AGI-Papers

AGI-Papers

A curated archive of breakthroughs in Agents, Architecture, Training, RAG, and On-Device AI.

Stars: 328

Visit
 screenshot

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

README:

๐Ÿš€ AGI-Papers

AGI-Papers Topic Status

Toward Artificial General Intelligence (AGI) in 2026.
A curated archive of breakthroughs in Agents, Architecture, Training, RAG, and On-Device AI.

๐Ÿ“Œ Introduction

2026๋…„, AGI์— ๊ทธ ์–ด๋А ๋•Œ๋ณด๋‹ค ๊ฐ€๊นŒ์šด ์‹œ๋Œ€๊ฐ€ ๋„๋ž˜ํ–ˆ์Šต๋‹ˆ๋‹ค.
์ด ์ €์žฅ์†Œ๋Š” AGI(Artificial General Intelligence) ๋กœ ํ–ฅํ•˜๋Š” ์—ฌ์ •์—์„œ ์ค‘์š”ํ•œ ๋…ผ๋ฌธ๋“ค์„ ๋ฆฌ๋ทฐํ•˜๊ณ  ์•„์นด์ด๋น™ํ•˜๋Š” ๊ณต๊ฐ„์ž…๋‹ˆ๋‹ค.

์ฃผ๋กœ ์ œ LinkedIn ์—์„œ ๋‹ค๋ฃฌ ๋…ผ๋ฌธ๋“ค์— ๋Œ€ํ•œ ์‹ฌ๋„ ์žˆ๋Š” ๋ฆฌ๋ทฐ๊ฐ€ ์—…๋กœ๋“œ๋˜๋ฉฐ, ๋•Œ๋กœ๋Š” ์†Œ์…œ ๋ฏธ๋””์–ด์— ๊ณต์œ ํ•˜๊ธฐ ์ „์˜ Pre-release ์ธ์‚ฌ์ดํŠธ๋‚˜ ๋‚ ๊ฒƒ์˜ ์ƒ๊ฐ๋“ค์ด ์ด๊ณณ์— ๋จผ์ € ๊ธฐ๋ก๋  ์˜ˆ์ •์ž…๋‹ˆ๋‹ค.

๐Ÿ“ Drafts (Work In Progress)

์ž‘์„ฑ ์ค‘์ธ ์ƒˆ๋กœ์šด ๊ธ€๋“ค์€ ์•„๋ž˜ ๋งํฌ์—์„œ ํ™•์ธํ•˜์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

๐Ÿ“‚ Archives

๊ณผ๊ฑฐ์— ์ •๋ฆฌํ–ˆ๋˜ ๋…ผ๋ฌธ ๋ฆฌ์ŠคํŠธ๋Š” ์•„๋ž˜ ๋งํฌ์—์„œ ํ™•์ธํ•˜์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.


๐Ÿ“š Contents

์ด ์ €์žฅ์†Œ๋Š” AGI๋ฅผ ํ–ฅํ•œ ์—ฌ์ •์„ ๋‹ค์Œ 8๊ฐ€์ง€ ํ•ต์‹ฌ ์ฃผ์ œ๋กœ ๋ถ„๋ฅ˜ํ•˜์—ฌ ์ •๋ฆฌํ•ฉ๋‹ˆ๋‹ค.

  • ๐Ÿค– Agents : ์ž์œจ ์—์ด์ „ํŠธ, ํ–‰๋™/๊ณ„ํš(Planning) ๋ชจ๋ธ, ํ”„๋ ˆ์ž„์›Œํฌ
  • ๐Ÿง  Architecture : LLM ์•„ํ‚คํ…์ฒ˜ ํ˜์‹  (Transformer, Mamba, MoE)
  • ๐Ÿ“š Pre-Training : ํ•™์Šต ๋ฐ์ดํ„ฐ, ์Šค์ผ€์ผ๋ง ๋ฒ•์น™, ํŒŒ์šด๋ฐ์ด์…˜ ๋ชจ๋ธ
  • ๐ŸŽฏ Post-Training : RLHF, DPO, GRPO, ์ •๋ ฌ(Alignment)
  • โš–๏ธ Evaluation : ๋ฒค์น˜๋งˆํฌ, ํ‰๊ฐ€ ๋ฐฉ๋ฒ•๋ก , ๋น„ํ‰
  • ๐Ÿ—‚๏ธ RAG & Knowledge : ๊ฒ€์ƒ‰ ์ฆ๊ฐ• ์ƒ์„ฑ, ์ง€์‹ ๊ทธ๋ž˜ํ”„, ๋ฉ”๋ชจ๋ฆฌ
  • ๐Ÿ’ป On-Device AI : ๋กœ์ปฌ ๊ตฌ๋™, ์—ฃ์ง€ ์ปดํ“จํŒ…, ์ตœ์ ํ™”
  • ๐Ÿš€ Projects : ์ง์ ‘ ๊ตฌํ˜„ํ•œ ํ”„๋กœ์ ํŠธ ๋ฐ ์‹คํ—˜ ๊ฒฐ๊ณผ
  • ๐Ÿ”ฅ Trends & Industry : AI ์‚ฐ์—…์˜ ๋™ํ–ฅ, ์ธ์‚ฌ์ดํŠธ, ์ฃผ์š” ๋‰ด์Šค

๐Ÿค– Agents

  • Adaptation of Agentic AI
    ๊ฑฐ๋Œ€ ๋ชจ๋ธ ํŠœ๋‹๋ณด๋‹ค ๋„๊ตฌ ํŠœ๋‹์ด ํšจ์œจ์ ์ธ ์ด์œ  (T2 > A2).
  • Memory in the Age of AI Agents
    ์—์ด์ „ํŠธ ๊ธฐ์–ต์˜ ํ˜•ํƒœ, ๊ธฐ๋Šฅ, ์—ญ๋™์„ฑ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ.
  • World Models Research
    World Knowledge Injection vs Specific Tasks.
  • Mixture-of-Models
    Unifying Heterogeneous Agents via N-Way Self-Evaluating Deliberation.
  • AIRS-Bench
    Frontier AI Research Science Agents๋ฅผ ์œ„ํ•œ ํƒœ์Šคํฌ.
  • OctoTools
    Training-free LLM Agent Framework.
  • Chain-of-Draft(CoD)
    CoT์˜ ์žฅ์ ์„ ์œ ์ง€ํ•˜๋ฉด์„œ ํ† ํฐ ์‚ฌ์šฉ๋Ÿ‰๊ณผ ๊ณ„์‚ฐ ๋น„์šฉ์„ ์ค„์ด๋Š” ํš๊ธฐ์ ์ธ ์ ‘๊ทผ๋ฒ•.
  • Scaling Agent Systems: ๋‹ค๋‹ค์ต์„ ์˜ ํ•จ์ •
    ๊ตฌ๊ธ€๊ณผ MIT๊ฐ€ ๋ฐํ˜€๋‚ธ ๋ฉ€ํ‹ฐ ์—์ด์ „ํŠธ์˜ ๊ณผํ•™.
  • LOTaD: Optimal Task Decomposition
    ์—์ด์ „ํŠธ๋Š” ์–ด๋–ป๊ฒŒ ์ผ์„ ๋‚˜๋ˆ ์•ผ ํ• ๊นŒ?
  • ADGR: Agentic Deep Graph Reasoning
    ์Šค์Šค๋กœ ์ง€๋„๋ฅผ ๊ทธ๋ฆฌ๋Š” ์—์ด์ „ํŠธ.
  • Agentic Reasoning
    ์ƒ๊ฐ์˜ ๋„๊ตฌ๋ฅผ ์“ฐ๋Š” ์—์ด์ „ํŠธ.
  • MetaChain
    Zero-code Framework: ๋ง๋งŒ ํ•˜๋ฉด ๋งŒ๋“ค์–ด์ง€๋Š” ์—์ด์ „ํŠธ.
  • LoRASA: Agent Adaption
    ๋”ฐ๋กœ ๋˜ ๊ฐ™์ด, ์—์ด์ „ํŠธ์˜ ๊ฐœ์ธ๊ธฐ.
  • AgentArcEval
    ์—์ด์ „ํŠธ ์•„ํ‚คํ…์ฒ˜, ์ ์ˆ˜ ๋งค๊ฒจ๋“œ๋ฆฝ๋‹ˆ๋‹ค.
  • SciAgents
    AI ๊ณผํ•™์ž์˜ ํƒ„์ƒ.
  • Agent Workflows (Anthropic)
    ์•คํŠธ๋กœํ”ฝ์ด ์ œ์•ˆํ•˜๋Š” 5๊ฐ€์ง€ ํ•ต์‹ฌ ํŒจํ„ด.
  • ASA: Training-Free Tool Calling
    ๊ฒŒ์œผ๋ฅธ ์—์ด์ „ํŠธ(Lazy Agent)๋ฅผ ๊นจ์šฐ๋Š” ๊ฐ€์žฅ ๊ฐ€๋ฒผ์šด ๋ฐฉ๋ฒ•.
  • HUMANLM: State Alignment for User Simulation
    ์ง„์ •ํ•œ ํŽ˜๋ฅด์†Œ๋‚˜๋Š” '๋งˆ์Œ'์—์„œ ๋‚˜์˜จ๋‹ค.
  • SKILLRL: ์—์ด์ „ํŠธ๋Š” '์‹คํŒจ'๋ฅผ ๋จน๊ณ  ์ž๋ž€๋‹ค
    ์—์ด์ „ํŠธ์—๊ฒŒ ๊ฒฝํ—˜์„ '์Šคํ‚ฌ'๋กœ ์ฆ๋ฅ˜(Distill)ํ•˜์—ฌ ํ‰์ƒ ํ•™์Šต์˜ ๊ธธ์„ ์—ด์–ด์ฃผ๋‹ค.

๐Ÿง  Architecture

๐Ÿ“š Pre-Training

๐ŸŽฏ Post-Training

  • Parameter-Efficient Fine-Tuning for Foundation Models
    ๊ฑฐ๋Œ€ ๋ชจ๋ธ์„ ํšจ์œจ์ ์œผ๋กœ ํŠœ๋‹ํ•˜๋Š” 5๊ฐ€์ง€ ํ•ต์‹ฌ ๊ธฐ๋ฒ•(PEFT) ์ด์ •๋ฆฌ.
  • When Reasoning Meets its Laws
    ๋‹จ 3,900๊ฐœ์˜ ๋ฐ์ดํ„ฐ๋กœ AI์—๊ฒŒ '์ถ”๋ก ์˜ ๋ฌผ๋ฆฌ ๋ฒ•์น™'์„ ๊ฐ€๋ฅด์น˜๋Š” ๋ฒ• (LORE).
  • LIE: ๊นŠ๊ฒŒ ์ƒ๊ฐํ• ์ˆ˜๋ก ๋” ๋˜‘๋˜‘ํ•ด์ง„๋‹ค
    LLM์—๊ฒŒ '์ƒ๊ฐ์„ ๋ฉˆ์ถ”์ง€ ์•Š๋Š” ๋ฒ•'์„ ๊ฐ€๋ฅด์น˜๋Š” ๊ฐ•ํ™”ํ•™์Šต ์ „๋žต.
  • ProRL: Prolonged Reinforcement Learning
    ๊ฐ•ํ™”ํ•™์Šต, ์งง๊ฒŒ ํ•˜์ง€ ๋ง๊ณ  ๊ธธ๊ฒŒ ํ•˜๋ผ. RL ์Šค์ผ€์ผ๋ง ๋ฒ•์น™์˜ ๋ฐœ๊ฒฌ.
  • DuPO: Self-Verification via Dual Preference Optimization
    ์ •๋‹ต์ง€ ์—†๋Š” ๋ฒˆ์—ญ์„ ์Šค์Šค๋กœ ๊ฒ€์ฆํ•˜๋Š” '์ผ๋ฐ˜ํ™”๋œ ์Œ๋Œ€์„ฑ' ๊ธฐ๋ฒ•.
  • From Code Foundation Models to Agents
    Code Foundation Model์—์„œ ์ž์œจ ์ฝ”๋”ฉ ์—์ด์ „ํŠธ๋กœ์˜ ์ง„ํ™” ์ฒญ์‚ฌ์ง„.
  • Emergent Misalignment
    ์ทจ์•ฝํ•œ ์ฝ”๋“œ๋ฅผ ๋ฐฐ์šด AI์˜ ์œ„ํ—˜ํ•œ ์ผํƒˆ.
  • Stabilizing RL with LLMs
    ํ™”๋ คํ•œ ๊ธฐ๊ต๋ณด๋‹ค ์ˆ˜ํ•™์  ๊ธฐ๋ณธ๊ธฐ๊ฐ€ ์ค‘์š”ํ•œ ์ด์œ .
  • Yann LeCun: World Model์˜ ์ค‘์š”์„ฑ
    LLM์€ ๋ฌผ๋ฆฌ ์„ธ๊ณ„๋ฅผ ๋ฐฐ์šธ ์ˆ˜ ์—†๋‹ค?
  • GDPO: Multi-reward RL
    GRPO์˜ ์•ฝ์ ์„ ๊ทน๋ณตํ•œ ์ƒˆ๋กœ์šด ๊ฐ•ํ™”ํ•™์Šต ๊ธฐ๋ฒ•.
  • Detailed balance in LLM-driven agents
    LLM์ด ๋ฌผ๋ฆฌํ•™์˜ '์ตœ์†Œ ์ž‘์šฉ์˜ ์›๋ฆฌ'๋ฅผ ๋”ฐ๋ฅธ๋‹ค๋Š” ๊ฒƒ์„ ์ฆ๋ช…ํ•œ ์—ฐ๊ตฌ.
  • iGRPO
    Self-Feedback-Driven LLM Reasoning: ๋ชจ๋ธ์ด ์Šค์Šค๋กœ ๋งŒ๋“  ์ดˆ์•ˆ์„ ๋ณด๊ณ  ๋ฐฐ์šฐ๋Š” ์ž๊ฐ€ ๊ฐœ์„  ๊ฐ•ํ™”ํ•™์Šต.

โš–๏ธ Evaluation

๐Ÿ—‚๏ธ RAG & Knowledge

๐Ÿ’ป On-Device AI

๐Ÿš€ Projects

๐Ÿค– Autonomous Agents

๐Ÿ› ๏ธ Coding & Dev Tools

๐Ÿ’ป On-Device AI

๐Ÿง  Model Experiments

๐Ÿช„ Post-Training Projects

๐Ÿ’ญ Insights & Essays

๐Ÿ”ฅ Trends & Industry


๐Ÿ“ฌ Connect


Disclaimer: The views and opinions expressed in these reviews are those of the author and do not necessarily reflect the official policy or position of any other agency, organization, employer or company.

For Tasks:

Click tags to check more tools for each tasks

For Jobs:

Alternative AI tools for AGI-Papers

Similar Open Source Tools

For similar tasks

For similar jobs