Papers by Tianyi Zhu

4 papers
Complex Numerical Reasoning with Numerical Semantic Pre-training Framework (2025.emnlp-main)

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Challenge: Numerical knowledge graphs (NKGs) are not limited to discrete entity-relation knowledge.
Approach: They propose to combine numerical values and entities to solve multi-hop complex reasoning over incomplete knowledge graphs.
Outcome: The proposed approach handles up to 102 types of complex numerical reasoning queries on three public datasets.
How Many Demonstrations Do You Need for In-context Learning? (2023.findings-emnlp)

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Challenge: Large language models (LLMs) are capable of complex reasoning when given a few input-output demos.
Approach: They use fewer input-output demos for each test query to study ICL . they do not observe significant degradation when using only one randomly chosen demo .
Outcome: The proposed model outperforms multi-demo models on the tasks in 2022.
TheraAgent: Self-Improving Therapeutic Agent for Precise and Comprehensive Treatment Planning (2026.findings-acl)

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Challenge: Existing large language models rely on one-shot output without explicit verification, resulting in rough, incomplete, and potentially unsafe treatment plans.
Approach: They propose an agentic framework that replaces one-shot generation with an iterative generate-judge-refine pipeline.
Outcome: The proposed framework achieves state-of-the-art results on HealthBench, leading in Accuracy and Completeness.
RISK: A Framework for GUI Agents in E-commerce Risk Management (2026.acl-long)

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Challenge: RISK is a framework designed to automate multi-step web interactions in e-commerce risk management.
Approach: a new framework is designed to build and deploy GUI agents for e-commerce risk management . RISK-R1 provides a scalable, domain-specific solution for automating complex web interactions .
Outcome: RISK provides a scalable, domain-specific solution for automating complex web interactions in e-commerce risk management.

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