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Austin V Huang

2 accepted papers

2024

A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis

ICLR 2024oral

Pre-trained large language models (LLMs) have recently achieved better generalization and sample efficiency in autonomous web automation. However, the performance on real-world websites has still suffered from (1) open domainness, (2) limited context length, and (3) lack of inductive bias on HTML. W…

Cited by 233SourcePDFScholar
2023

Understanding HTML with Large Language Models

EMNLP 2023long findings

Large language models (LLMs) have shown exceptional performance on a variety of natural language tasks. Yet, their capabilities for HTML understanding – i.e., parsing the raw HTML of a webpage, with applications to automation of web-based tasks, crawling, and browser-…

Cited by 0SourceScholar