A comprehensive community-maintained collection of PhD advice links covering admissions, research, writing, and academic career preparation. No code, just curated wisdom.
This repo implements academic paper planning and writing as a two-phase Claude Code skill pipeline with a 35-point quality rubric enforced by Python scripts at each stage.
gnnpapers is a curated, community-recognized bibliography of 800+ must-read graph neural network papers. It organizes GNN research evolution and applications without any code.
LiveTradeBench benchmarks LLM trading agents like GPT and Claude in live US equity and prediction markets with real-time news and sentiment integration.
LLM4Pentest aggregates 40+ research papers and tools tracking the evolving role of LLMs in automated penetration testing, highlighting progress and limitations.
A curated and frequently updated bibliography accompanying the IJCAI 2024 survey paper on LLM-based multi-agent systems, organizing research into five key categories and revealing emerging trends.
Awesome-GraphRAG is a curated repository organizing graph-based retrieval-augmented generation methods, with a taxonomy, benchmark, and original research from DEEP-PolyU.
llm-wiki is a shell-based orchestration layer that turns LLM agents into a persistent, multi-agent research wiki. Supports up to 10 agents, deep investigations, and durable provenance tracking.
open-researcher is a TypeScript app combining AI APIs and web scraping to assist research workflows. It offers an extensible setup and local dev server for experimentation.
StereoWorld uses binocular stereo vision cues to guide 3D-consistent stereo video generation, offering a biologically inspired approach to scene geometry understanding.
The Awesome-LLM-Ensemble repo catalogs research on combining multiple LLMs with a clear three-phase taxonomy: before, during, and after inference ensemble methods.
PAT3D composes a 9-stage pipeline combining LLMs, vision models, 3D asset generators, and physics simulation to produce physically plausible, simulation-ready 3D scenes from text prompts.
