Graph View

Backlinks

The Library

Search

SearchSearch

The Antilibrary

Feb 25, 2025, 6 min read

File

Paper Queue

  • 2 introduces a new mutual information framework for MARL. This leads to the development of an algorithm called Variational Maximum Mutual Information, Multi-Agent Actor Critic which allows agents to coordinate simultaneous actions without latency.

  • Branching Reinforcement Learning by Du, and Chen (Jun 15, 2022)

  • Vinyals et al. (2019) Grandmaster level in StarCraft II using multi-agent reinforcement learning

  • Wu et al. (2017) Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

  • Ecoclimates — Climate-Response Modeling of Vegetation by Palubicki et al. (2022)

  • Ma et al. (2024) Foundation Methods for Music — A survey

  • Human-level play in the game of Diplomacy

  • All these papers from Large Language Model

    • TransferTransfo — A Transfer Learning Approach for Neural Network based Conversational Agents by Wolf, Sanh, Chaumond, and Delangue (Feb 4, 2019)
    • ⭐ BERT — Pre-Training of Deep Bidirectional Transformer for Language Understanding by Devlin, Chang, Lee, and Toutanova (May 24, 2019)
    • Towards a Human-like Open-Domain Chatbot by Adiwardana et. al (Feb 27, 2020)
    • ⭐ Language Models are Few-Shot Learners by Brown et. al, (Jul. 22, 2020)
    • Dense Passage Retrieval for Open-Domain Question Answering by Karpukhin et. al (Sep 30, 2020)
    • TOD-BERT — Pre-trained Natural Language Understanding for Task-Oriented Dialogue by Wu, Hoi, Socher, and Xiong (November 2020)
    • ⭐Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks by Lewis et. al., (2020)
    • ⭐ LaMDA- Language Models for Dialog Applications by Thoppilan et. al (Feb 10, 2022)
    • Language-Agnostic BERT Sentence Embedding by Feng et. al (Mar 8, 2022)
    • ⭐ Training Compute-Optimal Large Language Models by Hoffmann et. al (Mar 29, 2022)
    • Generating Training Data with Language Models- Towards Zero-Shot Language Understanding by Meng, Huang, Zhang, Han (Oct 12, 2022)
    • ⭐ LLaMA- Open and Efficient Foundation Language Models by Touvron et. al (Feb 27, 2023)
    • ⭐ OpenAGI—When LLM Meets Domain Experts by Ge et. al (Apr 12, 2023)

  • All these papers from Prompt Engineering

    • Commonsense Knowledge Mining from Pretrained Models by Feldman, Davison and Rush (2019)
    • ⭐ Prefix Tuning — Optimizing Continuous Prompts for Generation by Li and Liang (Jan 1, 2021)
    • GPT Understands Too by Liu et. al (Mar 18, 2021)
    • Calibrate Before Use — Improving Few-Shot Performance of Language Models by Zhao et. al (Jun 10, 2021)
    • ⭐Pre-train Prompt and Predict- A systematic survey of prompting methods in Natural Language Processing by Liu et. al (Jul 28, 2021) - A survey of different prompting techniques.
    • KnowPrompt — Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction by Zhang et. al (Jan 23, 2022)
    • P-Tuning v2 - Prompt Tuning can be comparable to Fine-tuning Universally Across Scales and Tasks by Liu et. al (Mar 20, 2022)
    • ⭐ Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models by Wei et. al (Jan 10, 2023)
    • Complexity-Based Prompting for Multi-Step Reasoning by Fu et. al (Jan 30, 2023)

Backlogs

Bookstops

Future Readings

Notemarks

Utilities

  • Beall’s List - provides a list of predatory journals and publishers.

  • Library Genesis - site for searching millions of books

  • Anna’s Archive - site for searching millions of books

  • phind - a search engine that makes use of an LLM under the hood.

  • Pi.ai - an online personal assistant chatbot as an alternative to ChatGPT.

  • [Chat Paper](https://chatpaper.com/) - AI powered tool for reviewing research papers

General Knowledge Repositories

What to Learn?

Curios

Footnotes

  1. Lyu et al. (2023) On Centralized Critics in Multi-Agent Reinforcement Learning ↩

  2. Kim, Jung, Cho, Sung (2020) A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning ↩