Papers by Shunfeng Zheng

3 papers
Spiral of Silence in Large Language Model Agents (2025.findings-emnlp)

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Challenge: Existing theories of Spiral of Silence do not apply to large language models .
Approach: They propose an evaluation framework for examining SoS in large language models . they consider four controlled conditions that vary the availability of "History" and "Persona" signals .
Outcome: The proposed framework examines the SoS-like dynamics in large language models . it shows that history and persona together produce strong majority dominance .
SpatialWebAgent: Leveraging Large Language Models for Automated Spatial Information Extraction and Map Grounding (2025.acl-demo)

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Challenge: Understanding and extracting spatial information from text is vital for a wide range of applications, says nielsen . inherent complexity of geographic expressions in natural language presents significant hurdles for traditional extraction methods.
Approach: They propose a system that leverages large language models to extract spatial information from natural language.
Outcome: SpatialWebAgent is designed to extract, standardize, and ground spatial information from natural language text directly onto maps.
Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving (2025.findings-emnlp)

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Challenge: a new study examines the potential of retrieval-augmented generation (RAG) with foundation models to enhance expert-level reasoning.
Approach: They introduce PhoPile, a high-quality multimodal dataset specifically designed for Olympiad-level physics.
Outcome: The proposed model can be used to solve Olympiad-level physics problems.

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