LLMs are General Asynchronous Agents

arXiv:2609.35427 · cs.LG, cs.CL · Submitted 2026-09-28 · Read on arXiv

cs.LG, cs.CL

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/dvmazur/async_llm

Terminology

• Decode — 20× in this paper · explained in 2 episodes
• Transformer — 13× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• KV cache — 11× in this paper · explained in 3 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Generative AI — 7× in this paper · explained in 2 episodes
• Quantization — 7× in this paper · explained in 12 episodes
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Foundation Model — 6× in this paper · explained in 3 episodes
• AI Agents — 5× in this paper · explained in 2 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Sparse Attention — 4× in this paper · explained in 5 episodes
• Steering — 4× in this paper · explained in 2 episodes
• AUC — 3× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Elias — 3× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Speculative Decoding — 3× in this paper · explained in 2 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Gated Delta Nets — 2× in this paper
• Generative Model — 2× in this paper · explained in 2 episodes
• Active Perception — 1× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Commentary — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• DeepSeek Sparse Attention — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Frozen model — 1× in this paper · explained in 3 episodes
• Full-duplex interaction — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Grouped-Query Attention — 1× in this paper
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Multi-head Latent Attention — 1× in this paper
• Qwen Sparse Attention — 1× in this paper
• Self-consistency — 1× in this paper · explained in 2 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Laguna M.1/XS.2 Technical Report
• Gemini Robotics: Bringing AI into the Physical World
• SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills
• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
• GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
• Longformer: The Long-Document Transformer
• Better speech synthesis through scaling
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• LLM-Based Generalizable Hierarchical Task Planning and Execution for Heterogeneous Robot Teams with Event-Driven Replanning
• Interruption Handling for Conversational Robots
• MapQA: A Dataset for Question Answering on Choropleth Maps
• Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
• Moshi: a speech-text foundation model for real-time dialogue
• Extreme Compression of Large Language Models via Additive Quantization
• DualVLA: Building a Generalizable Embodied Agent via Partial Decoupling of Reasoning and Action
• GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
• Gemma 4 Technical Report
• Asynchronous LLM Function Calling
• Asynchronous Tool Usage for Real-Time Agents
• Robotouille: An Asynchronous Planning Benchmark for LLM Agents

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