."

Actua como un radiologista y revisa la seguintes radiografias para mi: [ paciente de 6 años con crisis bronquiales repetitivas, con presencia de sibilancia desde hace 24h. Optimizalo para hacerlo lo mejor y haz las preguntas que consideres necesarias antes de proceder]

Act as a radiologist and review the following x-rays for me: [6-year-old patient with repetitive bronchial attacks, wheezing for 24 hours. Optimize it to do the best and ask any questions you feel necessary before proceeding]

NX-AI / xlstm Star 2.2k Official repository of the xLSTM. nlp machine-learning deep-learning rnn llm deep-learning-architecture Updated Oct 24, 2026 Python

NanboLi / FACTS Star 32 [ICLR 2025] Implementation of "FACTS: A Factored State-Space Framework For World Modelling" machine-learning artificial-intelligence neural-networks world-modeling deep-learning-architecture Updated Jun 2, 2025 Python

[ICLR 2025] Implementation of "FACTS: A Factored State-Space Framework For World Modelling"

ShubhrangshuGhosh2000 / mat_p2ip_prj Star 5 Contains code for the paper "MaTPIP: a deep-learning architecture with eXplainable AI for sequence-driven, feature mixed protein-protein interaction prediction" explainable-ai protein-language-model deep-learning-architecture protein-protein-interaction-prediction protein-sequence-features Updated Jan 25, 2024 Python

Contains code for the paper "MaTPIP: a deep-learning architecture with eXplainable AI for sequence-driven, feature mixed protein-protein interaction prediction"

Andrew-Bonilla / conductor-simulator Star 4 A real-time gesture-controlled orchestra system. Wave your arms in front of a webcam and control the tempo and volume of a live orchestral rendering of Beethoven's 5th Symphony using deep learning. music classifier deep-learning lstm mlp conducting deep-learning-architecture Updated May 9, 2026 Python

5. Training Protocol, Convergence Behavior & Experimental Evaluation

A real-time gesture-controlled orchestra system. Wave your arms in front of a webcam and control the tempo and volume of a live orchestral rendering of Beethoven's 5th Symphony using deep learning.

sarowarahmed / ImageClassification-using-CNN-and-MLP-on-MNIST-and-FashionMNIST-Datasets Star 0 This project showcases the implementation and comparison of Convolutional Neural Networks (CNN) and Multi-Layer Perceptrons (MLP) for image classification on the MNIST and Fashion MNIST datasets. It includes experiments with hyperparameter tuning, model evaluation through accuracy/loss plots, and confusion matrices. tensorflow data-visualization data-preprocessing hyperparameter-tuning model-evaluation deep-learning-architecture Updated Sep 28, 2024 Jupyter Notebook

This project showcases the implementation and comparison of Convolutional Neural Networks (CNN) and Multi-Layer Perceptrons (MLP) for image classification on the MNIST and Fashion MNIST datasets. It includes experiments with hyperparameter tuning, model evaluation through accuracy/loss plots, and confusion matrices.

sighthough / Global-Trajectory-Anchor-Ai-architecture Star 0 Global Trajectory-Anchor Ai architecture is the evolution of the transformers attention mechanism pytorch state-space-models ai-research transformer-architecture model-optimization model-distillation efficient-transformers deep-learning-architecture long-context-llm slm-optimization kv-cache-optimization Updated Oct 14, 2026 HTML

Global Trajectory-Anchor Ai architecture is the evolution of the transformers attention mechanism

To associate your repository with the deep-learning-architecture topic, visit your repo's landing page and select "manage topics."

The Guide to AI Models, Libraries, and Frameworks: Building a Custom AI Architecture Table of Contents Introduction to AI and Its Evolution Types of AI Models Supervised Learning Unsupervised Learning Reinforcement Learning Deep Learning Models Generative AI Models Popular AI Libraries & Frameworks Core Machine Learning Libraries Deep Learning Frameworks Specialized AI Libraries Deployment & Production Tools Building a Custom AI Framework (Like CEWAI) Data Pipeline Architecture Model Training & Optimization Model Serving & APIs Monitoring & Scaling End-to-End AI System Workflow Emerging Trends in AI (2024-2025) Conclusion & Future of AI 1. Introduction to AI and Its Evolution Artificial Intelligence (AI) has evolved from simple rule-based systems to advanced deep learning models capable of human-like reasoning. The journey includes: 1950s-1980s : Symbolic AI (Expert Systems). 1990s-2000s : Machine Learning (SVM, Random Forest). 2010s-Present : Deep Learning (Neural Networks, Transformers). 2020s-Future : Generative AI (LLMs, Multimodal AI). Today, AI powers ChatGPT, self-driving cars, healthcare diagnostics, and financial forecasting . To harness AI, we need models, libraries, and frameworks —let’s explore them in detail. 2. Types of AI Models A. Supervised Learning Definition : Learns from labeled data (input-output pairs). Models : Linear Regression (Predicting continuous values). Logistic Regression (Binary classification). Decision Trees & Random Forest (Non-linear data). XGBoost/LightGBM (Winning ML competitions). Use Cases : Spam detection, sales forecasting. B. Unsupervised Learning Definition : Finds patterns in unlabeled data. Models : K-Means Clustering (Customer segmentation). PCA (Principal Component Analysis) (Dimensionality reduction). Apriori Algorithm (Market basket analysis). Use Cases : Anomaly detection, recommendation systems. C. Reinforcement Learning (RL) Definition : Learns via rewards/punishments. Models : Q-Learning (Basic RL). Deep Q-Networks (DQN) (Atari game-playing AI). PPO (Proximal Policy Optimization) (Robotics). Use Cases : Autonomous vehicles, game AI. D. Deep Learning Models 1. Computer Vision (CV) Models Convolutional Neural Networks (CNNs) : Image classification (ResNet, EfficientNet). YOLO (You Only Look Once) : Real-time object detection. Vision Transformers (ViT) : Beats CNNs in some tasks. 2. Natural Language Processing (NLP) Models RNN/LSTM : Sequential data (older NLP). Transformer Models : BERT (Bidirectional understanding). GPT-4 (Text generation). T5 (Text-to-text tasks). 3. Generative AI Models GANs (Generative Adversarial Networks) : Fake image generation (StyleGAN). Diffusion Models : Stable Diffusion, DALL·E. LLMs (Large Language Models) : ChatGPT, Claude, Gemini. 3. Popular AI Libraries & Frameworks A. Core Machine Learning Libraries Scikit-Learn Best for traditional ML (SVM, Random Forest). Simple API: fit() , predict() . XGBoost Optimized gradient boosting for tabular data. StatsModels Statistical modeling (hypothesis testing). B. Deep Learning Frameworks TensorFlow (Google) Industry-standard, supports production deployment. Keras (high-level API) for quick prototyping. PyTorch (Meta) Research-friendly, dynamic computation graphs. Used by OpenAI, Hugging Face. JAX (Google) Accelerated numerical computing (used in AlphaFold). C. Specialized AI Libraries Hugging Face Transformers 100,000+ pre-trained NLP models (BERT, GPT-2). OpenCV Computer vision (face detection, object tracking). LangChain Framework for LLM-powered apps (RAG, AI agents). D. Deployment & Production Tools FastAPI/Flask Build REST APIs for AI models. ONNX Runtime Run models across platforms (TensorFlow → PyTorch). MLflow Track experiments, manage model versions. 4. Building a Custom AI Framework (Like CEWAI) Step 1: Data Pipeline Data Collection : Scrapy, BeautifulSoup. Preprocessing : Pandas, NumPy, OpenCV. Feature Engineering : FeatureTools, Scikit-Learn. Step 2: Model Training Hyperparameter Tuning : Optuna, Ray Tune. Distributed Training : Horovod, PyTorch Lightning. Step 3: Model Serving API Layer : FastAPI + Docker. Model Optimization : TensorRT, Quantization. Step 4: Monitoring & Scaling Logging : Weights & Biases (W&B). Scaling : Kubernetes, AWS SageMaker. 5. End-to-End AI System Workflow Data Ingestion → Kafka, Apache Spark. Training → PyTorch + MLflow tracking. Deployment → FastAPI + ONNX Runtime. Monitoring → Grafana + Prometheus. 6. Emerging Trends in AI (2024-2025) Multimodal AI : GPT-4V (text + images). AI Agents : AutoGPT, Devin (AI software engineer). Small Language Models (SLMs) : Phi-3, Mistral 7B. Quantum Machine Learning : TensorFlow Quantum. 7. Conclusion & Future of AI AI is shifting from narrow AI (single-task) to Artificial General Intelligence (AGI) . Key takeaways: ✅ Choose the right model (CNN for images, Transformers for text). ✅ Use frameworks like PyTorch/TensorFlow for scalability. ✅ Build MLOps pipelines for reproducibility. The future lies in self-improving AI systems —stay updated! 🚀

Artificial Intelligence (AI) has evolved from simple rule-based systems to advanced deep learning models capable of human-like reasoning. The journey includes:

Today, AI powers ChatGPT, self-driving cars, healthcare diagnostics, and financial forecasting . To harness AI, we need models, libraries, and frameworks —let’s explore them in detail.

AI is shifting from narrow AI (single-task) to Artificial General Intelligence (AGI) . Key takeaways: ✅ Choose the right model (CNN for images, Transformers for text). ✅ Use frameworks like PyTorch/TensorFlow for scalability. ✅ Build MLOps pipelines for reproducibility.

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