interactive agents

DataFunTalk

Apr 4, 2024 · Artificial Intelligence

Enhancing Interactive Agents with Large Language Models: The SwiftSage Framework

This article reviews the challenges of textual‑only large language model interaction, introduces benchmark environments such as AFL World and ScienceWorld, compares baseline reinforcement‑learning approaches, and presents SwiftSage—a hybrid system that combines a fast T5‑based small model with a powerful LLM for planning and grounding, demonstrating superior performance, efficiency, and cost‑effectiveness while outlining current limitations and future research directions.

SwiftSageaibenchmark

0 likes · 22 min read

Enhancing Interactive Agents with Large Language Models: The SwiftSage Framework

DataFunTalk

Mar 7, 2024 · Artificial Intelligence

Enhancing Interactive Agents with Large Language Models: The SwiftSage Framework and Benchmark Analysis

This article reviews recent advances in using large language models for interactive embodied agents, introduces the SwiftSage dual‑model framework that combines a fast T5‑based small model with a powerful LLM for planning, evaluates it on benchmarks such as AFL World and ScienceWorld, and discusses efficiency, cost‑effectiveness, limitations, and future research directions.

SwiftSageaibenchmark

0 likes · 23 min read

Enhancing Interactive Agents with Large Language Models: The SwiftSage Framework and Benchmark Analysis

DataFunSummit

Jan 27, 2024 · Artificial Intelligence

Enhancing Interactive Agents with Large Language Models: The SwiftSage Framework

This article reviews recent advances in using large language models for embodied interactive agents, introduces the dual‑modality SwiftSage architecture that combines a fast T5‑based small model with a powerful large model for planning and grounding, and evaluates its performance on benchmarks such as ScienceWorld.

AI2SwiftSagebenchmark

0 likes · 23 min read