Gradient Bang
Summary
Gradient Bang is a massively multiplayer game where players interact with an LLM to play.
Similar Articles
We have built the first of it's kind interactive blog for matching open-source LLMs to GPUs.
AgentSwarms launched an interactive, gamified blog that helps users match open-source LLMs to the right GPU by calculating VRAM requirements based on model size and quantization, turning infrastructure planning into an engaging experience.
MTG Bench: Testing how well LLMs can play Magic
MTG Bench evaluates how well LLMs can play Magic: The Gathering using an MCP server for library operations, showing both successes and failures in complex game actions.
CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement
CollabBench is a new benchmark for evaluating and training LLM agents in cooperative games, featuring diverse player simulation and a collaborative training paradigm. Experiments show 19.5% higher efficiency and 24.4% improved affective performance over base models.
Evalatro: an open benchmark where LLMs play the real Balatro
Evalatro is an open benchmark where LLMs play the real game Balatro via a text-based interface, with fixed seeds, a public leaderboard, and the goal of clearing Ante 12. Early results show models struggle, with none reaching the target.
Accelerating LMO-Based Optimization via Implicit Gradient Transport
This paper proposes LMO-IGT, a new class of stochastic optimization methods that accelerates convergence using implicit gradient transport while maintaining a single-gradient-per-iteration structure. It introduces a unified theoretical framework and demonstrates improved performance over existing LMO-based optimizers like Muon.