When Agents Disagree With Themselves: Measuring Behavioral Consistency in LLM-Based Agents | ScienceToStartup | ScienceToStartup

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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

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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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When Agents Disagree With Themselves: Measuring Behavioral Consistency in LLM-Based Agents

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Founder's Pitch

"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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When Agents Disagree With Themselves: Measuring Behavioral Consistency in LLM-Based Agents

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References (10)

Founder's Pitch

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

Commercial Viability Breakdown

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