Awesome List Updates on Dec 11, 2022

5 awesome lists updated today.

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1. Awesome Chatgpt

Use ChatGPT Anywhere / Chatbots

• gpt-ai-assistant (⭐7.7k) (Chinese content): Run your own GPT LINE bot on Vercel in 10 minutes.

2. Awesome Vite

Vue / Ecosystem

• unplugin-vue-i18n (⭐260) - Integration for Vue I18n.

3. Awesome Zsh Plugins

Themes / superconsole - Windows-only

• gus (⭐0) - Hackable transient theme. Includes decorators for conda, git information and current directory.

4. Awesome Yew

Crates / Frameworks

• stackable (⭐22) - A framework experience for Yew.

5. Awesome Agi Cocosci

Bayesian Modeling / Bayesian Induction

• Testing a Bayesian Measure of Representativeness Using a Large Image Database - NeurIPS'11, 2011. [All Versions].

Bayesian Modeling / Generative Model

• Learning Latent Space Energy-Based Prior Model - NeurIPS'20, 2020. [All Versions]. [Project]. [Code (⭐36)]. A milestone paper on Latent Energy-Based Model.

Bayesian Modeling / Nonparametric Model

• Hierarchical topic models and the nested Chinese restaurant process - NeurIPS'03, 2003. [All Versions]. The original paper for nested Chinese restaurant process.

Communications / Language Compositionality

• Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols - NeurIPS'18, 2018. [All Versions].

Problem Solving / Human-Level Problem Solving

• Physion: Evaluating Physical Prediction from Vision in Humans and Machines - NeurIPS'21, 2021. [All Versions].

Problem Solving / Intrinsic Motivation

• Intrinsically Motivated Reinforcement Learning - NeurIPS'04, 2004. [All Versions]. A comprehensive review on intrinsic reward functions in classic reinforcement learning.

• Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning - NeurIPS'15, 2015. [All Versions]. The original paper on empowerment as intrinsic motivation.

Problem Solving / Reinforcement Learning

• A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation - NeurIPS'19, 2019. [All Versions].

• Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability - NeurIPS'21, 2021. [All Versions]. A formal treatment on the generalization problem in reinforcement learning.

• On the Expressivity of Markov Reward - NeurIPS'21, 2021. [All Versions]. A formal treatment of tasks and rewards in reinforcement learning modeling.

System 1 & System 2 / Neural-Symbolic AI

• DeepProbLog: Neural Probabilistic Logic Programming - NeurIPS'18, 2018. [All Versions]. The original paper on neuro-symbolic probabilistic programming.

• Bridging Machine Learning and Logical Reasoning by Abductive Learning. - NeurIPS'19, 2019. [All Versions]. [Slides]. [Code (⭐99)]. The original paper on Abductive Learning, a derivative-free approach for neuro-symbolic learning.

• Learning by Abstraction: The Neural State Machine - NeurIPS'19, 2019. [All Versions].

• Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components - NeurIPS'19, 2019. [All Versions].

• Understanding Deep Architectures with Reasoning Layer - NeurIPS'20, 2020. [All Versions].

• Compositional Generalization via Neural-Symbolic Stack Machines - NeurIPS'20, 2020. [All Versions].

• Learning Compositional Rules via Neural Program Synthesis - NeurIPS'20, 2020. [All Versions].

• Discovering Symbolic Models from Deep Learning with Inductive Biases - NeurIPS'20, 2020. [All Versions].

• Visual Concept-Metaconcept Learning - NeurIPS'19, 2019. [All Versions].

Explainability / Explainable Deep Learning

• Compositional Explanations of Neurons - NeurIPS'20, 2020. [All Versions]. [Project (⭐25)]. A concept-composition version of network dissection.

• This Looks Like That: Deep Learning for Interpretable Image Recognition - NeurIPS'19, 2019. [All Versions].

• Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation - NeurIPS'18, 2018. [All Versions]. Maching the learned pattern of neurons in different neural networks.

Meta-Level Considerations / Meta Learning

• Bayesian Model-Agnostic Meta-Learning - NeurIPS'18, 2018. [All Versions]. A Bayesian account on MAML.

• On Effective Scheduling of Model-based Reinforcement Learning - NeurIPS'21, 2021. [All Versions].

Theory of Mind / AI Assisted Research

• Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others - NeurIPS'21, 2021. [All Versions].

Analogy / AI Assisted Research

• VISALOGY: Answering Visual Analogy Questions - NeurIPS'15, 2015. [All Versions].

Commonsense / Intuitive Physics

• PHYRE: A New Benchmark for Physical Reasoning - NeurIPS'19, 2019. [All Versions]. A benchmark for AI physical reasoning.

Knowledge Representation / Commonsense Knowledgebase

• Unsupervised Structure Learning of Stochastic And-Or Grammars - NeurIPS'13, 2013. [All Versions].

Learning in the Open World / Commonsense Knowledgebase

• Energy-Based Models for Continual Learning - NeurIPS'20, 2020. [All Versions]. [Project].

• A causal view of compositional zero-shot recognition - NeurIPS'20, 2020. [All Versions].

Learning with Cognitive Plausibility / Commonsense Knowledgebase

• Self-supervised Learning Through the eyes of a Child - NeurIPS'20, 2020. [All Versions]. Concept learning through near-natural co-occurrence frequency estimation.

• BONGARD-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning - NeurIPS'20, 2020. [All Versions].

• Attention over Learned Object Embeddings Enables Complex Visual Reasoning - NeurIPS'21, 2021. [All Versions].

• Distributed Representations of Words and Phrases and their Compositionality - NeurIPS'13, 2013. [All Versions].

• Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals - NeurIPS'20, 2020. [All Versions].

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