Papers with future exploration

2 papers
Smurfs: Multi-Agent System using Context-Efficient DFSDT for Tool Planning (2025.naacl-long)

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Challenge: Teaching large language models to use tools for solving complex problems can grant them human-like reasoning abilities.
Approach: They propose a multi-agent system that enhances the Deep First Search Decision Tree (DFSDT) to address issues like error propagation and limited exploration in ReAct .
Outcome: The proposed system reduces token usage by 60.9% compared to existing methods and performs on par with GPT-4-DFSDT.
GuoFeng: A Benchmark for Zero Pronoun Recovery and Translation (2022.emnlp-main)

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Challenge: ZPs are often omitted when they can be pragmatically or grammatically inferred from intraand inter-sentential contexts.
Approach: They propose a benchmark testset for target evaluation on Chinese-English ZP translation.
Outcome: The proposed testset covers five genres and identifies current challenges for evaluation.

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