Papers by Jaewoong Yun

3 papers
FlashAdventure: A Benchmark for GUI Agents Solving Full Story Arcs in Diverse Adventure Games (2025.emnlp-main)

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Challenge: Existing game benchmarks lack diversity and evaluate GUI agents on completing entire storylines.
Approach: They propose a benchmark of 34 Flash-based adventure games to test full story arc completion and tackle observation-behavior gap.
Outcome: The proposed benchmarks show GUI agents struggle with full story arc completion while others improve on observation-behavior gaps.
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models (2024.eacl-long)

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Challenge: Abstractive summarization models generate factually inconsistent content when parametric knowledge conflicts with knowledge in the input document.
Approach: They propose a method to enhance factual adaptiveness while achieving factual consistency on original datasets.
Outcome: The proposed method improves factual adaptiveness while achieving factual consistency on original datasets.
Model Intrinsic Features of Fine-tuning based Text Summarization Models for Factual Consistency (2023.findings-acl)

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Challenge: a summarization model with relatively low factual consistency is more likely to model summaries that are not conditional to the documents.
Approach: They analyze the model intrinsic features by varying the fine-tuning objectives and datasets.
Outcome: The proposed models have a high inductive bias for factual consistency and are more likely to model summaries that are not conditional to the documents.

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