Awesome List Updates on Oct 15, 2024

13 awesome lists updated today.

1. Static Analysis

Griffe — Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API.

Cryptography 101: Building Blocks - This introductory course (Fall 2024) by Alfred Menezes covers the fundamental cryptographic primitives: symmetric-key encryption, hash functions, MACs, authenticated encryption, public-key encryption, signatures, key agreement, RSA, elliptic curve cryptography.

openai/swarm (⭐20k): Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

AIZU ONLINE JUDGE - A Japanese online judge from the University of Aizu, offering a wide range of algorithmic challenges.

Beecrowd - The Largest Competitive Programming and Online Code Judgement Platform in Latin America.

🐙 Performance Decorators (⭐46) - A collection of TypeScript decorators for performance optimization, including execution time logging, memory usage monitoring, and more.

vue-pagination (⭐7) - A non-style pagination with composable that can integrate with any frameworks.

bartekjaszczak/luma-nvim - A colorful theme with dark/light modes and adjustable contrast. Supports Tree-sitter and semantic highlighting.

njayman/season.nvim (⭐2) - A lightweight plugin to manage session based on current working directory.

AGENT: A Benchmark for Core Psychological Reasoning - ICML'21, 2021. [All Versions]. Inspired by cognitive development studies on intuitive psychology, this paper presents a benchmark consisting of a large dataset of procedurally generated 3D animations, AGENT (Action, Goal, Efficiency, coNstraint, uTility), structured around four scenarios (goal preferences, action efficiency, unobserved constraints, and cost-reward trade-offs) that probe key concepts of core intuitive psychology. The results suggest that to pass the designed tests of core intuitive psychology at human levels, a model must acquire or have built-in representations of how agents plan, combining utility computations and core knowledge of objects and physics.

Learning Triadic Belief Dynamics in Nonverbal Communication from Videos - CVPR'21, 2021. [All Versions]. [Preprint]. This paper incorporates different nonverbal communication cues (e.g., gaze, human poses, and gestures) to represent, model, learn, and infer agents' mental states from pure visual inputs. Crucially, such a mental representation takes the agent's belief into account so that it represents what the true world state is and infers the beliefs in each agent's mental state, which may differ from the true world states. By aggregating different beliefs and true world states, the model essentially forms "five minds" during the interactions between two agents. This "five minds" model differs from prior works that infer beliefs in an infinite recursion; instead, agents' beliefs are converged into a "common mind". Based on this representation, this work further devises a hierarchical energy-based model that jointly tracks and predicts all five minds. From this new perspective, a social event is interpreted by a series of nonverbal communication and belief dynamics, which transcends the classic keyframe video summary.