4 papers
LLMs are General Asynchronous Agents
George Yakushev, Denis Mazur, Vladimir Bartenev +4
Modern LLMs are increasingly capable as autonomous agents, but they follow sequential interaction cycles: read, think, reply or call tools, repeat. Many real-world use cases are no…
Asynchronous Reasoning: Training-Free Interactive Thinking LLMs
George Yakushev, Nataliia Babina, Masoud Vahid Dastgerdi +4
Many state-of-the-art LLMs are trained to think before giving their answer. Reasoning can greatly improve language model capabilities, but it also makes them less interactive: give…
Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data
George Yakushev, Alina Shutova, Ivan Rubachev +3
Tabular foundation models are becoming increasingly popular for low-resource tabular problems. These models make up for small training datasets by pretraining on large volumes of s…
Hogwild! Inference: Parallel LLM Generation via Concurrent Attention
Gleb Rodionov, Roman Garipov, Alina Shutova +6
Large Language Models (LLMs) have demonstrated the ability to tackle increasingly complex tasks through advanced reasoning, long-form content generation, and tool use. Solving thes…