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References (10)

[1]
AI Agents That Matter
2024Sayash Kapoor, Benedikt Stroebl et al.
[2]
τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
2024Shunyu Yao, Noah Shinn et al.
[3]
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
2023Qingyun Wu, Gagan Bansal et al.
[4]
WebArena: A Realistic Web Environment for Building Autonomous Agents
2023Shuyan Zhou, Frank F. Xu et al.
[5]
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
2023Lorenz Kuhn, Y. Gal et al.
[6]
Toolformer: Language Models Can Teach Themselves to Use Tools
2023Timo Schick, Jane Dwivedi-Yu et al.
[7]
ReAct: Synergizing Reasoning and Acting in Language Models
2022Shunyu Yao, Jeffrey Zhao et al.
[8]
Language Models (Mostly) Know What They Know
2022Saurav Kadavath, Tom Conerly et al.
[9]
Self-Consistency Improves Chain of Thought Reasoning in Language Models
2022Xuezhi Wang, Jason Wei et al.
[10]
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
2018Zhilin Yang, Peng Qi et al.

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"This paper offers insights into behavioral consistency of LLM-based agents like GPT-4o and suggests that consistency monitoring could enhance reliability."

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