human-ai-interaction

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

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

Papers and online resources related to machine learning fairness

All about human-AI interaction (HCI + AI).

LLM Roleplay: Simulating Human-Chatbot Interaction

A list of research papers of explainable machine learning.

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.

Operational doctrine for practical AI systems design.

给AI伴侣增强时间感的小器官（电脑端专用）

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.

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

Component for Collaborative Intelligence within the project AIREDGIO5.0

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

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.

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.

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

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

This repository provides a summarization of recent empirical studies/human studies that measure human understanding with machine explanations in human-AI interactions.

KSODI — structured, non-normative observation of interaction dynamics between distinguishable entities: attributable events, states, trajectories, drift and relational comparability. Light: reflection; Standard-Eval/Full: Observer layers. v3.5 public reference; validation ongoing.

让 AI 先把问题想清楚，再开始工作。两头乌的思辨对话能力包。