Papers by Bangde Du

2 papers
SimVBG: Simulating Individual Values by Backstory Generation (2025.emnlp-main)

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Challenge: Large language models (LLMs) have strong human-like capabilities, but rarely simulating individualized human values.
Approach: They propose a framework that simulates individual values based on individual backstories . they use structured data on an individual to transform their backstoried information to a backstory .
Outcome: The proposed framework improves top-1 accuracy by more than 10% over retrieval-augmented generation methods.
TwinVoice: A Multi-dimensional Benchmark Towards Digital Twins via LLM Persona Simulation (2026.findings-acl)

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Challenge: Existing studies show that advanced LLMs produce text indistinguishable from human writing.
Approach: They propose a benchmark to assess persona simulation across diverse contexts by decomposing the evaluation into six fundamental capabilities including opinion consistency, memory recall, logical reasoning, persona tone, and syntactic style.
Outcome: The proposed model achieves moderate accuracy but falls short of the basic capabilities needed to simulate personas in real-world contexts.

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